Don’t Replace the Customer With a Shiny Object: A Retail Futurist on Winning Tomorrow’s Shopper

Relational or Transactional: What Actually Changed

Three decades in, the answer starts with technology’s promotion.

Technology has moved from enabler to driver of both the transaction and the interaction, and where retailers apply it has shifted significantly.

Then the constant underneath it, which he has held to across his whole career.

Dave: “The relationship that a consumer has with a brand or with a retailer has to be relational. When it starts tilting toward a transactional only interaction, yes, it’s easy to automate a transaction, but it is very difficult to maintain loyalty or remain differentiated. Consumers are still people and they are relationship driven. So let’s figure out a way to use technology to strengthen a relationship, not replace the human interaction.”

Asked whether relationships will still matter by 2030, the alternative gets described in enough detail to make it uncomfortable. Once shopping turns transactional only, competition narrows to availability, price and shipping speed, with AI-curated assortments compressing the field further.

Dave: “As soon as you take that out of the equation and it becomes nothing more than I need a product, here’s a product, I’ll shop wherever it’s available fastest, then you don’t need people in that transaction. And loyalty is in the rear view mirror, very distant.”

A retailer competing purely on price, availability and speed has eliminated its own reason to employ people who build relationships. Most arrive at that choice by drift.

The Yes-And: Convenience, Loyalty and What Comes Next

Dave did improv comedy years ago, and it left him a frame he still uses. In improv, “yes, and” means every contribution builds on what came before.

Dave: “It is convenience, it is loyalty, and something else. So what is the and?”

Convenience of purchase, of return, of delivery, of customer service: none of it goes away.

The answer is a concept his firm has developed over years: the curated solution.

Dave: “A single product probably doesn’t solve the consumer’s needs. If you were going to fix your kitchen sink and all you needed was a faucet, you could buy that any place. But if your faucet also required a washer or a hose or some filtering system, you wouldn’t get a complete solution.”

The next frontier is true problem solving: here are the other three things that complete this for you with ease. That is where AI earns its place, curating the basket around an individual need.

Category management stays table stakes online and in store: right product, right place, right time. The addition is that the category itself becomes personal.

Dave: “Your category for home improvement probably doesn’t look a thing like mine because you know how to use a wrench. I don’t even know the end of a wrench to use. So my solution might include a video that says here’s how to do it, or a special hotline with a customer service rep that can walk me through it.”

Two things separate this from cross-selling. The bundle assembles around the job the shopper came to do, so composition follows skill level and circumstance ahead of attachment margin. And the components include service and content, so a how-to video counts as part of the basket. Assortment planning becomes a problem-definition question.

Why Consumers Stopped Caring About Channels

The omnichannel conversation is thirty years old and unfinished at most retailers.

Speaking as a consumer himself, the channel is irrelevant: online storefront, physical store, social media, a click on the television, or some means yet to exist. What matters is the right product at the right time.

The organizational reality lags far behind.

Dave: “I can point to retailers today who have an e-commerce department and a brick and mortar department, and they barely know each other. That needs to come together into one.”

Consistency has to extend past the two obvious channels. A customer service bot should look and feel like the online store and the physical store, and social commerce belongs inside the same system.

Dave: “The consumer doesn’t care which channel, just as they don’t care whether they’re shopping the cough and cold category or the skincare category. All I want to know is that the product meets my need and I can get it.”

Channels and categories are internal conventions that make sense on an org chart and register as noise for a shopper. Departments that barely know each other deliver inconsistent experiences the customer reads as one brand behaving unpredictably.

Curation Inside a Physical Store: The Concierge Idea

A physical store carries a constraint that online escapes: finite space and inventory that resists duplication. The problem gets worked through his own category.

Build a sports injury recovery section and it needs pain relief. Build a living with arthritis section and it needs pain relief too. Duplicate the inventory across both or the curation breaks.

The simple answer borrows from hospitality.

Dave: “Picture yourself going into a brand new hotel in a city you’ve never visited. You go over to the concierge desk and say, can you help me find a restaurant for dinner? How many retailers today have a concierge desk? I can’t think of any.”

Picture the retail version. Somebody asks what you are trying to solve today. A sports injury. From there: pain relief, braces and support, other recovery aids, with the assortment pulled up online while the shopper stands in the store.

The ambitious version needs engineering: shelving that reconfigures around a stated need.

Thirty years out he pictures something closer to an Apple store that happens to be your grocery store: little physical inventory on the shelves, a display product or two, everything else curated live and on the spot.

