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  • An Holistic Framework for Shared Design Leadership

    An Holistic Framework for Shared Design Leadership

    Imagine this: Two people are conversing in what appears to be the same pattern issue in a conference room at your software company. One is talking about whether the staff has the proper skills to handle it. The various examines whether the answer really addresses the user’s issue. Similar place, the same issue, and entirely different perspectives.

    This is the lovely, sometimes messy fact of having both a Design Manager and a Guide Designer on the same group. And if you’re wondering how to make this job without creating confusion, coincide, or the feared” to some cooks” situation, you’re asking the right issue.

    Fresh lines on an organizational chart have always been the standard solution. The Design Manager handles persons, the Lead Designer handles art. Problem is fixed, isn’t it? Except for fiction, fresh org charts. In fact, both roles care greatly about crew health, style quality, and shipping great work.

    When you begin to think of your style organization as a style organism, the magic happens when you accept collide rather than fight it.

    The biology of a good design team

    Here’s what I’ve learned from years of being on both flanks of this formula: think of your design team as a living organism. The Design Manager concentrates on the internal security, career advancement, team dynamics, and other factors. The Lead Designer is more focused on the body ( the handiwork, the design standards, the hands-on projects that are delivered to users ).

    But just like mind and body aren’t totally separate systems, but, also, do these tasks overlap in significant ways. Without working in harmony with one another, you didn’t have a healthier person. The technique is to recognize those overlaps and how to understand them gently.

    When we look at how good team really function, three critical devices emerge. Each requires the collaboration of both jobs, but one must assume the lead role in maintaining that system sturdy.

    Folks & Psychology: The Nervous System

    Major caretaker: Design Manager
    Supporting duties: Guide Custom

    The anxious system is all about mental health, feedback, and signals. When this technique is good, information flows easily, people feel safe to take risks, and the staff may react quickly to new problems.

    The main caregiver is around, the Design Manager. They are keeping track of the team’s emotional state, making sure feedback loops are healthier, and creating the environment for growth. They’re hosting job meetings, managing task, and making sure no single burns out.

    However, the Lead Designer has a vital enabling position. They’re offering visual feedback on build development needs, identifying stagnant design skills in someone, and pointing out potential growth opportunities that the Design Manager might overlook.

    Design Manager tends to:

    • development planning and profession conversations
    • internal security and dynamics of the group
    • Overhead management and resource allocation
    • Performance evaluations and opinions management methods
    • Providing learning options

    Direct Custom supports by:

    • Providing craft-specific evaluation of staff member growth
    • identifying opportunities for growth and style talent gaps
    • Providing style mentorship and assistance
    • indicating when staff members are prepared for more challenging problems.

    The Muscular System: Design & Execution

    Major caretaker: Lead Designer
    Supporting duties: Design Manager

    Power, cooperation, and skill development are the hallmarks of the skeletal system. When this technique is healthy, the team can do complicated design work with precision, maintain regular quality, and adjust their craft to fresh challenges.

    The Lead Designer is in charge of everything here. They are raising the bar for quality work, providing craft instruction, and ensuring that shipping work is done to the highest standards. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

    However, the Design Manager has a significant supporting role. They’re making sure the team has the resources and support they need to perform their best work, such as proper nutrition and time for an athlete recovering.

    Lead Designer tends to:

    • Definition of system usage and design standards
    • Feedback on design work that meets the required standards
    • Experience direction for the product
    • Design choices and product-wide alignment are important.
    • advancement of craft and innovation

    Design Manager supports by:

    • ensuring that design standards are understood and accepted by all members of the team
    • Confirming that a direction of experience is being pursued
    • Supporting practices and systems that scale without bottlenecking
    • facilitating team-wide design alignment
    • Providing resources and removing obstacles to outstanding craft work

    The Circulatory System: Strategy &amp, Flow

    Both the lead designer and the design manager were caretakers.

    How do decisions, energy, and information flow through the team according to the circulatory system? When this system is healthy, strategic direction is clear, priorities are aligned, and the team can respond quickly to new opportunities or challenges.

    This is the true partnership that occurs. Although both positions bring unique perspectives, keeping the circulation strong is a dual responsibility.

    Lead Designer contributes:

    • The product fulfills the user’s needs.
    • overall experience and product quality
    • Strategic design initiatives
    • User needs for each initiative are based on research.

    Design Manager contributes:

    • Communication to team and stakeholders
    • Stakeholder management and alignment
    • Team accountability across all levels
    • Strategic business initiatives

    Both parties work together on:

    • Co-creation of strategy and leadership
    • Team goals and prioritization approach
    • organizational structure decisions
    • Success frameworks and measures

    Keeping the Organism Healthy

    Understanding that all three systems must work together is the key to making this partnership sing. A team with excellent craftmanship but poor psychological protection will eventually burn out. A team with great culture but weak craft execution will ship mediocre work. A team that has both but poor strategic planning will concentrate on the wrong things.

    Be Specific About the System You’re Defending.

    When you’re in a meeting about a design problem, it helps to acknowledge which system you’re primarily focused on. Everyone has context for their input.” I’m thinking about this from a team capacity perspective” ( nervous system ) or” I’m looking at this through the lens of user needs” ( muscular system ).

    This is not about staying in your path. It’s about being transparent as to which lens you’re using, so the other person knows how to best add their perspective.

    Create Positive Feedback Loops

    The partnerships that I’ve seen have the most effective feedback loops between the systems:

    Nervous system signals to muscular system:” The team is struggling with confidence in their design skills” → Lead Designer provides more craft coaching and clearer standards.

    Nervous system receives the message” The team’s craft skills are improving more quickly than their project complexity.”

    Both systems communicate to the circulatory system that” We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities.”

    Handle Handoffs Gracefully

    When something switches from one system to another, this partnership’s most crucial moments occur. This might occur when a design standard ( muscular system ) needs to be implemented across the team ( nervous system ) or when a tactical initiative ( circulatory system ) requires specific craft execution ( muscular system ).

    Make these transitions explicit. The new component standards have been defined. Can you give me some ideas for how to get the team up to speed? or” We’ve agreed on this strategic direction. From here, I’ll concentrate on the specific user experience approach.

    Stay original and avoid being a tourist.

    The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both parties to be concerned with the entire organism, even when they are not the primary caregiver.

    This entails asking questions rather than making assumptions. ” What do you think about the team’s craft development in this area”? or” How do you think this is affecting team morale and workload”? keeps both viewpoints present in every choice.

    When the Organism Gets Sick

    Even with clear roles, this partnership can go wrong. What are the most typical failure modes I’ve seen:

    System Isolation

    The design manager ignores craft development and only concentrates on the nervous system. The Lead Designer ignores team dynamics and concentrates solely on the muscular system. Both people retreat to their comfort zones and stop collaborating.

    The signs: Team members receive conflicting messages, work conditions suffer, and morale declines.

    Reconnect with other people’s goals in the treatment. What are you both trying to achieve? Great design work typically arrives on time from a strong team. Discover how both systems accomplish that goal.

    Poor Circulation

    There is no clear strategic direction, shifting priorities, or accepting responsibility for keeping information flowing.

    The signs: Team members are unsure of their priorities, work is duplicated or dropped, and deadlines are missed.

    The treatment: Explicitly assign responsibility for circulation. Who is communicating with whom? How frequently? What’s the feedback loop?

    Autoimmune Response

    The other person’s expertise makes them feel threatened. The Design Manager thinks the Lead Designer is undermining their authority. The Design Manager is allegedly misunderstanding the craft, according to the lead designer.

    The signs: defensive behavior, territorial disputes, team members sucked into the middle.

    The treatment: Remember that you’re both caretakers of the same organism. The entire team suffers when one system fails. The team thrives when both systems are strong.

    The Payoff

    Yes, communication is required for this model. Yes, it requires that both parties be able to assume full responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

    When both roles are well-balanced and functioning well together, you get the best of both worlds: strong people leadership and deep craft knowledge. When one person is ill, taking a vacation, or overburdened, the other can support the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

    The framework has a balance, which is crucial. As your team expands, you can use the same system thinking to new problems. Need to launch a design system? Both the muscular system ( standards and implementation ), the nervous system (team adoption and change management ), and both have a tendency to circulate ( communication and stakeholder alignment ).

    The End result

    The relationship between a Design Manager and Lead Designer isn’t about dividing territories. It’s about multiplying impact. Magic occurs when both roles are aware that they are tending to various components of the same healthy organism.

    The mind and body work together. The team receives both the craft excellence and strategic thinking they need. And most importantly, the work that is distributed to users benefits both sides.

    So the next time you’re in that meeting room, wondering why two people are talking about the same problem from different angles, remember: you’re watching shared leadership in action. And if it’s functioning well, your design team’s mind and body are both strengthening.

  • From SEO to AEO: Todd Sawicki Reveals How AI Is Transforming Search

    From SEO to AEO: Todd Sawicki Reveals How AI Is Transforming Search

    From SEO to AEO: Todd Sawicki Reveals How AI Is Transforming Search written by John Jantsch read more at Duct Tape Marketing

    Listen to the full episode: Overview On this episode of the Duct Tape Marketing Podcast, John Jantsch interviews Todd Sawicki, founder and CEO of Gumshoe AI, a cutting-edge platform helping marketers navigate the rapidly evolving world of AI-driven search and discovery. Todd breaks down what AIO, AEO, and AI search really mean for marketers, why […]

    From SEO to AEO: Todd Sawicki Reveals How AI Is Transforming Search written by John Jantsch read more at Duct Tape Marketing

    Listen to the full episode:

    Todd Sawicki (1)Overview

    On this episode of the Duct Tape Marketing Podcast, John Jantsch interviews Todd Sawicki, founder and CEO of Gumshoe AI, a cutting-edge platform helping marketers navigate the rapidly evolving world of AI-driven search and discovery. Todd breaks down what AIO, AEO, and AI search really mean for marketers, why buyer behavior is shifting, and how brands can optimize for the new era where large language models (LLMs) drive discovery, answers, and conversions. If you’re looking for practical ways to future-proof your SEO and content marketing, this episode is packed with actionable insights and big-picture context.

    About the Guest

    Todd Sawicki is the founder and CEO of Gumshoe AI, a platform at the forefront of AI-driven search and discovery solutions. With a deep background in digital media, marketing technology, and scaling startups, Todd is a sought-after voice on the future of search, LLM optimization, and how marketers can adapt as buyer behavior and search platforms are transformed by AI.

    Actionable Insights

    • AI-driven search (AIO, AEO) is fundamentally changing how buyers search, what they expect, and how marketers must optimize—think “training the AI salesperson” rather than just ranking on Google.
    • LLMs (like ChatGPT, Perplexity, and Google AI Overviews) are increasingly personalizing answers, using your site’s content, FAQs, product detail pages, and structured data to deliver tailored recommendations.
    • AI search users are high-intent and convert at dramatically higher rates—often 2–20x higher than traditional organic or paid search—because they are pre-qualified and further down the funnel.
    • Content quality, structure, and freshness matter more than ever; LLMs reward authoritative, updated, and well-organized information, not just what’s most popular or backlinked.
    • Updating and repurposing existing content (especially with FAQs, schema, and summaries) is critical—LLMs cite content that has been updated within the last 90 days.
    • Competitive insights and personas are key: Tools like Gumshoe can reveal what LLMs say about you, your competitors, and which personas they surface—providing messaging ideas and identifying areas to improve.
    • Focus on high-intent, conversion-focused queries (not just top-of-funnel trends) and use AI insights to build better ad campaigns, content, and product positioning.
    • Track, measure, and iterate: AI traffic is growing fast—use analytics to see where it’s coming from, how it performs, and how your optimizations are working.

