The Experience Strategy Podcast

Hosted by Dave Norton, Aransas Savas, and Joe Pine

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Aug 2026

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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.

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August 27, 202613 min

Stupid, Dumb, Smart, Genius — The Framework That Tells You When and How to Use AI

The Experience Strategy Podcast | theexperiencestrategist.substack.com Part one of a four-part mini-series unpacking the frameworks in Dave Norton's new book, Human Context: How Intelligent Companies Build Customers. The Stupid/Dumb/Smart/Genius framework has been in use with clients for nearly a decade. It was born in a room in Burbank, in real time, when Joe Pine found himself in the back of a client workshop and Dave told the client that Joe would have a new framework for them. This episode tells that origin story, walks through how the framework works — with examples from glasses to healthcare — and explains why it's never been more relevant than right now. What's in This Episode How the framework was born. Joe and Dave were working with a media company in Burbank. Dave had mapped out consumer insights across a whiteboard — rows, columns, the full picture. Joe, watching from the back of the room, took it as a prompt to build a two-by-two on the spot. The dumb-versus-smart contrast came from the conversation itself: broadcasting is dumb — it sends out a signal with no feedback loop — and the client knew they needed to move toward smart but weren't sure how. From there, the natural extension followed: if dumb has a worse version, it's stupid (intelligence used against the consumer). If smart has a better version, it's genius (intelligence that truly knows and serves the individual). The framework has been a core part of Dave and Joe's client work ever since, and it's now a central chapter in Human Context . What each level actually means: Dumb — no context is being collected or used. Not a pejorative. A pair of glasses that helps you see is dumb. A family doctor who knows your history and gives good care is practicing dumb medicine. The product or service does exactly what it's supposed to do, without any data layer. There will always be a market for dumb — and increasingly, it may feel like a relief. Smart — an iterative sense-and-respond loop. The system collects some data and adjusts. Your streaming service tracking what you watch and making recommendations is smart. Glasses with an audio component connected to your phone are smart. Genius — anticipatory, fully contextual, deeply personalized support. The system knows your history, your situation, your mode, and acts on your behalf before you have to ask. Dave uses the example of a health AI that knows your supplements, your medical history, and the fact that you're going golfing today — and surfaces exactly what you need to know, without a doctor's visit. Meta smart glasses are a current candidate, though the jury's still out. Stupid — intelligence used adversarially against the consumer. Getting in the way of what someone is trying to do. Collecting and deploying data in ways that feel invasive or serve the platform instead of the person. Google Glass — where users were famously called "Glassholes" — is the canonical example. Joe's live case study: Amazon Prime serving him ads for Lioness every single episode, for a show he's already watched in full. That's not smart personalization. That's stupid. The same technology, all four levels at once. The glasses example makes the framework concrete: regular glasses are dumb (and excellent at it). Hearing-aid glasses or phone-connected frames are smart. Meta smart glasses are approaching genius. Google Glass was stupid. One product category, four distinct orientations — and a viable business model for at least three of them. Healthcare is the most important application. The dumb version: fill out the same form you filled out last time, see the doctor, get the prescription. Not bad care — just no data layer. The critical gap Joe identifies: no one has the full picture of what you're taking. Your GP, your specialist, your rheumatologist — each knows their piece. Nobody has the whole context, including your supplements, which means drug interactions go undetected. The genius version: a health AI with your complete medical history, supplement stack, and daily context — flagging what you need to pay attention to before you even call the office, with the doctor as a periodic checkpoint rather than the first point of contact. Consumer expectations will catch up to this. When they do, dumb healthcare won't feel bad — it'll feel retro. The consumer's rising expectations change the baseline. As genius becomes standard, what felt cutting-edge becomes expected, and what was once acceptable starts to feel quaint. Dave's point: companies need to be building toward genius now, because the window in which it's a differentiator is shorter than it looks. This Is Part One of Four The next three mini-episodes unpack the remaining frameworks from Human Context : Part 2: Situational Markets Part 3: Modes Part 4: Time Value Get the Book Human Context: How Intelligent Companies Build Customers by Dave Norton is available now on Amazon (Kindle and print) and on Dave's Substack. The ten industry workbooks — showing how each framework applies to your specific category — are available alongside the book. Questions for the hosts? Reply to any episode email or find us at theexperiencestrategist.substack.com .

August 12, 202625 min

Dave Norton's New Book Is Out — Human Context and the Paradigm Shift Every Company Needs to Make