The concierge is the more actionable of the two, on price alone. Reconfigurable shelving is a capital project with uncertain payback. A trained person with a tablet needs a job description and a headcount decision. It also captures the stated need as data: every conversation records what a real shopper was trying to accomplish, which is the input an assortment plan usually lacks.

AI Product Discovery and the Risk to Tail Brands

Shoppers now arrive having researched through ChatGPT or Gemini, and no two arrive with the same answer.

Dave: “Even if a retailer studied ChatGPT or Gemini and said, okay, what solution will it come up with, let me make sure I have these products on hand, the next consumer is going to put in a different prompt and use a different engine and get a different assortment.”

Optimizing for one assistant fails because the target moves with every shopper and prompt. Precision about the customer replaces it.

Dave: “It has to be down to the individual now. You cannot stereotype and say, I’m going to cater to everybody. Or only to the 30 to 50 year olds. That’s impossible because we’re all individuals.”

Then the most serious risk, which hits brands before retailers. Wonderful products sitting in the tail, low on turnover, stand to miss the notoriety the AI engines confer, and with it a place in the curated solution.

The retailer response requires staff who can carry two ideas at once.

A shopper walks in having decided that a specific product is perfect because AI said so. Staff need to be equipped to answer that it is indeed a great product, and here is the equivalent on the shelf.

Three parties absorb this differently. Tail brands risk vanishing from consideration, since an assistant recommending three options rarely reaches past the top sellers. Retailers face an assortment they can no longer predict. Shoppers narrow to a handful of products chosen for them upstream. Substitution becomes a frontline skill.

Three Things Retailers Are Getting Wrong

1) Fragmented presence. The channels that barely know each other, covered above. Retailers approaching this piecemeal are falling far enough behind that catching up gets hard.

2) Replacing customer-facing work with technology. The example comes from that morning, a case study in what a chatbot costs when it fails.

Dave: “I’m planning a rail trip in Italy. I don’t speak Italian. I don’t know the rail stations. And I needed to change something, so I used the online chat. After 35 minutes of trying to clarify my request and asking repeatedly for a live agent, I ended up with I hope this solved your problem. Please give us a high rating. Unsatisfied.”

Overlook the emotional side of a person, replace it with technology, and the whole interaction turns sterile.

3) Barriers to the transaction. This is where he is most direct, and the argument runs against a widely accepted retail practice.

Dave: “If you’re lucky enough to get consumers into your brick and mortar, and you’ve cut through the jungle and the noise, and they’re standing there and they find the right product. If it is behind glass, if there’s an obstruction to that transaction, you frustrated me. How many at-bats do we need before you strike out, Mr. Retailer?”

Sathish raises the razor behind glass with no employee nearby, an outcome Dave has watched repeatedly.

Dave: “They’re on their phone searching for an online retailer that can deliver it to their doorstep, because waiting for a customer service rep to come and unlock that case, and then walking with them with a tag hanging on it that says don’t steal this, is not as nice as having a box show up at your doorstep.”

The verdict is blunt: the relationship-killing side of anti-theft is ruining the one-to-one trust retailers have with their customers.

Theft is a real problem, acknowledged, and the position survives it. Most loss-prevention analyses skip one calculation: shrink is measurable and the abandoned purchase is invisible, which biases the decision toward locking things up. Every locked case also signals to the customer how the retailer sees them.

Where AI Genuinely Creates Value

The framing is collaboration.

The power comes from a collaboration between human knowledge and AI’s breadth of historical data and ability to connect disparate dots. Both halves are required.

The worked example is a store opening in an unfamiliar market.

Dave: “I’ve just opened in Panama City, Florida. I want to make sure my store is accustomed to the weather trends in that area, the buying habits of the people in that area, so that I don’t take something from Detroit, Michigan and try to plug it into Panama City.”

Weather patterns, community makeup, local buying habits and store navigation all feed the assortment decision. Done by humans, that means field research, competitive analysis and a plan months later.

Then the line worth taping to a wall.

Dave: “Over-reliance on AI to just say speed up an existing process is underutilizing the potential of AI. I’d spend a lot more time thinking about what is it that I want to solve for, and working collaboratively with AI to solve for some problem that I think doesn’t even exist yet. Don’t speed up old technology with new technology, because you’re just perpetuating your mistakes.”

That line separates two entirely different AI programs that get budgeted identically. Automating a flawed process delivers the same flawed output faster, and the efficiency metric reports success. Solving a problem before it surfaces creates something new. Most retail AI initiatives sit in the first category and get judged as though they sat in the second.

The Supply Chain Problems Nobody Has Solved

Three weaknesses, and the first rarely gets planned for.

Dave: “I used to sometimes frustrate manufacturers who were launching a product because I would often ask them, what does it look like at the end of life of that product? When it’s no longer relevant. What is your exit strategy?”