    Great Moments (with Timestamps)

    • 01:31 – The Rise of AI Search and Zero-Click Experiences
      How AI-driven search is changing user expectations, buyer behavior, and marketing priorities.
    • 03:21 – Why Buyer Behavior Matters More Than Technology
      Users are asking longer, more complex, and more high-intent questions, and expect personalized answers.
    • 05:18 – The Value of AI Traffic
      Why visitors from AI answers convert at much higher rates—and what marketers should do about it.
    • 06:49 – Training the AI Salesperson
      How to “teach” LLMs about your product, and why product marketing and messaging matter more than old-school SEO tactics.
    • 08:30 – What Content Do LLMs Prefer?
      Brand websites, FAQs, knowledge bases, and structured content are the top sources cited by AI.
    • 09:52 – Why Doing Content Right Pays Off
      How years of quality content and structure are finally being rewarded by AI-driven platforms.
    • 12:26 – Content Freshness, Updates, and Repurposing
      The average AI-cited content is only 86 days old—updating and repurposing is critical for ongoing visibility.
    • 14:42 – How Gumshoe AI Works
      Using personas, synthetic users, and competitive insights to see what LLMs are saying about your business—and what to do next.
    • 20:38 – The Future of High-Intent Search
      Marketers must focus on conversion-ready, long-tail queries and position for the new funnel managed by AI.

    Insights

    “AI-driven search means you have to train the AI like you’d train a salesperson—answer objections, provide detailed info, and position your product for each persona.”

    “Content quality, structure, and freshness are the new currency—LLMs reward the right answers, not just the most popular ones.”

    “Focus on high-intent, conversion-ready queries—AI search gets users further down the funnel, and marketers need to adapt their messaging and content to win.”

    “Analytics prove it: AI-driven visitors stay longer and convert more. Optimize now and track what’s working as AI’s role in discovery grows.”

    “Competitive intelligence and persona insights are critical—know what LLMs say about you and your competitors to improve your messaging and positioning.”

    John Jantsch (00:02.52)

    Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Todd Sawicki. He’s the founder and CEO of Gum Shoe AI, an innovative platform at the forefront of AI-driven search and discovery solutions. With a background in digital media marketing technology and leading high-growth startups, Todd is known for his deep insight into changing landscape of search. We’re going to talk about SEO, we’re going to talk about AIO, AEO, all the

    Other rows that are out there.

    Todd Sawicki (00:33.81)

    As long as we don’t call it GEO, what, you can tell the person who came up with that had no background in marketing because I’m sorry, the minute I’ve been in the paid landscape, the minute you see the letters GEO, you instantly think of geo targeting, hello people, the last thing we wanna do is make anything more confusing than it might otherwise be. So, my little soapbox for today.

    John Jantsch (00:48.622)

    Sure,

    John Jantsch (00:54.86)

    And so with that, with that Todd’s on the show. So welcome Todd. So let’s, mean, I kind of laid that out a little bit. You know, you’ve created a tool that is really taking advantage of some of the changes that are going on in marketing today, especially around search. So maybe give a high level kind of in your view, let’s start with the basics. All this stuff we’re hearing about.

    Todd Sawicki (01:10.609)

    Yes.

    John Jantsch (01:21.41)

    GEO for one, AIO, AIO, know, all those kinds of things. I mean, what does it all really boil down to for the typical marketer or typical business?

    Todd Sawicki (01:31.374)

    It is a it is a good question. So I think we all woke up a year ago. And with the rise of zero click searches with AI mode in Google search taking off, and we began to see Google traffic starting to decline. And at the same time, if anyone was sort of looking at their, like GA four analytics or whatever they’re using, they started to see, look, I’m getting this new basket of traffic from chat, tbt and others. And so AI

    John Jantsch (01:50.478)

    Mm-hmm.

    Todd Sawicki (01:58.706)

    and sort of looking at that. so the AI search is taking off. And so as a marketer, suddenly you had to start paying to this attention, this new thing called AI search. And so fundamentally, we look at it as, you know, marketers want to understand what the hell are LMS saying about me. And then from a product standpoint, we like to say yes, we help marketers understand what LMS think about them and their brands, and ultimately what to do about it. And I think that’s one of the interesting things is there’s a lot more you can do about it, because AI search is a

    fundamentally different platform and approach than traditional search and really in many ways I think a search is solving a lot of the problems we’ve been complaints as end users we’ve had about traditional search and then there’s downstream applications for marketers and how to think about how you work with those platforms as a result.

    John Jantsch (02:45.262)

    Well, and I think you’re hitting on one of the things that I try to get people to understand. Everybody always goes, oh, we’ve got these new platforms. Um, but what they fail sometimes to recognize is that the buyer behavior is changing because of these new platforms and how people, what their expectations are, how they now go to, even to Google. mean, I’m seeing people do this. We used to put it in these nice little compact searches. Well, I’m seeing people put in these very long searches now, very high intent, you know, very filtered almost because they know they can get AI overviews and things. And I think that.

    Todd Sawicki (02:57.202)

    Correct.

    Todd Sawicki (03:09.039)

    Exactly.

    John Jantsch (03:15.222)

    change is really what we really need to adjust to, right? It’s not necessarily the technology, is it?

    Todd Sawicki (03:21.778)

    I agree users have fundamentally changed and you probably hear this even anecdotally amongst your friend sets. Like you start kind of experimenting with chat tpt or perplexity or whatever it is and you’re like you ask it a real deep question that you know is very frustrating to get answered in traditional search and you would have to click through 10 things and it was just a pain in the ass and took a lot of time and where now you get a pretty good answer most of the time right away and it fundamentally changes the experience. I mean we’re seeing dramatic thing changes especially in complex areas like b2b type searches.

    It’s a great use case when you’re researching very technical things. You’re researching like more long tail areas for traditional search work wonderfully in the world of AI. And I think the other thing that traditional search really did a poor job of, and it really shows up in AI search is AI search does a phenomenal job of personalizing its answers for you. And that is one of the things that

    in even in terms of our own product and platform, but the implications of that are very interesting. And so as an end user rate, would you imagine think of the LM as you walk into a shoe store, and there’s a wall of 500 pairs of shoes behind that salesperson as you walk in, and the LM is the salesperson. And so you’re trying to know what’s the right pair of shoes? Well, Google you do it doesn’t really ever answer I need a new pair of shoes, you would never like Google just would struggle with that. But with

    John Jantsch (04:43.488)

    Or give you the most popular shoes or whatever.

    Todd Sawicki (04:45.488)

    Or give you the most popular one. Exactly. Just give you the most popular one. But the LLMs are really trying to understand, are you a runner? Are you a hiker? you have an account, you register, they’re building profiles of you, interestingly enough. Right? The minute you put your email in, it knows where you work. It knows what you’re affiliated with. And so as a result, your users are seeing that there really, there’s a value for that relationship between you and the LLMs. It learns more about who you are. It discovers things. It’s trying to personalize the answers. And so it therefore can give you a better answer and really help you in a way that

    Traditional search never quite got to.

    John Jantsch (05:18.252)

    You know, and one of things that I get business owners pretty excited about, because a lot of them are going, is all hype or like, don’t, you know, do I got to really do this or am I really going to get AI traffic or not get AI traffic? So all these questions and all I do is show them analytics. and I am able to demonstrate that to them, the people who come from AI stay on your site 10 times longer and convert seven times more than your paid ads, more than your organic traffic. And a lot of that, think is just what you talked about because.

    Todd Sawicki (05:43.602)

    Yup.

    John Jantsch (05:47.5)

    they are doing the filtering themselves. And if they get to your website, it’s because you had what they wanted. Right.

    Todd Sawicki (05:51.258)

    Exactly. They’re pre-qualified. Right. No, and we’re seeing stats on the B to C. We typically see a little bit less than seven X, probably more in the range of kind of two to five X increased conversions on the B to B side. We’re seeing increased conversion rates up to like 20 X better. Cause again, they’re down the funnel. Cause right. When I think about, you think of from a marketer standpoint, let’s think about the classic marketing funnel. There’s discovery, then consideration, then conversion.

    Google managed discovery and then handed you off to websites to manage consideration like your own website some third-party writer whatever it might be but AI is trying to do not just discovery but manage through the Q &A process consideration as well and then hand that user off for conversion and So that’s why you see these higher conversion rates. They’re further down the funnel AI has managed that now from a marketing standpoint You’re now your challenges. I need to manage AI differently because now suddenly it’s it’s the one selling my product

    John Jantsch (06:49.09)

    Yeah, yeah.

    Todd Sawicki (06:49.35)

    And I think that’s the fundamental shift here as a marketer is you have to going back to that, that shoe store analogy, that element as a salesperson means you’re going to have to manage that person, right? That’s not your job. Whereas SEO, and I think this is one of the other big changes. SEO is a very technical thing, like link building. And remember that the just the ridiculous debate we had for years about is it a sub domain or a folder? Right? Is that marketing? No, that’s a very technical thing. And you know, any non technical marketer, whenever that discussion and by the way,

    for those who don’t pay attention that went on for years like it was like a red versus blue sort of battle in the online marketing sphere. And but a very technical thing not marketing based at all. And I think the differences for LLMs, it’s much more of a, oh, how do I teach the LLMs what to say about my product, just like I teach, you know, a salesperson at the front of Dick’s Sporting Goods store kind of the same way. And so it’s now it’s much more of a product marketing exercise than it ever was with traditional search. And I think that’s the other thing is

    You’re going to have to think about how you talk to the LLMs and how you market to them.

    John Jantsch (07:50.35)

    Well, and this gets at the crux of, you know, a good salesperson is trained on, know, all the objections of, you know, all the questions they’re going to get. Right. And so now all of a sudden our content has to be answers.

    Todd Sawicki (07:57.222)

    Mm-hmm. Mm-hmm.

    Todd Sawicki (08:04.722)

    Correct? absolutely. So one of the things, so Gumshoo as a platform has been, we publicly launched it about six months ago and we’ve already worked more than 3,500 marketers have signed up. We’ve already generated millions of prompts on behalf of marketers so they understand what elements say in response to these prompts. And as a result, we’re able to analyze those response. think it’s like 10 million answers that we’ve analyzed.

    John Jantsch (08:29.112)

    Mm-hmm.

    Todd Sawicki (08:30.416)

    And then you really, you start to see patterns in what they’re doing, but they absolutely want you as marketers to provide them kind of sample question answers back. if you, of the fascinating things about LLMs is they actually link, they prefer the number one source that they link to for product information are brand websites. And then within that, they link to product description pages or PDPs or product detail pages, whatever description you want to use, like the PDPs, FAQs,

    John Jantsch (08:50.616)

    Mm-hmm.

    Todd Sawicki (08:59.896)

    knowledge base articles, how to sections, they love that sort of informative how to answer questions for them. And they use that as a guide. Now they process their own way, they kind of regurgitate it in their own way, but they want to use that as a basis. So you’re right, you’re gonna you have to just like you train that salesperson on Rude Q &A, you’re doing the same thing now with the models, which I think is interesting to marketers, when they start kind of like seeing and understanding like it’s not a marketing exercise, and not a weird technical link building sub domain folder esoteric discussion anymore.

    John Jantsch (09:04.738)

    Yep. Yeah.

    John Jantsch (09:25.292)

    Yeah. Yeah. Yeah. And, and one of the things that we have seen, because, know, I’ve always believed that, that you do content, right. You’re going to get rewarded by the search engines. Well, we’ve been doing content, right. In my view, you know, hub pages, structured content, FAQs, table of contents, summaries, schema, you know, we’ve been doing all that stuff because it was good content marketing. well,

    Todd Sawicki (09:37.244)

    Yes.

    John Jantsch (09:52.258)

    the LLMs and AI are actually rewarding us for that work right now because we ranked high in Google. We are now ranking higher in AI overviews and in chat GPT. Are you seeing that as well?