The Experience Strategy Podcast | theexperiencestrategist.substack.com It's a book launch episode. Human Context: How Intelligent Companies Build Customers — Dave Norton's new book — released yesterday on Amazon. Joe and Aransas have read the galley. This episode covers the why now, the four frameworks at the book's core, and how companies are meant to actually use it. What's in This Episode Why Dave felt compelled to write this now. It goes back to 2015 and Digital Context 2.0 , his first book, in which he argued that context would be the organizing logic that brought channels, tools, and technologies together in service of the human. It didn't quite unfold that way — companies didn't want to share data, API ecosystems were slow to develop, and the consumer-enabling vision got stuck. Then generative AI arrived and changed everything. Context is now the literal engine that makes LLMs work. But there's a problem: every AI company in the world is thinking about context as their asset — something to extract from consumers and use against them to sell more. Dave wrote Human Context to plant a stake in the ground against that direction. The book argues that context belongs to the individual, and intelligent companies will build around enabling people rather than extracting from them. The two definitions of context — and why they matter. Joe sharpens the distinction that runs through the whole book: AI companies think of context as the model's context — the information fed into the system to make it work. What the book argues is that companies need to think about the customer's context — the situations, mindsets, and life circumstances of the individual they're serving. These are not the same thing, and confusing them is how companies end up building technology that serves the platform instead of the person. The four frameworks. The book is organized around four interconnected frameworks: Stupid/Dumb/Smart/Genius — co-developed with Joe Pine in 2016 and referenced in Dave's 2023 HBR article, this framework helps companies understand when and why to use intelligence. Dumb means no context is being collected — not a pejorative, just a description of the state. Smart means iterative sense-and-respond. Genius is what generative AI has now made genuinely possible — anticipatory, deeply contextual support. Stupid is when intelligence is turned adversarially against the consumer: wasting their time, getting in the way, or pursuing nefarious motives. Situational Markets — the move away from demographic targeting toward situations. What people have in common is not age or income bracket — it's that they find themselves in common situations. Companies that learn to identify, size, and design for situations are already operating at a different level of contextual sophistication. Demographics, as Joe puts it memorably, tell you nothing — a point he illustrates with the famous example of two people born the same day in the same town, one of whom became King Charles and the other Ozzy Osbourne. Modes — the mindset and behavioral state a person is in at a given moment. Combined with situation, modes give a company a genuinely rich picture of what the individual needs right now. Dave has been developing this framework for twelve years. Time Value — the measurement framework. How do you evaluate a dumb experience using time value? A smart one? A genius one? The book distinguishes between time saved, time well spent, and time well invested — giving companies a way to think about what their interactions are actually delivering. Demographics and personas: a gentle funeral. Joe makes the case cleanly. Demographics are shifts in bell curves — everyone is somewhere on every curve, and they tell you nothing about what any individual values or needs. Personas were a useful intervention when product designers needed reminding that real humans would use their products. But reducing a person to a persona is an injustice to both the individual and to the company's own capability. The frameworks in Human Context are designed to replace both. How the book is meant to be used. Dave is unapologetic: the book introduces the concepts, but the real work happens in the workbooks. Ten industry-specific workbooks accompany the book — covering how to size situational markets in your category, how to map modes, how to apply the frameworks to your actual business model. There's also a case study. The core ask of the reader: spend real time asking what it would actually take to move away from demographic thinking and start sizing situations instead. How Dave wrote it — and why provenance matters. Every chapter started as Dave's own writing, in some cases material he'd been developing for over a decade. AI was used to synthesize, consolidate, and accelerate — combining multiple drafts, simplifying, and then editing back to his voice. He's transparent about this in the book itself, with a dedicated provenance section. His position: books built with AI assistance should always include provenance notes explaining the origins of the content. All the ideas are his. The tools helped him get them out faster than he could have alone. An audiobook is coming. Dave briefly considered recording it himself, heard the professionals on ACX, and wisely hired a narrator. Joe recorded the opening and closing of The Transformation Economy himself and let the professionals handle the rest. Aransas, for her part, heavily negotiated to narrate her own book, Courage Capital — forthcoming from Hachette in 2027. Key Quotes "We almost forgot that humans are intelligent too. We're actually the source of all the context that's being fed into the technology." — Dave Norton "AI companies think of context as the model's context. What we need to think about is the customer's context — the individual's context." — Joe Pine "Demographics tell you nothing about an individual person and how you might provide them with value. Prince Charles and Ozzy Osbourne — same day, same town." — Joe Pine "Calling a person a persona is an injustice. We are not personas. We are human beings with agency, and every human being is unique." — Joe Pine "The system has to be redesigned to support your needs and to empower you to do what you care about in the way that fits your life and values." — Aransas Savas "Books that are generated using AI should always have a section on provenance." — Dave Norton "The fact that you came up with these ideas years ago does not take away one iota from how valuable they are today." — Joe Pine Get the Book Human Context: How Intelligent Companies Build Customers by Dave Norton is available now on Amazon (Kindle and print). Early sales and reviews on Amazon make a real difference — if the book is useful to you, take 30 seconds to leave a review. The ten industry workbooks are available alongside the book at www.stonemantel.co Connect with Dave on Substack at theexperiencestrategist.substack.com . The Experience Strategy Podcast is hosted by Dave Norton and Aransas Savas — subscribe, reply to any episode email, and let them know what you're working on.