The industry pumps new product into the pipe well and manages the other end badly. Products whose relevance expired remain in the mix, which is how the market ends up over-producted.

The second is behavioral: supply chains overreact to disruption, and the pattern repeats.

Dave: “We recently had an announcement of tariffs and the same reaction was beginning to take place. Supply chain is going to be disrupted. We’re not going to be able to get toilet paper anymore. The sky is falling. Have a safety valve. Have Plan B. Absolutely. But don’t overreact.”

The third is communication, compared here to a marriage.

Dave: “In any relationship, finance and communications are usually the top two culprits. In supply chain, you’ve got both. Manufacturers promise something, retailers demand something, and sometimes they’re two ships passing in the night.”

He has always approached supply chain partners as partners.

On whether AI helps, the clearest application is disruption modeling, given the volume of historical data and predictive analytics now available. The second application goes back to assortment, correcting an old habit.

Retailers once drew a line and delisted anything falling below it. The risk falls on individuals who needed the product near the bottom of that list.

A velocity cutoff treats every slow-moving SKU identically. AI can weigh additional factors, including whether a low-turn product completes a solution for a specific segment. That connects back to the tail brand risk: the analytical shift that saves a slow product from delisting also keeps it inside a curated basket.

Why Some Retailers Adopt and Others Pilot Forever

Sathish raises the pattern of companies running pilot after pilot for years while nothing reaches production, against an Amazon that operationalizes quickly. Two answers.

Chasing a shiny object like AI and handing it all the decision making undervalues the knowledge, insight, human experience and emotion AI will never carry.

The second answer gives this piece its title.

Dave: “If we don’t have a deep understanding of who the customer is that we’re solving for, we’re missing the boat. The customer we’re serving has to be at the center. If we solve for what he or she needs, it may be technology driven, assortment driven, supply chain driven, customer service driven. Don’t replace customer with shiny object. Don’t replace customer with the excitement about technology, because you’re then just going to be self-serving.”

Perpetual piloting has a diagnosable cause. A pilot launched because a technology looked interesting has no completion criterion, so it runs indefinitely while dodging formal failure. A pilot launched to solve a defined customer problem either succeeds or fails, and both outcomes end it.

AI and the Retail Workforce

The fear that AI replaces retail workers gets a counter-model.

Dave: “A better approach is to understand the skill sets that our workforce already has, look for what it is we want them to achieve, and use AI to fill the gap.”

Retail and brand marketing remain relational work, which keeps the humans necessary. Their skills were built on a legacy operational system, so the question becomes what the future operating model requires and how far the two sit apart.

The communication matters as much as the training.

Tell a workforce that AI will build their base of knowledge so they can better serve the customer, and name the gap it fills. Employees come away empowered, with redundancy off the table.

Asked which role transforms first, the answer is in-stock condition: robots running a nightly out-of-stock scan, feeding results to someone trained in merchandising who evaluates the recommendations. A product unavailable for purchase sends the customer elsewhere by definition.

On merchandising more broadly, the perspective comes from retiring out of a company built on planograms.

A planogram is a picture of where products ought to go, and building one was laborious. Human intelligence went into product management, assortment selection and placement strategy alike.

The Panama City research that took months should take AI fifteen minutes. A human appears in each case: the merchandiser evaluating the scan, the person judging whether a placement strategy makes sense locally. AI returns informed recommendations based on factors somebody asked it to weigh, and a person still decides.

For rolling any of it out, three questions apply to every employee.

Dave: “The why. Why are we doing things? The how, how is it affecting my job? And the what. What do I have to do as a result? My father used to say that before you implement any decision, you need to walk in the shoes of the individuals affected. That’s empathy in a nutshell.”

The retention math closes it: replacing and retraining somebody runs considerably higher than equipping and keeping them.

What Leaders Should Prioritize

Two priorities, kept deliberately few.

1) Expectations. Define what consumers expect from the experience you offer, then prioritize meeting it.

Stop understanding what customers expect and somebody else fills the gap.

2) Transparency. The example comes from a shopping trip around the country’s 250th anniversary, when he and his wife wanted Fourth of July shirts made in America and treated sourcing as the deciding factor.

Some consumers need that transparency while navigating their choices, and the principle runs wider than sourcing.

Dave: “Transparency on product sourcing, on policies, on procedures. No surprises when it comes to an online transaction. Get it all the way to the basket before I find out what a return policy is.”

Late-surfacing policy is what most e-commerce teams underestimate. A return policy discovered at checkout reads as concealment, and the damage extends to every future order.

Four Investments Worth Making

The third deserves expanding, because companies skip it.