    Todd Sawicki (10:06.354)

    So if you don’t have content online, it is hard for AI to even know you exist. And so that’s sort of step one. You’d be surprised at the lack of content out there. It’s, know, all right, well, you sell it. You sell these programs. But I think it’s because everyone probably thinks they’ve all, everyone’s done content marketing. It’s not always the case.

    John Jantsch (10:12.526)

    Well, yeah.

    Well, no, no, I would not be surprised.

    Yeah. Yeah. I always love it. I always love it when we go to work with a new client and they say, yeah, well, our SEO firm is doing this for us. And it’s like, what are they SEOing? Like, there’s no content there.

    Todd Sawicki (10:35.83)

    There you go. Exactly. There’s no content. There’s nothing else. And so the differences here you mentioned, like you generated content that the difference here though is there’s a subtle, you know, benefit and you kind of address this, I’m gonna call it what you said, which is you’re getting rewarded. But what’s interesting is Google, it was rewarding popularity, not necessarily the best content and the most authoritative content. What LMS are doing is doing a much better job of rewarding the correct content. So

    It’s sort of like, and we have a good stator on this, is, we look up the traditional Google rank of all the URLs that are cited by AI and its answer, and its justification for its answers. The traditional Google rank is below 21, 50 to 90 % of the time, meaning page three and beyond. So it’s pulling out these, so it is looking at some of those that traditionally link to content SEO, but it was always these deep links. And the problem with traditional searchers,

    John Jantsch (11:18.658)

    Well, yes.

    Todd Sawicki (11:28.602)

    is, you know, we kind of generically use the stat one out of 100 people go to page two on Google, one out of 1000 go to page three, one out of 10,000 go to page four, and no one goes to page five. And that’s very exactly how the dead bodies but AI to my stat 59 % of the links they surface are in that that sort of buried into because they have AI or machines, they have infinite patients. So what they’re good at doing is finding authoritatively correct like we like to see canonical information. And then and so as a brand,

    John Jantsch (11:38.734)

    Yeah, that’s where you hide the dead bodies, right?

    John Jantsch (11:51.15)

    Yeah.

    Todd Sawicki (11:58.416)

    all that work that maybe struggled to get surfaced in Google, because it just wasn’t as popular or using out to people buying links. Now, now they’re really to your point, really rewarding good content, good highly valued structured content. And so it’s sort of like, it’s sort of the it’s paying off 10 years of work, finally. And so the people who may be struggled to get some of that popularity in Google, it is absolutely paying off in AI overview, AI search and AI overviews and things like that in a way that you always prayed and hoped for as a content market, like your day has come.

    John Jantsch (12:07.842)

    Yeah.

    John Jantsch (12:13.964)

    Yeah.

    John Jantsch (12:26.35)

    Yeah

    Todd Sawicki (12:26.716)

    Producing great content is a payoff and it’s happening. And I think that’s really fascinating here, which is people are like, with the rise of AI Slop, no, the models want good content and they’re good at deducing what is good content. AI Slop will not get ranked and you have to, they want authoritative information. And so that’s content that will get ranked in AI search and then drive traffic today and tomorrow, agentic purchases, right? You’re ultimately trying to drive some of that conversion more and more that AI will be driving that itself. Like Perplexity’s browser will load a cart for you today.

    Right, it’s loading products it’s picking on your behalf into that. So that future is coming fast and furiously. And so I think that change is sort of fascinating to see when you look at what’s happening. Now, the other stat about what’s really fascinating here is, okay, what if I don’t have been produced 10 years of content, am I screwed? Well, one of the other facts that we’ve seen is that the average age of a cited piece of content

    is only 86 days old in AI search. And that’s falling 10 to 15 % quarter per quarter. Now there’s a caveat there, which is it doesn’t have to be originally published, it just has to be updated. Like the AI will look at content that’s older, but as long as it’s been updated, and you note that that updated date, it will value that as well. And so and that 86 days is falling 10 to 15 % every quarter. So today it’s 86 days, next quarter is gonna be 78, 70 to the quarter after that, and see you get faster and faster.

    So you’re gonna have to be doing a lot more work around content, maintaining it, updating it. It’s not a publish once and walk away model anymore. It’s gonna be a constant refresh. And so, the good side of that is you’re just starting out. We’ve definitely seen this with people where you can impact the results well within a 90 day window where traditional search that was almost impossible. And so there’s a definitely, don’t wait, get started. Hire John and his team.

    John Jantsch (14:12.504)

    But again, yeah, well, but I was also going to say that another best practice for years has been repurpose your content. And so, I mean, I now it’s like repurpose your content in a specific way, you know, add FAQs, you know, to that content, right? But, but I think that’s what you’re saying is should be very helpful for those people that just kind of wrote the hundred one off blog posts. It’s like, no, now go back and make that pay. Let’s talk specifically.

    Todd Sawicki (14:28.146)

    Correct. Right.

    Todd Sawicki (14:39.94)

    Exactly, exactly. It’s fascinating to kind of, you know, watch that all happen and come to fruition.

    John Jantsch (14:42.742)

    Yeah, yeah, yeah. Let’s talk specifically about gumshoe. I know that’s what you want to talk about. But first off, I have an account. I’ve played with it and it is in seemingly incredibly complex what you’ve built. And so my first question is, my first question is, where did that come from? Are you a mad scientist or did you hire people or how did you develop that? Because

    Todd Sawicki (15:02.844)

    Well, thank you.

    Todd Sawicki (15:10.77)

    So we have a team, right? We have a team. I’ve been in digital marketing tech for 20 years in my career and got involved in, and really the common theme has been around customer acquisition as it turns out. And I even view the purpose, we only care about AI search as marketers, ultimately because it can drive business, right? It’ll drive traffic and revenue, right? So fundamentally it’s a, and so I 20 years ago got involved in toolbars and search. Then I got into the social marketing landscape, just as that was taking off like 2007 to,

    John Jantsch (15:28.334)

    That’s right. That’s right.

    Todd Sawicki (15:39.986)

    to 2012 and then got into paid and built a DSP. So in the programmatic space and then was playing in ecommerce and Shopify’s ecosystem, you building customer acquisition apps in there and then ultimately transition here. And it was sort of the space of a year ago was talking to marketers. And again, the beginning of this conversation around AI search and the rise of that. And if you’re a marketer, and suddenly the channel you’re relying on Google search falls off a cliff. for some key keywords, I heard

    30 60, even 90 % declines in traffic, even on the paid side. Like it just Google is sacrificing even paid traffic and on some keywords. So that’s an existential change in the landscape. And then as we started thinking about this in terms of working with marketers, you’re like, well, you know, to what I said earlier, gumshoe helps brands understand what elements think about them. And then what to do about it. Well, that where does that come from? Well, if you’re a marketer, you can’t just log into chat tpt and find out what it’s saying to you because

    John Jantsch (16:12.813)

    Mm.

    Todd Sawicki (16:37.508)

    as you I don’t know if any everyone should go watch the season premiere this fall’s episode from Boulder natives, you know, the creators of South Park, the first episode this year, the main one of the main characters dads is like falling in love with chat tbt because all it does is flatter him. And it says like every idea he has is wonderful. And it’s a great and he’s got some he’s trying to start a new business. And his wife gets all pissed off because he’s constantly going to ask chat tbt and says see I’m right, you know,

    John Jantsch (16:54.285)

    Right.

    Todd Sawicki (17:05.426)

    his wife’s name is Sharon, see I’m white Sharon, chat TBT says I’m right. And he’s like, No, it just says that to everybody. And so as a marketer, you you can’t just log in and ask chat TBT what it thinks about your business, because it’s going to kind of lie, it’s going to flatter you, it’s going to say the most optimal thing it can because it by the way, the minute you put your email in, it looks you up on LinkedIn, it knows it knows where you work, it knows your products, it’s no it knows how to answer things. And so then you realize as a marketer, I don’t care what LM say to me, I say, I care what it says to my target customers.

    John Jantsch (17:17.666)

    Mm-hmm. Mm-hmm.

    John Jantsch (17:31.832)

    Yeah. Yeah.

    Todd Sawicki (17:34.01)

    And so the way that we built our product was around how do you help marketers understand what it’s really saying to its customers? And so our point of view as well, how do we get in the shoes of that customer? And so what we do is we build these personas which become synthetic users. right, so those are what are asking prompts in the models. We have a better understanding of how they, how will they talk to, how the models speak to these different, different customers and those insights of like, okay, here’s how it, and by the way, the variety of answers between one type of

    persona and another is fascinating. And they’re absolutely customizing their answers. Like, John, you’ve seen this, right? Just one customer will say, like, just imagine you’re a hiker, you’re going to get a different answer for the pair of shoes than if you’re a marathon runner. And so that makes rational sense as a marketer kind of understanding this nuance and how it’s treating different types of end users using AI search is sort of a fascinating insight. And it’s cool just to look at the answers and see what they say to different things. So that’s my point about marketers and the messaging and seeing how it talks to different people.

    John Jantsch (18:06.594)

    Mm-hmm. Yeah.

    John Jantsch (18:31.374)

    One of my first observations that kind of blew me away frankly was I just put in a company’s URL, I think is all I did. yeah, and it came up with, I want to say eight, maybe it was a little more than that personas. And they were, we had already done that work, but they were very spot on, maybe even a little better descriptions. And what I found was interesting was it actually,

    Todd Sawicki (18:39.324)

    Correct, that’s what you start with. You start with the URL, correct.

    John Jantsch (19:00.342)

    All the analytics and search was great, but we actually got some messaging ideas just from that part of it, and that wasn’t even the intent.

    Todd Sawicki (19:10.652)

    Well, and that’s what I mean about it. you know, it’s, was talking with a head of product marketing earlier today, and I’m like, this is product marketing’s moment, because AI search is fundamentally a product marketing exercise. And it’s a positioning exercise. And when you read those prompts and answers, we hear that all the time, because what we help you on what we ask questions and basically ask questions around product areas for your business. And those will give you a set of responses like, we recommend these three companies or these eight companies or these five. And then you see the rationale for those

    recommendations. And that’s great marketing, right at feedback. It’s it’s what’s our positioning, what’s our competitive positioning, you show this to any product market, like, oh, my god, this is like my competitive messaging framework, which you’d by the way, what you describe john a itself serve, can do this yourself, anyone can enter a URL of a company to get this. And in like 10 to 15 minutes, you’re walking away with a really cool understanding of your products position in the marketplace, at least the marketplace of AI search, which is meant to be a broader perspective of the world, obviously.

    But it’s no, hear this all the time. It’s fascinating. Like it is a total rabbit hole for anyone who cares about commutative or comparative messaging.

    John Jantsch (20:13.742)

    Yeah. So the other observation is that, you know, lot of people that are talking about losing search traffic, it’s for, let’s say I’m a remodeling contractor. It’s they’re losing traffic for trends in kitchens, right? Which was not somebody that was going to buy anything, right? They’re losing a lot of that traffic because they’d written a great trend article for 2025, right?

    Todd Sawicki (20:37.138)

    Correct.

    John Jantsch (20:38.37)

    But that was not going to ever convert. But what’s interesting from what you’re unearthing is you’re unearthing all these really high intent searches. I mean, the search string is such that it’s like, yeah, that person’s looking to remodel their kitchen. And I think that that’s what marketers need to really focus on is that, forget about the, I mean, we do still have to do a lot of things to create awareness. But what we really need to focus on is high intent right now and capturing that search.

    Todd Sawicki (21:07.138)

    That is absolutely, I think a change, which is you’re going to go a little bit more down funnel. And you because you I think you can with AI search problem with Google is all those searches were so high level and so generic. It was hard to, to you’re right, the lack of long detailed searches in Google meant it was hard as a market, you couldn’t really target that sort of bottom of funnel activity. But AI is kind of all about that. And even if you ask a generic question, AI will follow it up with a more specific like they want to, they want to know which direction they need to go. There’s a back and forth that never existed in Google search.