July 22, 202621 min

Healthcare Is Coming Back — And It's Getting More Human

The Experience Strategy Podcast | theexperiencestrategist.substack.com A nurse whose only job was to hold a patient's hand during a procedure. A debrief with the doctor scheduled before the procedure was even booked. A title accidentally revealed mid-conversation. This episode covers a lot of ground — starting with where healthcare experience strategy stands right now, and ending somewhere that a certain author probably wasn't expecting. What's in This Episode Healthcare is recovering — and the investment is back. After a brutal five-year stretch that left providers burned out and hospital systems in survival mode, Dave sees real momentum returning. Capital is flowing back into healthcare, and what's different this time is a more mature understanding of where technology fits and where it doesn't. AI handling clinical note-taking is the clearest near-term win — freeing physicians from the documentation burden that was eating their limited time with patients. Longer term, the new generation of LLMs built for scientific discovery is accelerating treatment development in ways that weren't possible even three years ago. The problem with scaling human experience. Mayo Clinic and Cleveland Clinic were early adopters of design thinking — writing case studies on patient experience in the 2000s that the whole industry studied. But the business model kept pulling in the other direction: enormous capital expenses, opaque insurance structures, and the relentless pressure to grow. And as Dave puts it, when you scale up a healthcare system, individualized experience gets harder, not easier. That's always true in any category — but the stakes are higher in healthcare. Then a pandemic arrived and survival became the only goal. The better the patient experience, the better the outcomes. Joe has been saying this for years, and the research backs it. The insight is simple but organizationally difficult: healthcare is not a service business. It uses experiences, but it's fundamentally in the transformation business. Every patient walking through the door has an aspiration — some version of going from sick to well. That aspiration, and the experience designed around it, drives outcomes. Geisinger Health System has operationalized this through outcome-based pricing: knee replacement doesn't work, you don't pay. More systems are moving in that direction. Human needs versus patient needs — there's a difference. Aransas's experience at Memorial Sloan Kettering is the episode's anchor story. A procedure booked with a debrief appointment scheduled at the same time — eliminating the anxiety window between test and result. And a nurse whose sole role during the procedure was comfort: one hand on Aransas's hand, one hand on her shoulder. Joe's reframe lands hard: "They didn't just meet your patient needs — they met your human needs." The distinction matters. Patients are still too often seen as collections of symptoms. The shift toward the whole person is coming, but it's uneven. AI's real job in healthcare: offload the routine so humans can be human. The most useful frame for AI in any service category — and healthcare in particular — isn't automation for its own sake. It's freeing the human in the room to be fully present. Checklists, documentation, protocol verification: these are exactly the kinds of cognitive load that drain providers and crowd out the relationship. Aransas makes the point that the "which leg are we operating on?" verification ritual exists because it was a real risk. The goal is to use operations and AI to cover the routine, so providers can put their energy into the part that only humans can do. Trained empathy has a shelf life. Dave traces the arc from "Welcome to Wachovia!" — a scripted greeting that felt like cutting-edge hospitality in its day — to the present moment, where scripted warmth reads as inauthentic almost immediately. Rote empathy, whether from a human or an AI trained to flatter, produces the same result: it rings hollow. Consumers have been through enough now that they can tell the difference. Joe's COVID-era conclusion still stands: "Be human." That's not a soft directive. In an environment where AI handles more and more of the transaction, genuine human presence becomes the differentiator. The tools that made experiences more human are showing their age. Persona building. Journey mapping. Design thinking. These were genuinely useful frameworks, and the industry built real capability around them. But Dave argues they're no longer sufficient. The question isn't how to design a better map — it's how to build what he's calling intelligent experiences : a new framework for the human interface that fits the current environment. He's writing about it now. Referenced Memorial Sloan Kettering — patient experience design as a model for the category Geisinger Health System — outcome-based pricing for knee replacement procedures Wachovia Bank — early scripted greeting protocols as a case study in what hospitality looked like before it became a liability Have a question for Joe, Dave, or Aransas? Reply to any episode email on Substack — it goes straight to them. The Experience Strategy Podcast is hosted by Dave Norton and Aransas Savas. Subscribe at theexperiencestrategist.substack.com .

July 15, 202620 min

Personalized Pricing Is Coming — Should You Be Worried?