Dave: “Invest in surrounding yourself with people who aren’t so close to the problem that they can’t see the answer. Without an objective voice in the conversation, too often you end up in an echo chamber. It might be that the boardroom came up with the perfect answer. That’s great and rare.”

The fourth concerns outdated assumptions.

Dave: “Retailers who still think consumers walk every single aisle of a store to fill their basket need to lift their heads up and see the reality. Consumers are going into a store saying, I’ve done my discovery already. I know exactly what I need. Help me find it.”

Most store layouts were built for the old behavior. A floor plan routing shoppers past impulse categories was built for a browsing customer. Someone arriving with the decision already made experiences the same layout as an obstacle course, alongside the locked display case.

How Small Retailers Beat the Giants

The old expression was that you could never out-Walmart Walmart. The same applies a rung higher.

Dave: “I don’t think you can out-Amazon Amazon. If you want to outpace Amazon on assortment, by the time you do it, Amazon will be onto other things. Their flywheel is moving way too fast. So what is it that some of the big retailers are not doing effectively that you can do the best? If you can be the best at X, and it’s underserved or a blind spot for one of the bigger retailers, you can win.”

The example lands somewhere unexpected. Dave admires the over-the-road drivers who move product across the country, and he has gone looking for something on their behalf.

Dave: “If you’ve ever walked into a travel center, whether it’s Buc-ee’s or any other, and tried to find a pain relief product differentiated just for truckers, it doesn’t exist. If I had an ibuprofen product I could get support for along that group of customers, I could be fat and happy with a brand serving a very unique clientele with a product that is just right for their needs.”

Retailers and brands need no strategy for out-Walmarting Walmart. They need to be smart, purposeful, and clear about which customer they serve.

The trucker ibuprofen carries a better strategy lesson than it first appears. The product needs no reinvention. What changes is the customer definition, the formulation choices that follow from long hours and irregular sleep, and distribution that puts it where those customers already stop. A brand owning a segment everyone else left unnamed faces no direct competition.

The Trends Hiding in Plain Sight

Asked what retailers are missing, the first answer is a caution about something they have bet heavily on.

Dave: “Retail media being one of them. I’m a fan, there’s a place for it, and I don’t think it replaces customer transactions and the real root of why we’re in business. You can charge people to advertise as part of a retail media network, and that’s powerful, but those dollars are a finite bucket. At some point the value you think your audience brings to the manufacturer will diminish. Whereas if you serve the right customer at the right time repeatedly, that’s a growth engine versus a finite engine.”

On the opportunity side, two categories move slowly against real demand.

The first is weight management understood as a lifestyle, reaching far outside the drug category.

Dave: “This is not just a GLP-1 solution. This is for people thoughtfully and purposefully intending to improve their quality of life. If I lose two pant sizes, I’m in the clothing realm of healthy living. How many clothiers are focusing on a transitional life change?”

The second is aging in place.

Dave: “Living well at home is a huge growth category, because people don’t want to go into assisted living or skilled nursing. They want to live vitally at home. So how do we serve that customer?”

Some retailers are already serving it, and the practice remains narrow.

Both share a structure. Each spans categories that retailers organize separately, which is why they go unserved. Weight management as a life transition touches pharmacy, apparel, food and fitness. Aging in place touches home goods, mobility, health and technology. A retailer organized by department has no natural owner for either, which leaves the opening to anyone building across the lines.

On five years out, the prediction is short and the weight falls on who ends up in charge.

Dave: “Thirty years ago online didn’t exist. Twenty years ago delivery to doorstep barely existed. Ten years ago drone delivery was a pipe dream. One year ago we never thought that an agentic AI would be telling me what I should pack for my upcoming trip. We’ve got to put customer at the center, but they’re going to be in charge. Five years from now, customer enabled, not technology enabled.”

Your Retail Strategy Checklist

Start with the first three. They cost a week and surface most of what needs deciding.

• Walk your own store as a customer and count every barrier between a shopper and a purchase
• Total your locked-case categories, then estimate the abandoned purchases alongside the shrink saved
• Ask whether your e-commerce and store teams have met, and put them in one room this month
• Pick your highest-volume category and design the complete solution around one job the shopper is doing
• Test your own products in three AI assistants with three different prompts, and record what surfaces
• Brief frontline staff on how to handle a shopper who arrives with an AI recommendation you lack
• Audit every AI project for whether it speeds up an old process or solves a new problem
• Write the end-of-life plan for your three slowest-moving product lines
• Answer the why, the how and the what for every employee before your next technology rollout
• Name one blind spot a larger competitor leaves open, and size the customer group inside it