    John Jantsch (21:16.962)

    Yeah, right.

    Todd Sawicki (21:35.878)

    that absolutely exists in AI. And you anyone who’s experienced this, when you go to the models, it’ll it’ll ask for follow ups, it’ll clarify things, it’ll make sure it understands what you’re talking about. So that it’s its goal is to give you the very best answer possible.

    John Jantsch (21:41.932)

    Yeah, yeah.

    John Jantsch (21:48.686)

    Yeah, it wouldn’t have been great. You go to Google and say, no, that answer was wrong. Fix it, right?

    Todd Sawicki (21:52.324)

    Exactly, we all wish we could like that search, you’ll get some results. You’re like, that is a terrible right link. And now with all the like the amount of Google searches that are so link baited to death. I love to get the analogy of in a lot, you know, I said earlier, the AI search is fixing a lot of things wrong with traditional search, like how many times in our lives like you bought like a new TV, and I just need to know the damn matter the width of it. So will it fit on my mantle or not? And you do a search and like you get every link is 10 best this or 10 best that or trends of

    hot TVs this Christmas like I just need the dang measurement. Come on, Google.

    John Jantsch (22:23.854)

    or a link to Amazon that’s not even a TV. Those are my favorite. So I’m sorry, we got geeking out here on like all the under the hood stuff. And I’d love it you could just like give us the two minutes feel what is gumshoe? How you know, how does it work? How does somebody try it out?

    Todd Sawicki (22:28.187)

    Right!

    Todd Sawicki (22:42.556)

    So at any market, it’s a publicly available and you can try it out for free. It is, you can generate a report about your company. You go to it, as John said, you’re going to enter your company’s URL. And then from there, what we’re gonna do is again, show you what LMS think about your business and product. You’re gonna select a product that’ll generate personas and then we’ll generate the prompts that represent the activity that users are having with AI. And then…

    run a series of real-time conversations, we turn those personas effectively into synthetic users. That’s kind of a buzzy word. Synthetic is the ultimate now AI buzzword. It’s a simulated user, it’s a synthetic user. And then that user will, yeah, exactly. It’s better than that. We’ll have a series of conversations with the LLMs. We kind of create those and then we analyze the chat activity and kind of package that up in a way so that you can help identify areas, topics of these types of prompts where you’re doing well or you’re doing poorly.

    John Jantsch (23:14.648)

    Yeah, yeah, yeah.

    John Jantsch (23:18.83)

    It’s better than bot though, isn’t it?

    Todd Sawicki (23:38.736)

    And then the next step is we also allow you to sort of then generate the content based upon, you know, where your strengths and weaknesses are that through our platform that you can then host on your site. And the way to think of it is, is your personas are your predicted customers, who the elements think are your top customers, and then they want instructions, the content you generate is intended to be or write on your own, is intended to be the instruction set back to the models. Okay, for these customers, here’s the features and benefits that we believe appeal to them and why they want to pick our products.

    And ultimately, that’s going to send traffic back to your site. And then can help analyze that to understand was it good traffic, bad traffic, what have you. And so the goal of our point of view is to say, again, how do we help you understand what I’m thinking about you and then what to do about it, right? You’re ultimately how do you capture as much revenue or as much referral traffic as possible from the LLMs. And so that’s the way Gumshoe works. You can go to gumshoe.ai. They said you just start with the URL. And in 10 to 15 minutes, you’re going to walk away with sort of insights about what you can do. there’s, again, you don’t need an inter credit card that’s just freely available. Everyone can create an account. And then

    The way we work is it’s not a subscription based a time based. If you want to rerun a report, you want to run it again, like in a weekly or monthly basis, kind of track how you’re doing, you would then sign up to pay an ongoing basis. And so it’s just based upon how often you want to sort of leverage the platform and use it. That’s the model. So feel free once you generate a report, whether it’s a free one or a paid one down the road, it’s available to you for as long as we’re around as a company.

    John Jantsch (25:03.266)

    Yeah. And one of the things that I failed to mention, you didn’t mention either is I thought does a really good job at, at, identifying competitors, as well. Yeah.

    Todd Sawicki (25:12.466)

    Correct, because what we’ll do is in those answers, we’re going to get multiple companies products recommendations and we surface that to know your competitive great great point, John, you know, your competitive standing, our competitors doing better or worse than you in AI. And that’s obviously often a key indicator. And then we’ll help you analyze where they did better versus you. So you know, what’s your point about messaging, right? And the product messaging, like what features of a competitor are winning versus ours?

    where is their positioning better? Is it something else? Or and that’s sort of a great insight is where all the other companies getting mentioned alongside you, and then we’ll help you identify also, what were the reasons like what led to the models answering the way they did? Like what citations and sources so if you want to do outreach from a PR standpoint, you can we help you identify the places you should be going and talking to, or even read our core threads you should be posting on. We now have a feature where we’ll we’ll give you a draft post for Reddit and Cora.

    John Jantsch (25:49.816)

    Yeah.

    Todd Sawicki (26:05.498)

    Again, but it’s based upon, you know, strengths and weaknesses that we identified and said, here’s the things you should be talking about more to help you get more visibility to AI. And so that’s sort of the goal here is how do we help you talk back to AI. So you’re feeding it the features and benefits of your products. So they’ll talk about your products next time instead of someone else’s.

    John Jantsch (26:26.878)

    I’m sorry to sound like an ad for, for gum shoe, but you know, we actually took a lot of this long tail searches and built some ad campaigns around, around them as well.

    Todd Sawicki (26:35.792)

    We have heard that because the persona piece is great for that, like audience targeting and things like that. No, no, we’ve absolutely heard that, that there’s some interesting crossovers about this. Once you realize it’s messaging based, there’s a ton of things you can do with this data. It’s really, I’m not kidding about being a rabbit hole. Like you start reading the chats that we generate and surface. just, it becomes, it’s really fascinating to kind of see what’s being said in a way that you only ever got through focus groups or weird surveys before. And now and again, it like.

    15 minutes, getting some really interesting insights. can then spend a lot of time diving into and learning from in a way that we just never had access to before.

    John Jantsch (27:10.99)

    Well, we’ve gone over time. appreciate you. Take it a few moments to stop by the duct tape marketing podcast is gum shoe dot AI and Todd again, appreciate you stopping by and hopefully we’ll run into you one of these days out there on the road.

    Todd Sawicki (27:24.914)

    Thank you very much. Appreciate the time and attention.

    powered by

  • The Best Level from Every Main Console 2D Mario Game

    The Best Level from Every Main Console 2D Mario Game

    Nintendo has always kept its Super Mario roots in mind. Despite the fact that there have been many legends in the field since the turn of the century, including the wide galactic multitasking of Super Mario Galaxy and the sun-spotted holiday achievements in Super Mario Sunshine, […]

    The first article on Den of Geek was The Best Degree from Every Main Console 2D Mario Game.

    Nintendo has always retained its connection to the Super Mario company. The character’s heart and soul are the focus of the focus on 3D games, which has been a focus since the turn of the century and a number of classics in that music- from the wide galactic platforming of Super Mario Galaxy to the sun-spotted vacation exploits in Super Mario Sunshine -#8211.

    cnx. command. push ( function ( ) {cnx ( {playerId:” 106e33c0-3911-473c-b599-b1426db57530″, }). render ( “0270c398a82f44f49c23c16122516796” ), }),

    Each 2D Super Mario work has a degree that embodies both the sport and a long history of gameplay. These levels help usher in new methods to run, jump, and trample Goombas, not to be extremely dramatic, but they serve as the benchmark for all others. What is the best of all 2D Mario games? We are the ones who know! Please take note that this will only be the mainstream console games, so there is no Super Mario Land franchise around. Yoshi’s Island, which is a subsidiary of the Mario company, will not be included either. &nbsp,

    Super Mario Bros. – World 1-1

    I find it annoying when a group forerunner is awarded brownie points for doing something, but in the case of World 1-1 in Super Mario Bros., I must give it up for the first time in the background of the Super Mario company. Perhaps the most impressive achievement of Mario father Shigeru Miyamoto’s job is how simple the stage design is while also being fun to play 40 years later. &nbsp,

    World 3-1 Super Mario Bros. 2- World 3-1

    The second installment of the company attempted to do a lot of unusual products that wasn’t always appreciated, but it has since grown so beautifully. Clouds, magic rug rides, and a hard battle with Birdo are included in the next world’s second level, which includes a hard fight with Birdo. You can’t go wrong with Peach’s flying prowess if you choose your persona correctly!

    World 7 Airplane: Super Mario Bros. 3

    Although there are tough-as-a-Koopa shell platforming in Super Mario Bros. 3, the issues are good and the gameplay is strong and well-designed. The person must use all of their skills at the end of World 7, which has a wide range of risks and a variety of risks. &nbsp,

    Super Mario Bros. World 4-3: The Lost Levels

    Because Nintendo was concerned that players may be intimidated by the game’s great difficulty, the Lost Levels didn’t get released in the United States. World 4-3 perfectly exemplifies the Kaizo nature. You’ll wonder why you even decided to play Mario in the first place due to the tiny websites you have to hop from at the end of the stage!

    Vanilla Dome 3 in Super Mario World

    The best 2D system activity always, Super Mario World, might be the best. With a picking of everything that makes the sport so much fun, Villanilla Dome 3 embodies the creativity that the development staff has embedded in its worlds. Yoshi, navigating icebergs, soaring over floating platforms in volcano, and other challenges complete the degree with a potpourri of Mario’s platforming skills. &nbsp,

    New Super Mario Bros. – World 1-4

    The fifth stage of the first globe in New Super Mario Bros. combines the relaunch of the company in the middle of the 2000s with a ton of new equipment, the latter of which allows Mario to wreak havoc on the level. This game is more than just a beautiful update of 2D multitasking, thanks to plenty of techniques and design that looked great at the time on the Nintendo DS.

    World Mushroom-1 in New Super Mario Bros. 2

    Although this title may not be the most stale New Super Mario Bros. game in the franchise, it must still be represented. The theme of the game’s first level, Mushroom World, is to collect sizable coins against the backdrop of vibrant platforms in the sky. For Mario and his fans, it’s a comforting and well-known aesthetic. &nbsp,

    World 8-7 of New Super Mario Bros. Wii

    Just enough obstacles to overcome in the environment, but not too many annoyances to get in the way of a fun time, is exemplified by this fiery roller coaster ride of platforming at the end of the eighth world in New Super Mario Bros. Wii, a classic game design spirit of the franchise. The Wii’s party mentality was perfectly suited to the multiplayer aspect of this game. &nbsp,

    New Super Mario Bros. U – Soda Jungle &#8211, 4 ( Painted Swampland )

    Some of the world’s design and graphics in New Super Mario Bros. U were experimented with ( some claim to detract from the New franchise’s exhausting aesthetic ). The Painted Swampland with Vincent Van Gogh artwork in the background is a fan favorite, and The Soda Jungle has some exhilarating levels. &nbsp,

    Downpour Uproar in Petal Isles during Super Mario Bros. Wonder

    After so many years of re-treading games in the New Super Mario Bros. franchise, people now remember why Mario is GOAT. We’re going to take this cheery trek through the rainy Isles because Super Mario Bros. Wonder is so full of novel concepts that it’s difficult to pin down a best level!

    Gotta Walk the Dogs in Super Mario Maker 2

    Without including one Super Mario Maker game creation from the series, we can’t compile a list of the best Mario levels. As players guide one of Bowser’s minions to the end goal by turning switches on and off throughout the level, this puzzle level in Super Mario Maker 2 shows off the surprising number of genres that Mario can operate within when given the chance. &nbsp,

    The first article on Den of Geek was The Best Degree from Every Main Console 2D Mario Game.

