Dr. Kristen Lee Santos

Tag: AI

  • An AI Strategy Is Only as Good as the Operating Model Behind It

    The tool everyone’s racing to deploy can’t build the coordination it depends on. That part is still the company’s job.

    Every AI strategy inherits the shape of the organization running it. That’s the part the demos never mention.

    A model is only as good as the operating model around it: who owns what, how anyone knows it’s working, and who has the authority to keep it moving when a team falls behind. Point a powerful tool at a well-run operating model and it compounds. Point it at a siloed one and it doesn’t fix the silos. It runs them faster, and splinters the message into more pieces, more publicly.

    One place I keep running into this is GEO, Generative Engine Optimization. It’s the topic on every marketing call, and on almost every one of those calls it lands on a single desk: whoever owns the website, or whoever owns content. The logic feels obvious. GEO sounds like SEO with a new first letter, and SEO was one team’s job. So GEO becomes one team’s job too.

    That instinct is the mistake.

    GEO isn’t SEO 2.0. Traditional SEO could largely be run from inside one team. The pages, the keywords, the metadata all lived in one place, under one owner. GEO doesn’t live in one place. When an AI answer engine decides what to say about a company, it pulls from everywhere at once: the Google Business Profile, the influencer network, Glassdoor reviews, Reddit threads, the press, the podcasts. The raw material for the answer is scattered across a dozen teams who’ve often never sat in the same meeting. Hand that to one person and they can’t win, not because they aren’t good, but because the job was never one person’s to do.

    For years, that kind of fragmentation was survivable. A customer might search a brand, click a few links, and stitch the story together on their own. Now the machine does the stitching, instantly, and hands back a single answer. If sales says one thing, the careers page says another, and Reddit says a third, the AI notices. And so does the buyer.

    This is where GEO stops being a marketing quirk and starts looking like the whole AI economy. McKinsey found that more than 80% of companies say generative AI has had no real impact on their bottom line, despite all the spending. The single biggest thing separating the companies that do see a profit impact isn’t a better model or a bigger budget. It’s whether they redesigned how work flows across their teams. Only about one in five have actually done it.

    It’s worth sitting with that. The winners aren’t the ones with the best AI. They’re the ones who changed how their people work together around it. Everyone bought the tool. Almost nobody rebuilt the operating model. And the operating model is the whole game.

    The good news is that the fix isn’t heroic, and it isn’t more technology. When the operating model actually works on the ground, it comes down to three fairly unglamorous things: clearly defined roles and responsibilities, so someone owns each input and everyone knows who owns what; reporting and analytics, so the team can see whether it’s working instead of hoping it is; and executive support, so the work survives the day-to-day and there’s a place to escalate when one team falls behind on its part.

    That’s the whole operating model: who owns what, how anyone knows it’s working, and who has the authority to keep it moving. GEO is simply one place a lot of companies are discovering they never built one.

    Any AI strategy will eventually expose whichever of those three is missing. Integration isn’t the thing a company does after the AI works; it’s the thing that makes the AI work at all.

    The teams pulling ahead aren’t buying smarter tools than everyone else. They decided, before the tool ever showed up, that the handoff between teams was the product.

    Kristen Lee Santos is a go-to-market executive focused on strategy, growth, and delivery. More on how she works: her résumé and the brands she’s building. Find her on LinkedIn.

  • “I Have a Person” — And Now Every Customer Can

    How AI scales the kind of loyalty that used to live in one person’s memory.

    The first sale gets all the glory. It gets the budget, the dashboards, the celebration in the team channel. But the second sale — the one that turns a first-time buyer into a regular — is where a business actually gets built. And a lot of go-to-market teams are still spending like it’s the other way around.

    None of this is new, which is the strange part. The idea that keeping a customer beats chasing a new one is about as old as commerce itself. What’s changed is the stakes. For years, cheap money let companies buy their way to the next growth number, so weak retention could hide in the background. That’s a lot harder now — investors want to see customers who stay and spend more, not just a pile of new logos. Winning those new customers, meanwhile, keeps getting pricier and noisier. And the real shift: the kind of one-to-one attention that used to live only in a great salesperson’s head can finally be built into how a company operates. Old idea, brand-new stakes.

