『The Experience Strategy Podcast』のカバーアート

The Experience Strategy Podcast

The Experience Strategy Podcast

著者： Dave Norton Aransas Savas and Joe Pine
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概要
 With over 100 episodes, the Experience Strategy Podcast is that secret superpower that helps strategists around the world grow their business acumen. Your hosts, Aransas Savas, Joe Pine, and Dave Norton discuss the most important topics in the business world, but they do it by focusing on the experiences and transformations that customers attain.2024 マネジメント マネジメント・リーダーシップ 経済学
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  • Etsy Learns About Situational Markets and Customization

    Etsy Learns About Situational Markets and Customization
    2026/11/09

    The Experience Strategy Podcast

    Hosts: Aransas Savas | Joe Pine, author of The Transformation Economy | Dave Norton, PhD, author of Human Context: How Intelligent Companies Build Customers

    Episode Overview

    A Wall Street Journal article on Etsy's AI-powered personalization push gives the hosts a real-world case study in what happens when companies finally stop confusing purchase history with preference — and start thinking in situations. The results are hard to argue with: Etsy's sales are up 7.5% since they began making the shift.

    What We Cover

    What Etsy got wrong — and what they're fixing
    Etsy's recommendation engine was built on Bayesian algorithms that treated every purchase as a revealed preference. Buy a onesie, and the system assumes you must love baby gear. The obvious problem: most people buying baby gifts are not having babies. Etsy figured this out themselves and began reworking their algorithms to identify whether someone is shopping for themselves or for someone else — and to make recommendations based on that context rather than raw purchase history.

    Purchase history is not preference
    Joe draws a distinction worth holding onto: purchases can be one-offs, while preferences tend to persist. The two are not the same thing, and conflating them is what produces the kind of recommendations that make customers feel like the system simply isn't listening. Dave puts it plainly — most retailers have built their entire recommendation infrastructure on a faulty assumption.

    The situation Etsy is still missing
    Etsy is asking the right question — gift or self-purchase — but that is only the beginning. What the hosts push toward is the fuller situational picture: what mode is the shopper in? What is the occasion? What is the relationship between the buyer and the recipient? Those questions are not being asked yet, and the gap between where Etsy is and where they could be is significant.

    Spotify's approach as a signal
    Aransas flags a Spotify feature that inverts the usual dynamic: instead of inferring everything from behavior, it simply asks. Tell us what you like to listen to in the mornings. What are we missing? The survey feeds directly into the listening experience with no human intermediary. Joe reframes it: this is not a survey in the marketing research sense. It is a tool for understanding individual customers in real time.

    The Muse disruption on the horizon
    Dave brings the conversation back to the larger threat. Personal AI agents — Muse and those like it — are going to know each user's context in a way that Etsy, Amazon, and every other retailer cannot match from the outside. The agent will do the shopping. Amazon has already blocked Muse for exactly this reason. Retailers who are not building toward situational understanding now are not behind on a future problem — they are behind on a current one.

    Etsy's homepage tells the story
    Four of Etsy's seven navigation tabs are gift-oriented. Aransas notes that once you click into the gifts section, the site does ask who you are shopping for and for what occasion — which is real progress. But the entire frame assumes gifting as the default context, leaving significant surface area unaddressed for shoppers who are there for themselves.

    Key Idea

    If you can see that something is going to become a problem in the future, it is a problem now. The retailers who are treating contextual personalization as a roadmap item — rather than an urgent response to present disruption — are already behind.