  • Win a Copy of Saltcrop by Yume Kitasei in Our Flatiron Books Giveaway

    Win a Copy of Saltcrop by Yume Kitasei in Our Flatiron Books Giveaway

    Den of Geek is excited to work with Flatiron Books to observe the launch of Yume Kitasei’s most recent book Saltcrop, which is best known for her sci-fi attack thriller The Stardust Grail. Five lucky visitors stand a chance of winning a version of Kitasei’s expansive new venture. It’s simple to enter: just]…

    Yume Kitasei’s Saltcrop was featured in the Den of Geek blog’s first article,” Win a Copy of Saltcrop.”

    Nintendo has always retained its connection to the Super Mario company. The character’s heart and soul are the focus of the focus on 3D games, which has been a focus since the turn of the century and a number of classics in that music- from the wide galactic platforming of Super Mario Galaxy to the sun-spotted vacation exploits in Super Mario Sunshine -#8211.

    cnx. command. push ( function ( ) {cnx ( {playerId:” 106e33c0-3911-473c-b599-b1426db57530″, }). render ( “0270c398a82f44f49c23c16122516796” ), }),

    Each 2D Super Mario work has a degree that embodies both the gameplay era and the game itself. These levels help usher in new methods to run, jump, and trample Goombas, not to be extremely dramatic, but they serve as the benchmark for all others. What is the best of all 2D Mario games? The solutions are available to us! There will be no Super Mario Land sub-franchise around because this will only be the mainstream console games. Yoshi’s Island will not be included because it is a subsidiary of the Mario franchise. &nbsp,

    Super Mario Bros. – World 1-1

    I have a pet complaint, which is when the forerunner of a group receives brownie points for being the first to do anything, but in the case of World 1-1 in Super Mario Bros., yet I have to give it up for the first stage in the history of the Super Mario franchise. 40 years later, Shigeru Miyamoto’s job is perhaps the most impressive success, combining the simplicity of the stage design with fun while teaching the player how to play the game. &nbsp,

    World 3-1 Super Mario Bros. 2- World 3-1

    The second installment of the company attempted to do a lot of unusual products that wasn’t always appreciated, but it has since grown so beautifully. The second world’s first degree introduces clouds, magic rug trips, and a difficult fight with Birdo. You can’t go wrong with Peach’s flying prowess if you choose your persona correctly!

    World 7 Airplane: Super Mario Bros. 3

    Every earth in Super Mario Bros. 3’s last level often features some tough-as-a-Koopa shell platforming, but the challenges are good and the platforming is strong and well-designed. The player must use all of the skills they’ve learned so far in the final airship level of World 7, and a wide range of hazards makes it a fun challenge. &nbsp,

    Super Mario Bros. World 4-3 The Lost Levels

    Because Nintendo was concerned that gamers would be intimidated by the game’s high difficulty, The Lost Levels didn’t officially debut in the United States. World 4-3 perfectly exemplifies the Kaizo spirit. You’ll wonder why you even decided to play Mario in the first place due to the tiny platforms you have to jump from at the end of the level!

    Vanilla Dome 3 in Super Mario World

    The best 2D platform game ever, Super Mario World, might be the best. Villailla Dome 3 exemplifies the creativity of the development team’s worlds with a sampling of everything that makes the game so enjoyable. Yoshi, soaring over platforms that float on lava, traversing ice sections, and other challenges complete the level in a potpourri of Mario’s platforming skills. &nbsp,

    Worlds 1 through 4 of New Super Mario Bros.

    The first world in New Super Mario Bros. ‘ fourth level, which includes the Mini Mushroom and the Mega Mushroom, allows Mario to wreak havoc on the stage while capturing the reboot of the franchise in the middle of the 2000s. This game is more than just a shiny upgrade of 2D platforming, thanks to numerous secrets and graphics that were fantastic at the time on the Nintendo DS.

    World Mushroom-1 in New Super Mario Bros. 2

    Although this title belongs in the sub-franchise, it must still be represented, despite being the most stale New Super Mario Bros. title. The theme of the game’s first level,” Mushroom World,” is to collect sizable coins against the backdrop of elaborate platforms in the sky. For Mario and his fans, it’s a comforting and well-known aesthetic. &nbsp,

    World 8-7 of New Super Mario Bros. Wii

    Just enough obstacles to overcome in the environment, but not too many annoyances to get in the way of a fun time, is exemplified by this fiery roller coaster ride of platforming at the end of the eighth world in New Super Mario Bros. Wii, a classic game design spirit of the franchise. This game’s multiplayer functionality worked perfectly with the Wii’s party mentality. &nbsp,

    Soda Jungle 4 in New Super Mario Bros. U ( Painted Swampland )

    Some of the world design and graphics in New Super Mario Bros. U were experimented with by Nintendo, with some alterations to the Mushroom Kingdom’s aesthetic ( some would say this to disorientation from the New franchise’s exhaustion ). The Painted Swampland with Vincent Van Gogh’s background is a fan favorite, and The Soda Jungle has some thrilling levels. &nbsp,

    Downpour Uproar in Petal Isles during Super Mario Bros. Wonder

    After so many years of rehashing the New Super Mario Bros. franchise games, people now recall why Mario is GOAT. Super Mario Bros. Wonder is full to the brim with novel ideas, which make it difficult to pin down a favorite concept, but we’re going to take the cheery journey through the Petal Isles!

    Gotta Walk the Dogs in Super Mario Maker 2

    Without including one Super Mario Maker game creation from the series, we can’t compile a list of the best Mario levels. As players guide one of Bowser’s minions to the end goal by turning switches on and off throughout the level, this puzzle level in Super Mario Maker 2 shows off the surprising number of genres that Mario can operate within when given the chance. &nbsp,

    The first post on Den of Geek was The Best Level from Every Main Console 2D Mario Game.

  • Vicious Review: Dakota Fanning Discovers Horror in Holiday Box

    Vicious Review: Dakota Fanning Discovers Horror in Holiday Box

    A single package occupies a spot in the middle of a snow-covered street that seems completely abandoned at night. The enticing hook of Bryan Bertino’s Vicious is this sturdy black cube and the even more utter dark secrets contained within. We are cautioned that it is hidden in this subject that […]

    On Den of Geek, Dakota Fanning discovered a despair in a vacation package.

    Nintendo has always kept its roots in the Super Mario video game. The character’s heart and soul are the focus of the Mario games that take place in a fewer dimensions, even though there has been a target on 3D games since the turn of the century and a number of legends in that style.

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    Each 2D Super Mario work has a stage that embodies both the gameplay era and the game itself. These are the rates that support usher in new methods to run, jump, and trample Goombas, not to be overly dramatic. What is the best piece of every 2D Mario activity? The solutions are available to us! There will be no Super Mario Land sub-franchise around because this will only be the mainstream console games. Yoshi’s Island, which is a subsidiary of the Mario company, will not be included either. &nbsp,

    World 1-1 of Super Mario Bros.

    I have a pet complaint, which is when the forerunner of a group receives brownie points for being the first to do anything, but in the case of World 1-1 in Super Mario Bros., yet I have to give it up for the first stage in the history of the Super Mario franchise. 40 years later, Shigeru Miyamoto’s job is perhaps the most impressive success, combining the simplicity of the stage design with fun while teaching the player how to play the game. &nbsp,

    World 3-1 of Super Mario Bros.

    The second installment of the company attempted to do a lot of unusual products that wasn’t always appreciated, but it has since grown so beautifully. The next world’s first degree introduces clouds, magic rug trips, and a difficult fight with Birdo. You can’t go wrong with Peach’s flying prowess if you choose your character correctly!

    World 7 Aircraft: Super Mario Bros. 3

    Although there are tough-as-a-Koopa shell platforming in Super Mario Bros. 3, the issues are good and the gameplay is strong and well-designed. The player must use all of the expertise they’ve learned so far in the last aircraft level of World 7, and a wide range of risks makes it a fun challenge. &nbsp,

    Super Mario Bros. World 4-3 The Lost Levels

    Because Nintendo wanted players to be intimidated by the game’s great difficulty, the Lost Levels didn’t get released in the US. World 4-3 perfectly exemplifies the Kaizo nature. You’ll wonder why you even decided to play Mario in the first place due to the tiny systems you must climb from at the end of the stage!

    Vanilla Dome 3 in Super Mario World

    Super Mario World might be the best 2D system sport ever. Villailla Dome 3 exemplifies the imagination of the growth team’s worlds with a sampling of everything that makes the sport so enjoyable. Yoshi, soaring over platforms that float on volcano, traversing ice sections, and other challenges complete the amount in a melange of Mario’s platforming skills. &nbsp,

    World 1-4 of New Super Mario Bros.

    The second globe in New Super Mario Bros. ‘ fourth level, which includes the Mini Mushrooms and the Mega Mushroom, allows Mario to wreak havoc on the level while capturing the relaunch of the franchise in the middle of the 2000s. This game is more than just a beautiful update of 2D multitasking, thanks to plenty of strategies and images that looked great at the time on the Nintendo DS.

    World Mushroom-1 in New Super Mario Bros. 2

    Although this title may not be the most stale New Super Mario Bros. game in the franchise, it must still be represented. The game’s theme of collecting sizable sums of money is reflected in the first level of Mushroom World against the backdrop of brightly lit platforms in the sky. For Mario and his fans, it’s a comforting and well-known aesthetic. &nbsp,

    World 8-7 of New Super Mario Bros. Wii

    Just enough obstacles to overcome in the environment to avoid becoming irritable as much as they can get in the way of a fun time, is exemplified by this fiery roller coaster ride of platforming at the end of the eighth world in New Super Mario Bros. Wii. The Wii’s party mentality was perfectly suited to the multiplayer aspect of this game. &nbsp,

    New Super Mario Bros. U – Soda Jungle &#8211, 4 ( Painted Swampland )

    Some of the world’s design and graphics in New Super Mario Bros. U were experimented with ( some claim to detract from the New franchise’s exhausting aesthetic ). The Painted Swampland with Vincent Van Gogh’s background is a fan favorite, and The Soda Jungle has some thrilling levels. &nbsp,

    Downpour Uproar in Petal Isles during Super Mario Bros. Wonder – Downpour

    After so many years of rehashing the New Super Mario Bros. franchise games, people now recall why Mario is GOAT. Super Mario Bros. Wonder is full to the brim with novel ideas, which make it difficult to pin down a favorite concept, but we’re going to take the cheery journey through the Petal Isles!

    Gotta Walk the Dogs in Super Mario Maker 2

    Without adding one fan-created item from the Super Mario Maker series, we can’t compile a list of the best Mario levels. As players guide one of Bowser’s minions to the end goal by turning switches on and off throughout the level, this puzzle level in Super Mario Maker 2 shows off the surprising number of genres that Mario can operate within when given the chance. &nbsp,

    Den of Geek‘s first post The Best Level from Every Main Console 2D Mario Game.

  • Asynchronous Design Critique: Giving Feedback

    Asynchronous Design Critique: Giving Feedback

    One of the most powerful smooth abilities we have at our disposal is the ability to work together to improve our designs while developing our own abilities and perspectives, regardless of how it is used or what it might be called.

    Feedback is also one of the most underestimated equipment, and generally by assuming that we’re now great at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Bad feedback can cause conflict in jobs, lower motivation, and negatively impact faith and teamwork over the long term. Quality opinions can be a revolutionary force.

    Practicing our knowledge is absolutely a good way to enhance, but the learning gets yet faster when it’s paired with a good base that programs and focuses the exercise. What are some fundamental components of providing effective opinions? And how can comments be adjusted for isolated and distributed job settings?

    We can find a long history of sequential opinions on the web: code was written and discussed on mailing lists since the beginning of open source. Currently, engineers engage on pull calls, developers post in their favourite design tools, project managers and sprint masters exchange ideas on tickets, and so on.