    The numbers make the case on their own. Research popularized by Fred Reichheld at Bain & Company found that nudging customer retention up by just 5% can lift profits somewhere between 25% and 95%. And as Harvard Business Review has reported, winning a brand-new customer can cost five to twenty-five times more than holding onto one already in the fold. Retention isn’t the warm, fuzzy corner of marketing. It’s the best return in the P&L, hiding in plain sight.

    Here’s what that looks like when it’s real and not just a slide. Earlier in my career, I worked with a national automotive services company — hundreds of locations, and a whole lot of discount oil-change promotions. Those promos were fantastic at exactly one thing: getting cars into the bay. But a cheap oil change is not a business. If that was the only reason someone showed up, they’d happily drive to the next cheap oil change down the street next time. The discount was the doorway. It was never the relationship.

    The relationship lived in the second sale. So the model shifted around a free inspection — an honest, no-pressure look at the car — to catch the things a driver actually needed before they became a Saturday-morning breakdown. The free tire rotation was the sleeper move: rotating the tires meant a real look at the brakes, one of the most common higher-margin repairs, and the customer drove off better cared for either way. None of it worked without consistency, so we rebuilt the entire training system to make sure every location delivered the same experience, the same way, every time.

    The payoff was the part that surprised even us. By widening what those shops could do well — and earning the trust to do it — many locations raised their labor rates by as much as 20%. Not deeper discounts to chase volume. Higher prices, paid willingly, because the relationship had changed what people trusted the shop to handle. That’s the whole difference between renting a transaction and building something that lasts.

    Which brings me to the thing I’ll happily argue about with anyone: loyalty is not a discount. I’ve spent years building loyalty programs, and the ones that flop all make the same mistake — they quietly become one more way to hand out a coupon. Plenty of them are so complicated the customer can’t even find the path to value. A program that’s “sticky” because it dangles a deal is not the same as a brand someone genuinely feels part of.

    The brands that get this right make people feel like the brand is on their side. One of my favorite examples right now is, of all things, an AI tool I open every morning. It greets me by name — a small “back at it, Kristen?” — and offers me new features to try in beta. There’s not a discount anywhere in sight. But it makes me feel like I’m on the inside of something. I saw the same thing for years in auto service, where the clearest sign of a loyal customer was never a punch card. It was the customer who said, “I have a guy,” meaning the service advisor they trusted. Loyalty was never about the gimmick. It was about an ecosystem that understood them and looked out for them.

    And here’s the catch that held that kind of loyalty back for decades: that trusted relationship never scaled. It lived in one advisor’s memory, at one location, and it walked out the door the day that advisor retired. A brand could train for consistency, but it couldn’t make ten thousand customers each feel personally known.

    That ceiling is the one AI finally lifts. Done well, personalization means a brand can actually remember — what someone drives, what’s already been done, what’s coming due — and reach out like an advisor who’s paying attention instead of a promotions calendar that isn’t. It’s that same feeling — having a person who knows you — made repeatable, and available to everyone. That little morning greeting is a tiny taste of it. The real opportunity is designing that kind of attention across an entire customer journey, so it shows up everywhere, not just wherever a great employee happens to be standing.

    The caution matters just as much. Done carelessly, personalization tips into something creepy, or slides right back into being another discount engine. The brands that get it right use what they know to serve the customer, not to follow them around or buy them off. That line is a judgment call, and it belongs to leadership, not to a piece of software.

    So here’s the takeaway worth keeping: the first sale is a transaction, but the second sale is a relationship — and relationships are the only growth that compounds. The brands pulling ahead aren’t the ones with the loudest discount. They’re the ones treating customer experience as a growth engine instead of a support cost, designing the handoffs so no one gets dropped between marketing, sales, and service, and using every tool available — AI included — to give every customer a person. That’s not a loyalty program. That’s a business that lasts.

    Kristen Lee Santos is a go-to-market executive focused on strategy, growth, and delivery. More on how she works: her résumé and the brands she’s building. Find her on LinkedIn.