    Resources Mentioned

    • Etsy Aims to Get More Personal and Boost Business with AI — Jennifer Williams, Wall Street Journal
    • Muse Is a Wake-Up Call to Any Customer-Facing Company — Dave Norton, The Experience Strategist on Substack
    • Human Context: How Intelligent Companies Build Customers — Dave Norton
    • The Transformation Economy — Joe Pine

    Continue the conversation at the Experience Strategy Substack. New episodes drop weekly.
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    16 分
  • Speed Puzzling, Midlife Pivots, and the Case for Dumb Solutions

    Speed Puzzling, Midlife Pivots, and the Case for Dumb Solutions
    2026/10/28
    The Experience Strategy Podcast | theexperiencestrategist.substack.com We rarely bring guests onto the show. But when Dave heard Jarrett King's story — a layoff, a national speed puzzling competition, and a new puzzle company built from scratch in 90 days — he knew the audience needed to hear it. This episode is part entrepreneurship story, part experience strategy case study, and part argument for why the most human solutions might be the ones with no intelligence in them at all. What's in This Episode Who is Jarrett King? A marketer and designer with a long corporate career who, after a role elimination in December 2024, found herself with open time and an old passion: jigsaw puzzles. She'd been puzzling since age five — her grandmother's kitchen table, beach vacations, COVID lockdowns. What she didn't know existed was competitive speed puzzling. How speed puzzling works. The USA Jigsaw Puzzling Association governs competitive speed puzzling and puts on a national championship. Pairs have one hour and fifteen minutes to complete a 500-piece puzzle. Solo competitors get an hour and a half. There are heats, state championships, and a national event — held in Atlanta, both last year and again this coming March. Jarrett found out about the organization in October 2024, went through a layoff six weeks later, and spent her holiday downtime doing what felt natural: training. The 90-day sprint. Starting January 1st — literally on New Year's Day, spreadsheet open, puzzle boxes open — Jarrett and her co-founder went from zero speed puzzling experience to competing at the Georgia State Championship in February. They finished in one hour and thirteen minutes, just under the wire. Two minutes to spare, next to a Delta Airlines corporate team. They were near last. They were thrilled. A month later at nationals, they didn't finish in time — but neither did 67 of the other 200 teams. And that failure launched the company. The puzzle design question that started a business. When you DNF at nationals because the puzzle was particularly hard, and you're a marketer and designer by training, you start asking: what actually makes a good puzzle? Not good for casual solving — good for competitive speed puzzling, where you're spending so much time with the art that the distinctions between pieces become critical. Jarrett's framework: color palette range (too many colors or too few both create different challenges), line clarity (hand-drawn thick lines versus blurry or muddy edges), and pattern and texture variation within similar color zones. What emerged was a product company built around getting these things right. No AI art. Ever. Borderline Obsessive Puzzles has made a public pledge: no AI-generated art in their puzzles. Their mission is to feature the work of human artists and creatives — and to support the artisans behind the physical product too, including the craftsman who hand-bent every piece of metal in the die that will cut their puzzles. Jarrett watched him work in person. The guy has spent decades learning that craft. That's what's behind the physical object. Why this is a perfect dumb solution — in the best sense. Dave brings it back to the framework from Human Context: puzzles are a dumb solution. No intelligence. No data layer. No sense-and-respond loop. And right now, that's a feature, not a limitation. There's a growing consumer release happening — a desire to set the screen down, engage differently, and experience something that is purely, beautifully human. Jarrett sees it in the speed puzzling community: Gen Z participants who are vocal about AI fatigue, gravitating toward analog activities that open creative pathways. The same reason companies used to bring fidget toys into brainstorming sessions — puzzles open neural firing that doesn't happen in front of a screen. Accumulated knowledge, applied in new directions. Aransas connects Jarrett's story to the research she's been conducting for Courage Capital — 200+ interviews with women who've made significant midlife pivots. The consistent pattern: they're not starting from scratch, they're applying decades of accumulated expertise in new domains. Jarrett brings design sensibility, marketing instincts, and consumer research habits to a product category where most competitors are just enthusiasts. That combination is hard to replicate. The fundamentals don't change. As Jarrett puts it: whether it's a digital solution or an analog one, the fundamentals are the same. Put the human at the center, and you get a better outcome. Dave's book was written with AI-powered companies as the primary audience — and here's a puzzle company with no technology at all demonstrating the same principle. About Borderline Obsessive Puzzles Jarrett and her co-founder are building a puzzle company grounded in thoughtful design, human-made art, and competitive-grade quality. Kickstarter campaign (live through November 18): kickstarter.com/projects/...
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    22 分
  • Time Value — The Measurement Framework Every Intelligent Company Needs