    Design analysis is often the label used for a type of input that’s provided to make our job better, jointly. It generally shares many of the concepts with comments, but it also has some differences.

    The material

    The content of the feedback serves as the foundation for every effective criticism, so we need to start there. There are many versions that you can use to design your content. The one that I personally like best—because it’s obvious and actionable—is this one from Lara Hogan.

    This calculation, which is typically used to provide feedback to users, even fits really well in a design critique because it finally addresses one of the main issues that we address: What? Where? Why? How? Imagine that you’re giving some comments about some pattern function that spans several screens, like an onboard movement: there are some pages shown, a stream blueprint, and an outline of the decisions made. You notice anything that needs to be improved. If you keep the three components of the equation in mind, you’ll have a mental unit that can help you become more precise and effective.

    Here is a reply that could be included in some feedback, and it might appear fair at first glance because it appears to partially fulfill the requirements. But does it?

    Not confident about the keys ‘ patterns and hierarchy—it feels off. Can they be altered?

    Observation for style feedback doesn’t really mean pointing out which part of the software your input refers to, but it also refers to offering a viewpoint that’s as specific as possible. Do you offer the user’s viewpoint? Your expert perspective? A business perspective? From the perspective of the project manager? A first-time user’s perspective?

    I anticipate that one of these two buttons will go forward and the other will go back when I see them.

    Impact is about the why. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

    I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

    The question approach is meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s generally a viable option for feedback, I’ve found that going back to the question approach typically leads to the best solutions for design critiques because designers are generally more open to experiment in a space.

    The difference between the two can be exemplified with, for the question approach:

    I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

    Or, for the request approach:

    I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

    At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

    I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

    Choosing the question approach or the request approach can also at times be a matter of personal preference. I spent a while working on improving my feedback, conducting anonymous feedback reviews and sharing feedback with others. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. Until I changed teams. Surprise surprise, my next round of criticism from a specific person wasn’t very positive. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. However, there was a member of this other team who preferred specific guidance. So I adapted my feedback for them to include requests.

    One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. Yes, but no. Let’s explore both sides.

    No, this kind of feedback is actually effective because the length is a byproduct of clarity, and giving this kind of feedback can provide precisely enough information for a sound fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just,” Let’s make sure that all screens have the same two forward and back buttons”. The designer receiving this feedback wouldn’t have much to go by, so they might just implement the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. The designer might assume that the change is about consistency without the explanation, but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

    Yes, this style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (” The font used doesn’t follow our guidelines” ) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

    Therefore, the above equation serves as a mnemonic to reflect and enhance the practice rather than a strict template for feedback. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

    The tone

    Well-grounded content is the foundation of feedback, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. It has been demonstrated that only positive feedback can lead to sustained change in people, and tone alone can determine whether content is rejected or welcomed.

    Since our goal is to be understood and to have a positive working environment, tone is essential to work on. Over the years, I’ve tried to summarize the necessary soft skills in a formula that resembles the one for content: the receptivity equation.

    Respectful feedback comes across as grounded, solid, and constructive. It’s the kind of feedback that, whether it’s positive or negative, is perceived as useful and fair.

    The term “timing” describes the moment when the feedback occurs. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. If a new feature’s entire high-level information architecture is about to go live when it’s about to be released, it might still be relevant if that questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration later? Polishing work in progress? Each of these needs a different one. The right timing will make it more likely that your feedback will be well received.

    Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. That entails checking before writing to see if what we have in mind will actually help the person and improve the project overall. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Hopefully that’s not the case, but it can happen, and that’s okay. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I encourage constructive behavior?

    Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. There could be many reasons for this: some words might cause particular reactions, some non-native speakers might not understand all the nuances of some sentences, and other times our brains might be different and we might perceive the world differently. Neurodiversity must be taken into account. Whatever the reason, it’s important to review not just what we write but how.

    A few years back, I was asking for some feedback on how I give feedback. I was given some sound advice, but I also got a surprise comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That wasn’t my intention at all! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. I was horrified … but also thankful. I quickly changed my situation by adding “oh” to my list of replaced words (your choice between aText, TextExpander, or others ) so that when I typed “oh,” it was immediately deleted.

    Something to highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. A positive attitude doesn’t necessarily mean giving in to criticism; it just means that you give it in a respectful and constructive manner, whether it be in the form of criticism or criticism. The nicest thing that you can do for someone is to help them grow.

    We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. The best, most insightful moments for me came when I shared a comment and asked a trusted person how it sounds, how can I do it better, or even” How would you have written it”? I discovered that by seeing the two versions side by side, I’ve learned a lot.

    The format

    Asynchronous feedback also has a significant inherent benefit: we can devote more time to making sure that the suggestions ‘ clarity of communication and actionability meet two main objectives.

    Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. There are many ways to accomplish this, and context is of course important, but let’s try to think about some things that might be worthwhile to take into account.

    In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you have a thorough understanding of the project, or is this your first encounter with it? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s point of view do you consider when providing feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

    Even if you’re giving feedback to a team that already has some background information on the project, providing context is helpful. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

    We frequently concentrate on the negatives and attempt to list every improvement that could be made. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. Although this may seem superfluous, it’s important to keep in mind that design is a field with hundreds of possible solutions for each problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. Positive feedback can also help, as an added bonus, prevent impostor syndrome.

    There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo ( compared to a previous iteration, competitors, or benchmarks ) and why, and then on that foundation, you can add what could be improved. This is powerful because there is a big difference between a critique of a design that is already in good shape and one that is critiqued for a design that isn’t quite there yet.

    Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. It’s” This button isn’t well aligned” versus” You haven’t aligned this button well”. This can be changed in your writing very quickly by reviewing it just before sending.

    In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. You might also consider breaking up the feedback into sections or even across multiple comments if it is longer. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

    One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. A red square indicates that it is something I consider blocking, a yellow diamond indicates that it should be changed, and a green circle indicates that it is fully confirmed. I also use a blue spiral � � for either something that I’m not sure about, an exploration, an open alternative, or just a note. However, I’d only use this strategy on teams where I’ve already established a high level of trust because the impact could be quite demoralizing if I had to deliver a lot of red squares, and I’d change how I’d communicate that a little.

    Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

    • 🔶 Navigation—I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
    • � � Overall— I think the page is solid, and this is good enough to be our release candidate for a version 1.0.
    • � � Metrics—Good improvement in the buttons on the metrics area, the improved contrast and new focus style make them more accessible.
    • Button Style: Using the green accent in this context gives the impression that it’s a positive action because green is typically seen as a confirmation color. Do we need to explore a different color?
    • Considering the number of items on the page and the overall page hierarchy, it seems to me that the tiles should use Subtitle 2 instead of Subtitle 1. This will keep the visual hierarchy more consistent.
    • � � Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the purpose of using that?

    What about giving feedback directly in Figma or another design tool that allows in-place feedback? These are generally difficult to use because they conceal discussions and are harder to follow, but in the right setting, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

    One final note: say the obvious. Sometimes we might feel that something is clearly right or wrong, and we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

    Asynchronous feedback also has the benefit of automatically guiding decisions, according to writing. Especially in large projects,” Why did we do this”? There’s nothing better than open, transparent discussions that can be reviewed at any time, and this could be a question that arises from time to time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved.

    Content, tone, and format. Although each of these subjects offers a useful model, improving eight of the subjects ‘ observation, impact, question, timing, attitude, form, clarity, and actionability is a lot of work to put in all at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others ) and start there. Then the third, the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

    Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

  • Asynchronous Design Critique: Getting Feedback

    Asynchronous Design Critique: Getting Feedback

    ” Any feedback?” is perhaps one of the worst ways to ask for opinions. It’s obscure and unreliable, and it doesn’t give a clear picture of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

    Starting the process of receiving feedback with a question may seem counterintuitive, but it makes sense if we consider that receiving input can be considered a form of pattern research. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

    Design criticism is not a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

    And suddenly, as with any great research, we need to examine what we got up, get to the base of its perspectives, and take action. Problem, generation, and analysis. This look at each of those.

    The query

    Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your mind” at the end of a presentation are likely to garner a lot of different ideas, or worse, to make people follow the lead of the first speaker. And next… we get frustrated because vague issues like those you turn a high-level moves review into folks rather commenting on the borders of buttons. Which topic may be a savory one, so it might be difficult to get the team to switch to the subject you wanted to concentrate on.

    But how do we get into this scenario? It’s a combination of various aspects. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the issue open and assume that everyone else will agree. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, so we don’t work to make them better.

    The work of asking good questions guidelines and focuses the criticism. It’s even a form of acceptance because it specifies what kind of feedback you’d like to receive and how you’re open to them. It puts people in the right emotional state, especially in situations when they weren’t expecting to give opinions.

    There isn’t a second best way to ask for opinions. It simply needs to be certain, and sensitivity can take several shapes. The concept of stage than level is a design for design criticism that I’ve found to be particularly helpful in my coaching.

    Stage” refers to each of the steps of the process—in our event, the design process. The type of input changes as the customer research moves on to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed comments into updated designs as the project has evolved. The layers of user experience could serve as a starting point for potential questions. What do you want to know: Project objectives? user requirements? Functionality? the content Interaction design? Information architecture UI design? Navigation planning? Visual design? Branding?

    Here’re a few example questions that are precise and to the point that refer to different layers:

    • Functionality: Is it desirable to automate account creation?
    • Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
    • Information architecture: This page contains two competing pieces of information. Is the structure effective in communicating them both?
    • User interface design: What do you think about the top-most error counter, which ensures that you can see the next error even when the error is outside the viewport?
    • Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Exist any recommendations for resolving this?
    • Visual design: Are the sticky notifications in the bottom-right corner visible enough?

    The other axis of specificity is determined by how far you would like to go with the presentation. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially helpful when switching between iterations because it’s crucial to highlight the changes made.

    There are other things that we can consider when we want to achieve more specific—and more effective—questions.

    A quick fix is to get rid of the generic qualifiers from questions like “good,” “well,” “nice,” “bad,” “okay,” and” cool.” For example, asking,” When the block opens and the buttons appear, is this interaction good”? is possible to appear specific, but the “good” qualifier can be found in an even better question,” When the block opens and the buttons appear, is it clear what the next action is?”

    Sometimes we actually do want broad feedback. Although that’s uncommon, it can occur. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps just say,” At first glance, what do you think”? so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

    Sometimes the project is particularly broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding getting back into rabbit holes like those that could lead to even more refinement if what’s important right now isn’t.

    Asking specific questions can completely change the quality of the feedback that you receive. Even experienced designers will appreciate the clarity and efficiency gained from concentrating solely on what is required, and those with less refined critique skills will now be able to offer more actionable feedback. It can save a lot of time and frustration.

    The iteration

    Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Many design tools have inline commenting, but many of those methods typically display changes as a single fluid stream in the same file. These methods cause conversations to vanish once they’re resolved, update shared UI components automatically, and require designs to always display the most recent version unless these would-be useful features were manually turned off. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That’s probably not the most effective way to go about designing critiques, but even if I don’t want to be too prescriptive, it might work for some teams.

    The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. For this, I’ll use the term iteration post. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. This can be used on any platform that can accommodate this structure. By the way, when I refer to a “write-up or presentation“, I’m including video recordings or other media too: as long as it’s asynchronous, it works.

    Using iteration posts has a number of benefits:

    • It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
    • Decisions are always available, and conversations are also made accessible for future review.
    • It creates a record of how the design changed over time.
    • It might also make it simpler to collect and act on feedback depending on the tool.

    These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. And from there, other feedback techniques ( such as live critique, pair designing, or inline comments ) can emerge.

    I don’t think there’s a standard format for iteration posts. However, there are a few high-level components that make sense to include as a baseline:

    1. The goal
    2. The layout
    3. The list of changes
    4. The querys

    Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. In every iteration post, I would copy and paste this, so I could do it again. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. The most recent iteration post will have everything I need if I want to know about the most recent design.