The Experience Strategy Podcast | theexperiencestrategist.substack.com A Wall Street Journal article from June 3, 2026 asked a question that stopped the hosts cold: What is personalized pricing, and why are lawmakers scrambling to ban it? The premise — that companies might start using behavioral data to charge you a price uniquely calibrated to what you'll pay — prompted an immediate, live Google search and a conversation that spanned economics, loyalty, Kmart's demise, Coca-Cola's famous blunder, and a grocery delivery mishap that somehow became a love story. What's in This Episode Dynamic pricing versus personalized pricing — there's a real difference. Seasonal pricing, surge pricing, and inventory-based price swings are old news. What the WSJ article is pointing at is something newer: AI-powered systems that use your specific behavioral data — browsing history, routines, purchase patterns, location — to set a price just for you. The Uber example makes it concrete: if the system knows you take your kid to school every morning at 8am, it can raise the price for that ride because it knows you'll pay it. Does Amazon already do this? Amazon says no — prices shift every ten minutes based on competitor pricing, inventory, and overall popularity, not individual profiles. But dig deeper and you find location-based and behavior-based price discrimination already in practice. Joe's verdict: "Amazon is really good at hiding it." Aransas found documentation confirming that Prime membership status, browsing history, and purchase behavior all factor in — which, as she points out, is exactly what the article is describing. The economic logic is real, but so are the ethics. Joe makes the case for dynamic pricing on classical economics grounds: it clears markets, matches price to willingness-to-pay, and brings sellers to the table who wouldn't otherwise show up (hence the umbrella vendor in the rain). But Dave flags where it gets dangerous fast: zip code-based pricing is functionally equivalent to race-based pricing in many markets. Charging more to people in food deserts, or gouging communities after a tornado, is a different proposition entirely than charging more for a hotel room during peak season. The Coca-Cola cautionary tale. About 20 years ago, Coca-Cola announced dynamic pricing in their vending machines — prices would rise when it was hot out. They were immediately lambasted. Joe's observation: all they had to do was flip the frame. "When it's cold, we charge less" and "when it's hot, we charge more" describe the exact same pricing model — but one is a gift and the other is exploitation. How you present it is everything. They never launched it. Consumers will have counter-tools — and faster than you think. Dave predicts the AI arms race runs both ways. The same technology enabling personalized pricing will power consumer-side tools that comparison-shop in real time, flag price discrimination, and route purchases to cheaper alternatives automatically. He's watching Gemini (especially through Apple's Siri integration) as the likely first mover on this. Joe's point: "Information will out." If you're doing it in secret, your customers will eventually find out. Would you do it if you had to announce it at the same time? The subscription model is the cleaner answer. Both Dave and Aransas point to subscription as the more honest path — you get a flat, predictable price; the company gets reliable lifetime value; and the relationship isn't built on information asymmetry. Aransas's Stop and Shop story becomes the episode's centerpiece here: online grocery delivery, happily paying the subscription fee and weekly tips, lower total grocery spend despite the higher convenience cost, and 100% share of wallet. The relationship survived bruised bananas and a botched delivery in a heat wave — because a customer service rep named her new best friend recovered the moment with warmth and a complete solution. That's the model. The Kmart lesson. Dave connects the dots to history: Kmart's blue light specials trained customers to hold out for the deal. Consumers got tired of gaming the system, Walmart offered everyday low prices and won. Ticketmaster is living the next version of this story right now. Pricing models that turn every transaction into a battle erode trust and invite regulation. Transparency is the experience strategist's job. Aransas closes with the takeaway she most wants the audience to carry out: experience strategists are going to be in the room when these conversations happen. Be the person who says, let's not do this in secret. The companies that deploy personalized pricing with transparency — "here's why you're seeing this price" — are the ones that preserve the relationship. The ones that don't will get caught. Referenced "What is Personalized Pricing?" — Wall Street Journal , June 3, 2026, by Jackie Snow Coca-Cola dynamic vending machine pricing announcement (circa 2000) Kmart blue light specials as a cautionary pricing model Ticketmaster as a current case study in pricing backlash and regulatory scrutiny The Experience Strategy Podcast is hosted by Dave Norton and Aransas Savas. Subscribe at theexperiencestrategist.substack.com .

June 9, 202620 min

The $900 Billion Wellness Tourism Trade — and What Luxury Hotels Are Really Selling Now

Featured article: " Wellness Tourism Could Top 900 Billion in 2030. Luxury Hotels Are Racing to Keep Up. " — Forbes A Forbes feature highlighting 12 luxury hotels leading the wellness tourism shift — immersive White Lotus –style programming, longevity-driven design, destination spa experiences — opens the door to one of the most consequential conversations on the show this year. Wellness tourism is on track to hit nearly $900 billion by 2030. The architecture is gorgeous. The marketing is aspirational. But the strategic story underneath is bigger than any single hotel. Joe, Dave, and Aransas use the article as a launch point to talk about what luxury actually means now, why reflection is the highest-leverage cost-free upgrade an experience stager can make, why integration therapists are showing up at high-end destinations, and what the White Lotus effect tells us about the power of the guide. Key Ideas Place is the offer. The most successful destinations are not selling generic luxury — they are repositioning their authentic environments as wellness solutions. Sedona sells healing rituals. Greece sells the water. Aransas's framing: these hotels immerse you in a film, a script, an aspirational lifestyle you have already seen on Netflix. The destination becomes the set, and you get to step into the story. The MGM prediction came true. Joe takes the show back to 2000–2002, when he told MGM in Las Vegas that there would come a day when they made more revenue, and eventually more profit, off non-gaming experiences than off gaming. They thought he was crazy. The line crossed before 2010. Today the money-value-of-time per minute in the spa beats gaming. The Aria does not care if you skip the casino for the spa floor. Luxury is no longer about exclusivity. It is about transformation. Dave's reframe: luxury used to be the biggest diamond and the nicest car. Now it is who can go to Greece and walk away with better sleep, better biometrics, hormones optimized, and a body ready for the next experience. The shift is from possession to durable change. That is why the willingness to pay is climbing — the value compounds instead of fading on the flight home. The transformation stack. GLP-1s, biometrics, prevention, hormone optimization, longevity supplements, fitness tracking, anti-aging skincare — all converging inside hotels and spas. The result is not a vacation. It is a chrysalis. Joe's frame from the Rotterdam Third Place Summit: think of your place as a chrysalis between what your guest was before and what they are becoming, and help them through the change. Reflection is the highest-leverage upgrade in the experience economy. Dave names it clearly: the single biggest thing you can do to increase the value of an experience costs nothing. Get people to reflect. Joe builds on it from the work he and Aransas did at the Arival travel event in DC — reflection automatically and retroactively increases the value of the experience. It cements the memory, surfaces the impact, fuels the aspiration to come back, and turns guests into evangelists. It is the most consistently skipped step in experience staging today. The four-step transformation arc. From Joe's chapter on encapsulation in The Experience Economy : preparation (some academics call it preflexion), the experience itself, reflection, and integration. The fourth step is where most experience providers fall off — what happens after the guest leaves your property to keep the change taking root. Integration therapists are entering hospitality. Joe references a Wall Street Journal piece on luxury hotels hiring integration therapists — a model previously associated with ketamine therapy and plant medicine — to help guests integrate transformations they undertook elsewhere. Othership in Toronto and Brooklyn does the same thing for ayahuasca journeys done in the desert. The pattern is spreading. The White Lotus effect is really about the guide. Aransas's read on the most recent season: it makes the case, in narrative form, for how intimate and consequential the guide relationship can be inside a transformation setting. Some guides are destructive, some are generative. Either way, the show is teaching mainstream audiences to imagine what it would mean to travel with someone helping you become the next version of yourself. That imagination is what hotels are now being asked to deliver. A Useful Distinction Aransas's nuance on what counts as transformation: in your research, guests draw a hard line. A massage and a facial feel good. They are not transformation. Longevity — sustained, measurable, durable change — is transformation. The risk for the industry is selling the impression of transformation without delivering the underlying change. Beautiful sets, aspirational scripts, and no actual chrysalis. Memorable Moments Joe on the Aria: "It's a hundred degrees outside. We will keep you so pampered you won't want to leave." Dave: "Luxury used to be about who has the biggest diamond. Now it is about who can go to Greece and walk away with their sleep better, their biometrics better." Aransas: "You can't logic emotion, Joe." The Strategic Takeaway If you are in hospitality, third places, or any business adjacent to the transformation economy, the upgrade path is clear: Stop selling memorable experiences. Sell transporting ones — and inside the transport, design transformation. Pick the chrysalis you actually are. Place, ritual, regimen, guide — what specifically helps the guest move from before to after? Stage all four steps. Preparation, experience, reflection, integration. Reflection is free and almost no one does it. Start there. Treat the guide as a role, not a job title. The White Lotus audience is being trained to look for one. Subscribe and Continue the Conversation Find the show on theexperiencestrategist.substack.com , the podcast feed, and everywhere else. Got a topic you want us to dig into? Reach out on Substack. We are building the next round of episodes around what listeners are actually reading. And if you have a kid going to college this fall, Aransas would like to start a support group.