    Time Value — The Measurement Framework Every Intelligent Company Needs
    2026/09/24
    The Experience Strategy Podcast | theexperiencestrategist.substack.com Part four of a four-part mini-series unpacking the frameworks in Dave Norton's new book, Human Context: How Intelligent Companies Build Customers. You can build the right market strategy, identify the right situations, understand your customer's mode — and still not know if what you built is actually working. Time value is the measurement framework that closes that gap. In this final episode of the series, Dave explains the four categories of time value, how they map to the Stupid/Dumb/Smart/Genius framework, and why AI creates a compounding effect that changes what customers expect from every minute they spend with a product. What's in This Episode Why time value is the right measurement. NPS, sales lift, likelihood to buy — these are all useful, but they measure the company's outcomes. Time value measures the customer's outcome. When someone uses a tool, an app, a service, or an AI, what they're actually asking is: was this worth my time? That question has always mattered. Now, with AI compressing what used to take months into hours, customers' expectations for the value of their time are rising sharply — and companies that measure with yesterday's metrics will miss what's actually happening. The four categories. The framework has been part of Dave and Joe's work for nearly twenty years, and it's now a central chapter in Human Context: Time wasted — the experience consumed time and delivered nothing. The baseline failure case.Time well saved — the experience completed something faster than the alternative. Adjusting a thermostat with Alexa. Quick, functional, done.Time well spent — the experience was worth being in, beyond just efficiency. Engagement mattered. The person was present and got something from it.Time well invested — the time spent now pays dividends later. A skill developed, a relationship deepened, an outcome that compounds. Any experience — dumb, smart, or genius — can land in any of these categories. A pen and paper can be time well invested. A sophisticated AI tool can be time wasted. The category isn't determined by the technology; it's determined by the customer's experience of it. The compounding effect of genius solutions. With AI, there's a fifth dynamic layered on top: compounding. When a well-trained AI starts doing in hours what used to take months, customers don't just experience time saved — they experience something closer to a superpower. And that changes the baseline expectation. The more capable the tool appears, the less tolerance there is for failure. Dave's point: we need measurement frameworks that account for this — because evaluating a genius solution by the same standards as a dumb one misses what's actually at stake. Stupid is in the incident, not just the category. The episode's sharpest clarification comes through a live case study from the TV show The Pit: a hospital AI tool takes dictation and charts for the doctor, immediately freeing up time. But it mishears a drug name and records the wrong medication. Was it time wasted? Joe's framing cuts through the debate cleanly: an incident can be stupid even when the overall tool is smart. The doubter on the show sees the error and says the whole thing is risky. The loyalist says you still have to proof your work. Both are right in their own frame. Dave's conclusion: if errors like that happen repeatedly, the tool loses value. If it happens occasionally and the system learns from it, the tool gets better. The key variable is whether the person using it can train it. The trainability gap. Companies haven't caught up to what consumers now expect from AI tools. People who use Claude, ChatGPT, or Gemini daily have learned to train their tools — to shape responses, correct mistakes, build better versions over time. Then they open Copilot and find a system that can't learn the way they need it to. Dave's diagnosis: the doctor in The Pit should be able to flag the wrong drug and have the system remember. That's what closes the gap between smart and genius. And it's what most enterprise AI deployments are still missing. What's actually working right now. A quick round of AI tools the hosts are finding genuinely useful: A transcription app (beginning with G) that can handle multi-person conversations at a table, distinguishing speakers in real time.OpenAI's voice interface — Dave's son switched from Claude to ChatGPT specifically for this, and Dave says Siri now feels painful by comparison.Google's paid Workspace / Gemini integration — Aransas is getting smart email suggestions, natural-language search across past conversations, and contact introductions that pull in context automatically. Useful enough to feel slightly unsettling. Three questions for measuring dumb experiences. For solutions with no intelligence layer, Dave offers a simple diagnostic: Did I accomplish what I set out to do? How engaged was I with the ...
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    18 分
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