    This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts helps to ensure that everyone is on the same page.

    The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. It’s any design object, to put it briefly. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture.

    It might also be helpful to have clear names on the artifacts so that it is easier to refer to them. Write the post in a way that helps people understand the work. It’s not very different from creating a strong live presentation.

    For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

    Finally, as mentioned earlier, a list of the questions must be included in order to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

    Not every iteration is the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then, later, the iterations begin coming to a decision and improving it until the feature development is complete.

    I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be a draft, just a concept to start a discussion, or it might be a cumulative list of all the features that have been added over the course of each iteration until the full picture is achieved.

    Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

    • Unique—It’s a clear unique marker. Everyone knows where to go to review things, and it’s simple to say” This was discussed in i4″ with each project.
    • Unassuming—It works like versions ( such as v1, v2, and v3 ) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Exploratory, incomplete, or partial should be the definition of an argument.
    • Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

    The wording release candidate (RC ) could be used to describe a design as complete enough to be worked on, even if there might be some bits that still need more attention and in turn, more iterations would be required, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

    The review

    What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, when we work asynchronously, using a different approach is more effective: we can adopt a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

    Asynchronous feedback is particularly effective around these friction points because of this shift’s significant benefits:

    1. It removes the pressure to reply to everyone.
    2. It lessens the annoyance of snoop-by comments.
    3. It lessens our personal stake.

    The first friction is being forced to respond to every comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s simple, and there isn’t much of a problem with it. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. If the respondent is a stakeholder or a person directly involved in the project, this might be especially true. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. When we treat a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives: In asynchronous spaces, responding to all comments can be effective.

      One is to let the next iteration speak for itself. The response is received when the design changes and a follow-up iteration is made. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
    • Another tactic is to formally acknowledge each comment in a brief response, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. In the upcoming iteration, I’ll include these. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
    • One more thing is to quickly summarize the comments before proceeding. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

    The swoop-by comment, which is the kind of feedback that comes from a member of the project or team who might not be aware of the context, restrictions, decisions, or requirements —or of the discussions from earlier iterations. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep saying the same thing over and over.

    Let’s begin by acknowledging again that there’s no need to reply to every comment. However, if responding to a previously litigated point is useful, a brief response with a link to the previous discussion for additional information is typically sufficient. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

    Swoop-by commenting can still be useful for two reasons: first, they might point out something that isn’t clear, and second, they might have the power to represent a user’s first impression of the design. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

    The personal stake we might have in relation to the design could be the third friction point, which might cause us to feel defensive if the review turned out to be more of a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego ( because yes, even if we don’t want to admit it, it’s there ). In the end, presenting everything in aggregated form helps us to prioritize our work more.

    Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come to a decision that can be justified, but sometimes “no” is the best choice.

    As the designer leading the project, you’re in charge of that decision. In the end, everyone has their area of expertise, and as a designer, you are the one with the most background and knowledge to make the right choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

    Thanks to Mike Shelton and Brie Anne Demkiw for their contributions to the initial draft of this article.

  • Designing for the Unexpected

    Designing for the Unexpected

    Although I’m not sure when I first heard this statement, it has stuck with me over the centuries. How do you generate solutions for scenarios you can’t think? Or create items that are functional on products that have not yet been created?

    Flash, Photoshop, and flexible pattern

    When I first started designing sites, my go-to technology was Photoshop. I set about making a layout that I would eventually drop content into a 960px cloth. The growth phase was about attaining pixel-perfect reliability using set widths, fixed levels, and absolute placement.

    All of this was altered by Ethan Marcotte’s speak at An Event Apart and the subsequent article in A Checklist Off in 2010. I was sold on responsive pattern as soon as I heard about it, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.

    My first encounter with flexible style didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. You can’t really put responsiveness at the end of a job, which I learned the hard way. To make smooth design, you need to prepare throughout the style stage.

    A new way to style

    Making articles accessible to all devices a priority when designing responsive or liquid websites has always been the goal. It relies on the use of percentage-based design, which I immediately achieved with local CSS and power groups:

    .column-span-6 { width: 49%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-4 { width: 32%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-3 { width: 24%; float: left; margin-right: 0.5%; margin-left: 0.5%;}

    Therefore using Sass to re-use repeated slabs of code and transition to more semantic premium:

    .logo { @include colSpan(6);}.search { @include colSpan(3);}.social-share { @include colSpan(3);}

    Media answers

    The next ingredient for flexible design is press queries. Without them, regardless of whether the information was still readable, may reduce to fit the available space.

    Media answers prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on. 

    For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.

    String premium was a mainstay of early flexible design, present in all the frequently used systems like Bootstrap and Skeleton.

    1 of 7
    2 of 7
    3 of 7
    4 of 7
    5 of 7
    6 of 7
    7 of 7

    Another difficulty arose as I moved from a design firm building websites for little- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those capacities, I began to work many more with washable pieces.

    Our rely on multimedia queries resulted in parts that were tied to frequent screen sizes. If the goal of part libraries is modify, then this is a real problem because you can just use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process never really hitting that “devices that don’t already occur” goal.

    Then there’s the problem of space. Media answers allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?

    Container queries: our savior or a false dawn?

    Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. There are workarounds for JavaScript, but they can lead to dependencies and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.

    One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is an important step in moving toward a form of component-based design that works at any size on any device.

    In other words, responsive layouts are to be replaced by responsive components.

    Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.

    We still use layout to determine when a design needs to adapt, which is my concern. This approach will always be restrictive, as we will still need pre-defined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component?

    The best place to make that choice is probably not a component library that is disconnected from context and real content.

    As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?

    In this example, the dimensions of the container are not what should dictate the design, rather, the image is.

    Without reliable cross-browser support for them, it’s difficult to say for certain whether container queries will be successful. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might always need to modify these elements to fit our content.

    CSS is changing

    Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.

    .wrapper { display: grid; grid-template-columns: repeat(auto-fit, 450px); gap: 10px;}

    The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space. 

    .wrapper { display: flex; flex-wrap: wrap; justify-content: space-between;}.child { flex-basis: 32%; margin-bottom: 20px;}

    The biggest benefit of all of this is that you don’t have to wrap elements in container rows. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.

    This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid.

    Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?

    Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.

    .wrapper { display: grid; grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); grid-template-rows: auto 1fr auto; gap: 10px;}.sub-grid { display: grid; grid-row: span 3; grid-template-rows: subgrid; /* sets rows to parent grid */}

    CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. Subgrid is only supported by Firefox at the time of writing, but the above code can be implemented behind an @supports feature query.

    Intrinsic layouts

    I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional CSS features used to create layouts that respond to available space.

    Responsive layouts have flexible columns using percentages. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.

    frunits is a statement that says,” I want you to distribute the extra space in this way, but… don’t ever make it smaller than the content that is inside of it.”

    —Jen Simmons,” Designing Intrinsic Layouts”

    Intrinsic layouts can also make use of a mix of fixed and flexible units, letting the content choose how much space it occupies.

    What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Without having the same breakpoints or the same amount of content as in the previous implementation, components and patterns can be lifted and reused.

    We can now create designs that adapt to the space they have, the content within them, and the content around them. We can create responsive components using an intrinsic approach without relying on container queries.

    Another 2010 moment?

    This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. It’s another “everything changed” moment for me.

    But it doesn’t seem to be moving quite as fast, I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention.

    One possible explanation for that might be that I now work for a sizable company, which is significantly different from the role I held as a design agency in 2010: In my agency days, every new project was a clean slate, a chance to try something new. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase.

    Another possibility is that I’m now more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s a different way to use existing skills and CSS knowledge.

    You can’t framework your way out of a content problem

    Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change.

    Ten years ago, responsive grid systems were everywhere. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

    Because having a selection of units is a benefit when creating layout templates, intrinsic design and frameworks do not go hand in hand quite as well. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

    And then there are design tools. We probably all used Photoshop templates for desktop, tablet, and mobile devices at some point in our careers to drop designs in and demonstrate how the site would look at each of the three stages.

    How do you do that now, with each component responding to content and layouts flexing as and when they need to? Personally, I’m a big fan of this kind of design in the browser.

    The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. It’s not ideal to do this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it continue to function? Is the design too reliant on the current content?

    Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.

    First, the content

    Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account changes in content, like in our earlier Subgrid card illustration, which allowed the cards to modify both their own content and that of their sibling components.

    Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.

    This is not the same as previous markup hacks like this.

    First line of text with different styling...

    —we can target content based on where it appears.

    .element::first-line { font-size: 1.4em;}.element::first-letter { color: red;}

    Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().

    This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

    Directional variables must be set in the Sass version.

    $direction: rtl;$opposite-direction: ltr;$start-direction: right;$end-direction: left;

    These variables can be used as values—

    body { direction: $direction; text-align: $start-direction;}

    —or as properties.

    margin-#{$end-direction}: 10px;padding-#{$start-direction}: 10px;

    However, now we have native logical properties, removing the reliance on both Sass ( or a similar tool ) and pre-planning that necessitated using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.

    margin-block-end: 10px;padding-block-start: 10px;

    There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.

    Like the earlier examples, these properties help to build out designs that aren’t constrained to one language, the design will reflect the content’s needs.

    Fluid and fixed

    We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative. 

    For min() this means setting a fluid minimum value and a maximum fixed value.

    .element { width: min(50%, 300px);}

    The element in the figure above will be 50 % of its container as long as the element’s width doesn’t exceed 300px.

    For max() we can set a flexible max value and a minimum fixed value.

    .element { width: max(50%, 300px);}

    Now the element will be 50 % of its container as long as the element’s width is at least 300px. This means we can set limits but allow content to react to the available space.

    The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.

    .element { width: clamp(300px, 50%, 600px);}

    This time, the element’s width will be 50 % of its container’s preferred value, with no exceptions for 300px and 600px.

    With these techniques, we have a content-first approach to responsive design. We can separate content from markup, meaning the changes users make will not affect the design. By anticipating unforeseen language or direction changes, we can begin creating future-proofing designs. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

    First, the circumstances

    Thanks to what we’ve discussed so far, we can cover device flexibility by changing our approach, designing around content and space instead of catering to devices. But what about that last bit of Jeffrey Zeldman’s quote,”… situations you haven’t imagined”?

    It’s a lot different to design for someone using a mobile phone and walking through a crowded street in glaring sunshine than it is for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

    This is why making a decision is so crucial. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

    Thankfully, there is a lot we can do to provide choice.

    Responsible design

    ” There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure”.

    I Used the Web for a Day on a 50 MB Budget.”

    Chris Ashton

    One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. However, our users may be commuters using smaller mobile devices that may experience disconnects in connectivity in the real world. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.

    The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.

    Image alt text

    The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience. 

      

    There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.

    …

    With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make. 

    So how can we put users in control?

    The media queries are now being returned.

    Media answers have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.

    We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. These checks allow us to provide options that suit more than one scenario, it’s less about one-size-fits-all and more about serving adaptable content.

    The Level 5 spec for Media Queries is still being developed as of this writing. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

    For instance, a light-level option lets you alter a user’s style when they are in the dark or in the sun. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.

    @media (light-level: normal) { --background-color: #fff; --text-color: #0b0c0c; }@media (light-level: dim) { --background-color: #efd226; --text-color: #0b0c0c;}

    Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable. 

    Media answers like this go beyond choices made by a browser to grant more control to the user.

    Expect the unexpected

    In the end, we should always anticipate that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

    We can design for content, but we can’t do it for this constantly changing landscape. By putting content first and allowing that content to adapt to whatever space surrounds it, we can create more robust, flexible designs that increase the longevity of our products.

    A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. There are still many more things we can do to adopt a more intrinsic approach, from responsive to fluid and fixed. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

    When it comes to unexpected circumstances, we need to make sure our goods are accessible whenever and wherever needed. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries.