June 3, 202624 min

The Death of Personas — and What Actually Replaces Them

The Experience Strategy Podcast Hosts: Aransas Savas, Dave Norton, Joe Pine Featured articles: " Death of the Segment: Why Personas Are Killing Personalization " — SwiftERM " Your Personas Are Outdated. It's Time to Evolve Your Approach ." — Audrey Chee-Read, Principal Analyst, Forrester Every other post on LinkedIn is announcing the death of something. Most of it is alarmist storytelling dressed up as insight. But under the noise, two recent articles — one from SwiftERM, one from Forrester — are pointing at a real problem: personas and segmentation, built for an earlier era of marketing, have become a drag on personalization in the era of AI. Dave, Joe, and Aransas trace where personas actually came from, why they got merged with segmentation, what AI changes about the math, and what should replace the persona as the stable determinant companies are still looking for. The answer Dave keeps returning to: situations. Key Ideas Personas were never built for marketers. Dave opens with the history. The persona originated around 1999–2001 as a design thinking technique to get engineers to think more like customers. It worked. Then it migrated into marketing and merged with segmentation, and the original purpose got lost. Segmentation is the search for a stable determinant. Companies need something they can count on to define a market — geography, demographics, lifestyle, generation. Stable determinants make markets identifiable, and identifiable markets are countable. But the stability is increasingly fictional. Customers are not stable. They want different things at different times. Joe's arc: mass market → segments → niches → markets of one → markets within one. Joe walks the progression from Henry Ford's mass market through Alfred Sloan's segments through the minivan that opened up niche thinking. Stan Davis's Future Perfect (1987) saw the path to markets of one. What comes next is the flip: multiple markets inside every customer. Joe on a business trip is a different market than Joe on a leisure trip with his wife, even though it is the same person and the same credit card. This is the situational markets argument. Dave's frame: situations can be the new stable determinant. Friday night with your wife is a context. Monday morning before work is a context. Travel in cold Chicago is a different context than travel in France. The behavior changes with the context, even when the person does not. The SwiftERM line that lands the case. "While your team is busy building a persona for Sarah, the 35-year-old yoga enthusiast, Sarah has already moved on. She isn't a persona. She's a dynamic stream of intent." She bought a yoga mat six months ago. For the last three days, her behavior shows interest in high-end supplements and weightlifting gear. The persona missed the shift. The window of intent closed before the system caught up. Bayesian thinking is the right math for this. Predictive analytics has historically used past behavior to predict future behavior — yesterday you watched a romance, so tomorrow you will too. The newer move is using context, not just history. Yesterday you watched a romance because it was Friday and you were with your wife. The probability updates with every new piece of information. AI makes this practical at scale for the first time. The Apple Watch and Netflix examples make it concrete. The latest Apple Watch update no longer just serves up the workout you did last. It serves up the workout you usually do on that day of the week. Aransas lifts Monday and Wednesday and the watch knows. Netflix recommends romance on Friday night because the pattern holds across the whole user base. Restaurants have understood this for a hundred years — they do not serve breakfast at nine at night because they read the context. Customers have the same AI you do. Joe's reminder at the end is the one that should make every CMO uneasy. Customers can now vibecode their own shopping experience. They can customize as easily as you can customize for them, and they will configure it for their own context every time. The companies that win are the ones whose offerings can flex to the customer's situation, not the ones with the most polished persona deck. A Word on "Moments" Dave makes a careful distinction at the end. Moments is the right idea, but 20 years of design thinking have loaded the term with retail-moment-one, retail-moment-two, retail-moment-three thinking — discrete and product-out, not organic and customer-out. Situations carry the meaning without the baggage. Memorable Moments Joe: "I might be multiple personas, but you never say there's a person, they're that persona. That's just wrong — morally, much less business-wise." Joe: "Dave has yet to find a situation in which talking about situations does not work." Dave's bathroom study: weather changed bathroom usage at French gas stations. It did not move the needle at Chicago train stations. Different situational markets. Aransas on the Paris Marathon: one toilet, a hundred urinals, 20,000 runners — half of whom needed to sit. A persona designed for one imagined customer, and the actual situation ignored. Joe on the American Girl Place men's bathroom stocking products that men do not use — because the company actually thought about who was walking in with their daughter. The Strategic Takeaway Companies need something they can count on. Personas have stopped being that thing. Aggregated situations — Friday night, business travel with kids, post-workout, end-of-quarter — are stable enough to plan against and dynamic enough to respect what the customer actually wants in the moment. AI no longer makes one-to-one a scary thing to attempt. The excuse is gone. The companies that move now will be the ones the customer feels actually understands them. Subscribe and Continue the Conversation Find the show on the Experience Strategist Substack , the podcast feed, and everywhere else. Article links in the show notes.