    Good design for the unexpected should allow for change, provide choice, and give control to those we serve: our users themselves.

  • Voice Content and Usability

    Voice Content and Usability

    We’ve been conversing for many thousands of years. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have we begun to write our conversations, and only recently have we outsourced them to the system, a system that exhibits a far greater affection for written communications than for the vernacular rigors of spoken speech.

    Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the complexity of human statement, including the pauses and pauses, the gestures and brain speech, and the word selection and spoken dialect variations that can impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.

    In contrast, written language develops its own fossil record of dated terms and phrases as we report it and keep utilization long after they are no longer needed in spoken communication ( for example, the welcome” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for devices to interpret and know.

    Spoken speech lacks this pleasure. Besides the visual cues that mark conversations with emphasis and personal context, there are also linguistic cues and outspoken behaviors that mimic conversation in complex ways: how something is said, never what. Our spoken speech conveys much more than the written word may actually contain, whether it be rapid-fire, low-pitched, or high-decibel, sarcastic, awkward, or moaning. But when it comes to words interfaces—the devices we conduct spoken discussions with—we experience exciting difficulties as designers and content strategists.

    Voice Compositions

    We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too ( ). We typically strike up a discussion in the following ways:

    • we need something done ( such as a transaction ),
    • we want to know everything, some kind of knowledge, or
    • we are social people and want someone to talk to ( conversation for conversation’s pleasure ).

    These three categories, which I refer to as interpersonal, technical, and prosocial, also apply to virtually every voice interaction: a solitary conversation that begins with the voice interface’s initial greeting and ends with the user leaving the interface. Notice here that a discussion in our individual sense—a talk between people that leads to some outcome and lasts an arbitrary length of time—could encompass many interpersonal, technical, and altruistic voice interactions in succession. In other words, a voice interaction is a conversation, but it must not be one particular voice interaction.

    Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. Additionally, there is ongoing debate about whether users actually prefer the type of organic human conversation that starts with a prosocial voice and progresses seamlessly into new ones. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users ‘ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ( ).

    That leaves two different types of conversations we can have with one another that a voice interface can also have easily, such as one that focuses on a transactional voice interaction ( buying iced tea ) and another on learning something new ( discuss a musical ).

    Transactional voice interactions

    When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza ( generously topped with pineapple, as it should be ).

    How are things going, Alison?

    Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

    Alison, can I get a pineapple-onion pizza in Hawaii?

    Burhan: Sure, what size?

    Large, Alison.

    Burhan: Anything else?

    Alison: No thanks, that’s it.

    Burhan: Something to drink?

    Alison, I’ll have a bottle of Coke.

    Burhan: You got it. That will cost$ 13.55 and take about fifteen minutes.

    Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Conversations that are transactional have certain characteristics: they are direct, concise, and cost-effective. They quickly dispense with pleasantries.

    Informational voice interactions

    Meanwhile, some conversations are primarily about obtaining information. Alison might only want to place an order at Crust Deluxe, but she might not want to leave without a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Even though we have a prosocial mini-conversation once more at the beginning to establish politeness, we’re after much more.

    How are things going, Alison?

    Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

    Alison: Can I ask a few questions?

    Burhan: Of course! Go right ahead.

    Do you have any halal options on the menu, Alison?

    Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Do you have any other dietary restrictions in mind?

    Alison: What about gluten-free pizzas?

    Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you, without a problem. Anything else I can answer for you?

    Alison: That’s it for the moment. Good to know. Thank you.

    Burhan: Anytime, come back soon!

    This dialogue is entirely different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions that seek the truth through information gathering. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. In order for the customer to understand the key takeaways, responses are typically longer, more in-depth, and carefully communicated.

    Voice Interfaces

    Voice-based user interfaces use speech at the core to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned with pure voice interfaces, which depend entirely on spoken conversation and lack any visual component, making multimodal voice interfaces much more nuanced and challenging to deal with because they can lean on visual components like screens as crutches.

    Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

    IVR ( interactive voice response ) systems

    Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech ( TTS ) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. We became familiar with the first real voice interfaces that engaged in authentic conversation with the advent of interactive voice response ( IVR ) systems, which were created as an alternative to overburdened customer service representatives.

    IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. When you call an airline or hotel company, which is a common practice in the corporate world, these systems were primarily intended as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), which are more likely to happen when you call one. Despite their functional issues and users ‘ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

    IVR systems have a reputation for having less scintillating conversations than we’re used to in real life ( or even in science fiction ), despite being extremely repetitive and monotonous.

    Screen readers

    The screen reader, a program that converts visual information into synthesized speech, was a development that accompanied the development of IVR systems. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Perhaps the closest thing we have today to an out-of-the-box delivery of content via voice is represented by screen readers.

    Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 ( ). In the same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, which was later reworked for computers with graphical user interfaces ( GUIs ) ( ).

    With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Screen readers started facilitating quick interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one with the introduction of semantic HTML and especially ARIA roles in 2008, allowing them to do so in an aural and temporal space. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. in A List Apart, writes Aaron Gustafson, “into useful information.” ” At least they do when documents are authored thoughtfully” ( ).

    There is a big draw for screen readers: they’re challenging to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. Working with web-based interfaces takes a cognitive toll for many screen reader users.

    In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

    I disliked the operation of Screen Readers from the beginning. Why are they designed the way they are? It makes no sense to present information visually before converting it to audio only after that. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information without worrying about it. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.

    Voice assistants

    Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film A Space Odyssey or with Majel Barrett’s voice as the omniscient computer from Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And because of their assistive potential, they are quickly receiving more attention from accessibility advocates.

    Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

    There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 1 ). At one extreme, everything except vendor-provided features is locked down, for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.

    At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, developers who feel constrained by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are extensibable and customizable. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Users can choose from among the thousands of custom-built skills available today in the Google Assistant and Amazon Alexa ecosystems.

    As businesses like Amazon, Apple, Microsoft, and Google continue to dominate their markets, they are also selling and open-sourcing an unmatched range of tools and frameworks for designers and developers, aiming to make creating voice interfaces as simple as possible, even without the use of any code.

    Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. In contrast, many development platforms, such as Google’s Dialogflow, have omnichannel capabilities that allow users to create a single conversational interface that then manifests as a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

    Voice content

    Simply put, voice content is content delivered through voice. Voice content must be free-flowing and organic, contextless and concise in order to preserve what makes human conversation so compelling in the first place. Everything written content is not.

    Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. We’re most concerned with the content in this book being delivered auditorically, not as an option but as a necessity.

    For many of us, our first foray into informational voice interfaces will be to deliver content to users. There is only one issue: any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice movements?

    Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while extending like microfilm viewers of newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

    An example of microcontent can be a day’s weather forecast [sic], an airplane flight’s arrival and departure times, an abstract from a lengthy publication, or a single instant message. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    I would update Dash’s definition of microcontent to include all instances of bite-sized content that goes beyond written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. The best way to learn how to stretch your content to the limits of its potential is through microcontent, which will inform both established and new delivery methods.

    As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly look at a digital sign for an instant and be informed when the next train is coming, but voice interfaces keep our attention captive for so long that we can’t quickly evade or skip, a feature that screen reader users are all too familiar with.

    Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

    Our voice content’s legibility and discoverability in general both depend on how it manifests in terms of perceived space and time.

  • Sustainable Web Design, An Excerpt

    Sustainable Web Design, An Excerpt

    Some members of the elite running group were beginning to think it was impossible to run a hour in less than four hours in the 1950s. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

    But Roger Bannister surprised all on May 6, 1956. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

    The world today knew that the four-minute hour was possible because of this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Finally, a year later, three runners all managed to cross the four-minute hurdle in the same culture. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

    We accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for man running speed, we also think there are the strictest requirements for how a website should do.

    Establishing requirements for a green website

    The key indicators of climate performance in most big companies are pretty well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. However, we are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods to do so.

    The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the CO2 output of a online product. We can’t assess the pollutants coming out of the exhaust valves on our laptops. Our websites produce far-away, invisible, and unremarkable emissions when they leave fuel and gas-burning power plants. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. What then do we do?

    If we can‘t measure the actual carbon pollution, therefore we need to get what we can measure. The following are the main elements that could be used as coal pollution gauges:

    1. Transfer of data
    2. Electricity’s carbon power

    Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

    Transfer of data

    Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a reliable indicator of how much power is being consumed and how much coal is being released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.

    The page weight, or the page’s transfer size in kilobytes, can be most easily calculated for a single visit for web pages. It’s fairly easy to measure using the developer tools in any modern web browser. Frequently, the statistics for the total data transfer of any web application are included in your web hosting account ( Fig. 2.1 ).

    The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes.

    A large scope is necessary to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for roughly half of this data transfer, making them the single biggest contributor to carbon emissions on a typical website.

    History clearly shows us that our web pages can be smaller, if only we set our minds to it. While the majority of technologies, including the underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.

    You may be aware of the idea of performance budgeting as a method for directing a project team to deliver faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than vague suggestions, much like speed limits while driving, so the goal should always be to come within budget.

    Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Page weight and transfer size are more objective and reliable benchmarks for sustainable web design, whereas web performance often depends more on the user’s perception of load times than it does on how effective the underlying system is.

    We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use the page weight to compare it to competitors or the outdated website we’re replacing. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.

    We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, repeat users who load the same page frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all of the files back on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Moving beyond the first visit and measuring page weight budgets for scenarios beyond this level of detail can help us learn even more about how to optimize efficiency for users who regularly visit our pages.

    Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose carbon emissions and energy consumption data, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

    In summary, less data transfer leads to more energy efficiency, which is a crucial component of lowering web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some power.

    Electricity’s carbon power

    Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” (gCO2/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity ). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO2/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO2/k Wh.

    The majority of electricity is produced by national or state grids, which combine energy from a variety of sources with different carbon intensity levels. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

    Although we have some control over where our projects are hosted, we do not have complete control over the energy supply of web services. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. This user-provided data is reported and mapped by Danish startup Tomorrow, and a look at their map demonstrates how, for instance, choosing a data center in France will result in significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

    However, we don’t want to move our servers too far away from our users because it requires a lot of energy to transmit data through the telecom’s networks, and the more energy is used, the further the data travels. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

    We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance from that location to the data center used by our hosting company by using the distance itself as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.

    For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could look up the travel distance between London and San Francisco, which is 5,300 miles. That’s a long way! We can see how significantly lessening the distance and energy needed to transmit the data would be if it was hosted somewhere in North America, ideally on the West Coast. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

    Reverting it to carbon emissions

    If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. The method my team developed converts the amount of electricity transferred when loading a web page into a CO2 figure ( Fig. 2.4), and then converts that data into a figure for the tool. It also factors in whether or not the web hosting is powered by renewable energy.

    The Energy and Emissions Worksheet that comes with this book teaches you how to take it one step further and tailor the data more precisely to the unique aspects of your project.

    With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO2 is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds a layer of abstraction that isn’t as intuitive, carbon budgets do focus our minds on the main thing we’re trying to reduce, which supports the main goal of sustainable web design: reducing carbon emissions.

    Browser Energy

    Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

    One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational load is increasingly shifting from the data center to users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React make it possible to create applications where the” thinking” process is performed either partially or completely in the browser.

    All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more energy is used by the user’s devices as a result of the user’s web browser’s increased computation. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally exclude users with older, slower devices and make the batteries on phones and laptops drain more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only harms the environment, but it places a disproportionate financial burden on the poorest members of society.

    In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the Safari browser’s developer console ( Fig. 2.5 ) is one of the tools we currently use.

    You know when your computer’s cooling fans start spinning so frantically that you suspect it might take off when you load a website? That’s essentially what this tool is measuring.

    It uses these figures to create an energy impact rating based on the percentage of CPU used and how long it took the web page to load. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.