May 20, 202619 min

Microshifting, Modes, and the Life Systems Companies Still Refuse to See

Featured article: " I'm Not Doing Laundry on the Clock. I'm Microshifting ." by Eve Upton-Clark, Fast Company , October 7, 2025 Owl Labs reports that 65% of workers are interested in microshifting — what the company calls structured flexibility built from short, nonlinear work blocks matched to energy, duties, and productivity. Joe, Dave, and Aransas take the article apart and put it back together in a more useful frame. The term itself gets challenged early. Joe argues most of what the article describes is closer to macroshifting (hour-long, hour-and-a-half-long focused blocks), not micro. Dave reframes the word entirely: a shift is not a period of work, it is a change of mode. And once you read it that way, the whole article becomes a confirmation of two frameworks the show has been working with for years — modes and life systems. The conversation widens into how midlife women, AI-augmented workers, and traditional workplaces all bump up against the same problem: human productivity has never been a flat eight-hour line, and the companies still pretending it is are losing the people who know better. Key Ideas Microshifting is really mode-shifting. A mode is a temporary mindset and set of behaviors. Beast mode is a mode. Podcast mode is a mode. Writing mode is a mode. What the Fast Company article describes — moving between focused blocks of work and the recovery, errands, or walks in between — is what mode-shifting looks like when a worker actually has the autonomy to do it. Routines are permanent. Life systems are responsive. Dave makes the distinction clearly. Joe's morning is not a routine. It is a life system: PT, breakfast, email, a walk through the cul-de-sac with the newspaper and a cigar, then writing or meetings, then a midday return to email, then a shift to whatever is next. The tools, timing, cadence, and energy levels all interact. Life systems are the hidden architecture under what people now call flexibility. Midlife women have been doing this all along. Aransas's book research keeps surfacing the same finding: midlife women with shifting hormones, attention spans, and energy levels need flexible work to keep performing at their best. The advocacy community has been making this argument for years without the label. Owl Labs surveyed a different population and gave the same behavior a name. The label travels; the underlying truth was already there. Autonomy is the through-line from YouTube to work. People prefer YouTube because they get to follow their interest in the moment instead of waiting for Channel 7 to air a plumbing show. The same instinct shows up in how people want to work: responsive to the mode they are in, not locked into a schedule designed for someone else's mode. AI is changing the limits. AI does not get tired. People do. Recent reporting suggests AI-heavy workers are working longer hours, but framing it positively — they are finally getting to things that used to hang over their heads. The question for companies is whether that ends in more output or more exhaustion. Likely both. A new question about vulnerability. Aransas raises something she has not heard discussed elsewhere: people are admitting things to AI they would not admit to other humans. Does that practice transfer back into human relationships and make people better at acknowledging what they do not know? Or does it stay locked inside the chat window? Probably depends on the person. A change is coming either way. And a reminder about privacy. The OpenAI–Musk depositions are a useful warning. ChatGPT history is not a diary. It is discoverable. The Strategic Takeaway Dave's closing argument: the idea that productivity equals maximum focused time on a single task has never described the human condition unless someone forced it to. What workers and customers actually want is the ability to shift modes — focus mode, recovery mode, creative mode — and to have their life systems supported through the shifts. The companies that recognize this and design for it are personalizing in a way the rest of the market is still missing. Aransas lands the frame cleanly: ask your machines to run like machines, and your humans to run like humans. Joe's add: there is a real opportunity here for companies to help people spend their time well. Watch the modes your customers move through. Help them get the most out of each one. Memorable Moments Joe describing his morning walk: cul-de-sac, newspaper, cigar, possibly a future bathrobe and pipe Dave: "It's like you're from a novel. A British novel." Joe pushing back on the word "micro" — most of what the article describes runs 30 to 90 minutes per block The pachinko parlor footnote: Japanese office workers logging the hours without working the hours Aransas: "Ask your machines to run like machines, and your humans to run like humans." Mentioned in This Episode Fast Company , " I'm Not Doing Laundry on the Clock. I'm Microshifting " by Eve Upton-Clark Owl Labs flexibility research The previous episode on YouTube and shifting media attention Dave's upcoming workshops

May 15, 202624 min

'Subway Takes' and the Future of YouTube TV

Kareem Rahma built Subway Takes into a hit with 2 million Instagram followers, a metro card as a microphone, and a format that runs in seconds. Now he's walking away from a CNN deal to put his next show Keep the Meter Running on YouTube — because YouTube, in his words, is where the next Bourdain and the next Lena Dunham will come from. In this episode, Joe, Dave, and Aransas dig into what Rahma's bet actually means for experience strategy. The conversation moves from short-form content design, to the death of "Gen Z YouTube" as a useful category, to why every brand needs to rethink where and how it reaches customers in the micro-moments that now define modern media consumption. 100% agree or 100% disagree — you decide. What We're Talking About This Episode Rahma's CNN walk-away. Why he turned down a legacy media deal to own his independence on YouTube, and what that signals about creator economics now. YouTube as television, not social media. YouTube's monthly share of TV watch-time hit ~12% in 2025 per Nielsen — higher than any network or streamer. Rahma's read: "this is a TV screen, but right now no one's making television for it." Subway Takes as situational design. The subway isn't a backdrop. It's the situation. The format, the duration, the point of view, the 100% agree / 100% disagree script — all of it is built around a specific consumer moment. The Lorne Michaels frame. Rahma isn't playing the virality slot machine. He's building a show. A nice change from all of the influencer content out there. Why "Gen Z YouTube" is a lazy frame. Dave pushes back on the article's generational framing. His adult kids watch YouTube over Netflix. So does Aransas. So do millions of others. The situation around the screen has changed. Why This Matters for Experience Strategy Three themes worth pulling out: 1. Content is situational, not channel-based. Dave traces this back to a 2015 Collaboratives conversation with a major media company about designing content for the 30-second, 90-second, two-minute windows that now define daily consumption. A decade later, that conversation is finally mainstream. The companies still organizing around channel rather than situation are the ones being lapped. 2. POV is the differentiator. Rahma's 100% agree / 100% disagree technique forces you to take strong point of view in every interaction. Brands that hedge — that try to be all things to all customers — are getting outpaced by creators who plant a flag. 3. The CNN ticker is the OG infinite scroll. Joe drops a sharp observation mid-episode: 24-hour news already pioneered the segment-plus-chyron structure we now call short-form. The need hasn't changed. The means of meeting it has. Which connects to a Clayton Christensen line Dave only partly agrees with — and to Stone Mantel's view that situations themselves do change, not just the jobs underneath them. Memorable Moments Joe's Transformation Economy book made Thinkers50's top 10 management books of 2026. Aransas on the invisible load of AI: ideas start faster, but humans still have to finish them — and the cognitive load is going up, not down. Dave on what Cargo has done to his wardrobe: black t-shirt to medium gray. Things have changed. The unhoused-person-falling-in-your-lap test for quintessential New York. Joe's Easter Bunny / Cargo joke. You'll know it when you hear it. Quick References The Talk Show Where Celebrities and Mamdani Share Their Hot Takes — Sam Schube, WSJ Magazine, May 12, 2026 Subway Takes — Kareem Rahma's hit short-form show The Transformation Economy by B. Joseph Pine II — recognized by Thinkers50, 2026 Join the Collaboratives Dave's working the phones — it's that time of year. The Collaboratives is the Stone Mantel + Cargo partnership exploring situational markets as a growth mechanism in a world where parity is everywhere and growth is harder than ever. Free market analyses are my gift to anyone who joins. Workshop coming May 21. Send me a note if you'd like to be invited to the May 21st Workshop.

April 22, 202618 min

Why Spas and Gyms Are Beating Stores — and What It Signals About the Transformation Economy

For the first time on record, experience-based tenants — spas, gyms, wellness studios, entertainment venues — are outpacing traditional goods retailers in leasing shopping center space, with wellness and fitness leading the charge. Joe Pine, Dave Norton, and Aransas Savas unpack what this shift actually means: it is not just a retail story, it is confirmation that the transformation economy Joe predicted more than two decades ago has arrived. The conversation traces the arc from malls to experiential anchors, examines why some brands (Red Bull) rode the wave and others (Nike) missed it, and lands on a provocation for any company still selling goods: if you want to sell products today, sell experiences. If you want to sell even more products, sell transformation. Key Takeaways The bifurcation is accelerating. Post-COVID data from high-end luxury shows goods flattening or declining in price while experiences shot upward. The Economist's October feature on high-net-worth luxury quietly re-labeled "services" as "experiences" in its TikTok follow-up — a small edit that tells the whole story. Experiential venues are the new anchors. The old mall anchor was a department store. The new anchor is an escape room cluster, a bowling alley that is really an entertainment complex, an NHL team's practice facility inside a converted suburban mall. Square footage is shifting toward places people want to spend time, not places they pass through. Goods still sell — but best through the experience. Joe's story about the original Nike Town in Chicago captures the mistake most brands still make: Nike Town had a line out the door and did not charge admission. Over time, goods crept back into the floor space that used to belong to basketball courts and events. Red Bull took the opposite path and became an experience company that sells an energy drink. The trajectories diverged for a reason. Experiences commoditize fast. SoulCycle opened a category; spin studios saturated it within a decade. The same glut is forming in spas and boutique gyms right now. The next move is specialization and bespoke combinations — and beyond that, transformation. Transformation is the durable business model. Experiences are episodic. Transformations are long-term engagements, which makes them long-term revenue. Aransas frames the shift cleanly: not just time well spent, but time well invested. Companies that move from experience provider to journey partner earn a different kind of relationship — and a different kind of margin. Social media is an experience platform. Influencers are in the experience business. Some investors will not touch a product today until the influencer strategy is nailed down. Advertising and packaging are shrinking as a share of how people discover and buy. Memorable Moments Joe's recap of his Monaco keynote at the Forbes Travel Guide Summit, where luxury goods manufacturers showed up because they are all getting into luxury experiences now The Nike Town queue that was not charging admission — and what it foreshadowed about Nike's retreat from flagship experiences Dave on the Utah Mammoth buying a suburban mall and turning most of the square footage into a place fans come to watch practice Aransas on walking out of a spa day carrying products because she had just seen, on her own face, what they actually do The throwaway that lands: "Gosh, we're smart." The Strategic Question for Every Brand If you sell goods, where is your experiential venue — physical or virtual — and what transformation are you actually offering the customer who shows up? The brands that answer this well over the next five years will be the ones occupying the square footage the department stores used to hold. Also In This Episode Aransas's Substack is now the 30th fastest-rising publication in Health and Wellness on the platform. Subscribe, Share, Comment If this conversation sparked something, share it with a colleague and leave a comment. We read them. And subscribe to the Substack for the written companion to the show. Joe is heading out on book tour for The Transformation Economy . We will be back soon.

April 2, 202622 min

AI Twins and the Future of Research

AI Twins and the Future of Research The Experience Strategy Podcast Episode Overview Two Wall Street Journal articles are making waves in the market research world — one asking whether AI can replace human research participants, and another profiling a teenage-founded startup called Aura that's already attracted McDonald's and EY. Dave, Joe, and Aransas bring their combined decades of consumer research experience to the question everyone in insights is quietly asking: is this the end of primary research, or the beginning of something more powerful? What We Cover The two WSJ articles at the center of this conversation The first covers Simile, a startup building agentic AI twins modeled on real people for polling and market research. The second profiles Aura, a company founded by people younger than Aransas's high schooler, betting that AI bots can predict human behavior better than humans themselves. Dave's evolving reaction — Worry, skepticism, and then possibility His first instinct was worry. Stone Mantel has built its practice on deep consumer research, and the promise of AI twins that can answer with 0.5% accuracy at first felt wrong. But the more he sat with it, the more he saw a useful analogy: flight simulators. Simulators serve a real purpose as long as everyone is clear they are not the same as flying the actual plane. The critical flaw in current AI twin models Both Dave and Joe land on the same problem independently: AI twins are built on static preferences and demographic profiles. They treat people as if behavior is fixed — "this is how soccer moms respond" — when the entire premise of situational research is that behavior shifts with context. What mode is the person in? What situation are they navigating? Those questions are not being asked. Joe puts it plainly: they didn't ask anything about modes. Where AI twins might actually work well Trend prediction and aggregate market analysis are reasonable use cases. If you want to know whether fruit-flavored tea is about to have a moment, AI models scanning historical purchasing data and cultural signals can probably get you there. The harder problem — and the more valuable one — is understanding what a specific person cares about in a specific moment, and that requires something current AI twins are not equipped to provide. What AI twins could become with better design Dave raises an intriguing possibility: after completing primary research with a real consumer, could that data become the seed for ongoing simulation and modeling? Not as a replacement for the research, but as a way to extend its value across time and decisions. He also flags the bias risk — every feedback loop that improves AI accuracy may also drift it further from the original human signal. Joe's Wall-E scenario The Terminator isn't Joe's fear. Wall-E is. Personal language models hanging out in your Alexa, learning everything you say and do, eventually making purchasing decisions on your behalf — and research shifting to focus on the PLM rather than the person. The result: consumers with no agency, led entirely by AI intermediaries and the consumer goods companies they serve. The consent problem CBS claimed 400,000 people opted in to being replicated as AI twins. Aransas is skeptical — and direct. That was some very fine print. Companies building AI twin programs need to be serious about how they are collecting this data, not just technically compliant. Key Idea If AI can actually predict behavior change, it is no longer a tool — it is strategy. That quote, attributed to a Coca-Cola executive in the second article, captures what is at stake. Dave frames it through the lens of superpowers: AI gives companies the ability to do things they could not do otherwise. The question is whether the thing they are doing actually reflects how real humans behave. Continue the Conversation Join Dave, Joe, and Aransas on The Experience Strategist Substack to go deeper on this episode's themes.