The Story of Footprint: Building the Future of Retail Intelligence Through AI

The Story of Footprint: Building the Future of Retail Intelligence Through AI

In a recent episode of Category Visionaries, Eli Wachs, CEO of Footprint, shared a story that every founder fears—watching your startup die in slow motion while you scramble to find something, anything, that works. What makes Eli’s story worth telling isn’t the happy ending at $100M ARR. It’s what happened in between: the pivot executed with six months of runway, the channel arbitrage play that bought them time, and the distribution insight that built a moat.

The Product Nobody Wanted

Footprint started with what seemed like a logical idea: help retailers predict which products would sell. The technology worked. The forecasts were accurate. But as Eli explains, technical success meant nothing in the face of organizational politics.

“We were building a product that could tell merchandisers which products were going to sell well and which products weren’t,” Eli recalls. The reality check came from a retail VP who laid out the impossible position Eli was asking him to take: “I have a team of 50 people whose job it is to forecast what’s going to sell. If I use your product and it works, I have to fire 30 of them. And if I use your product and it doesn’t work, I still have to fire 30 of them because I just spent a bunch of money on software that doesn’t work.”

That conversation crystallized everything wrong with their approach. They’d built software that forced buyers to bet their careers on being wrong about their own teams. “We were like, oh shit, we need to change what we’re doing,” Eli says. The company had maybe six months left.

The Pivot to Survival

Most pivot stories sanitize the desperation. Eli doesn’t. With the clock running out, the team made a decision based purely on where they could actually close deals. “Marketers were where the budget was. They had budget, they had urgency, and they actually wanted to try new things.”

This wasn’t elegant strategy—it was survival instinct. Marketing budgets operate under different physics than operations budgets. Marketers are measured on campaign ROI, not cost optimization. They have quarterly budgets they need to deploy. Most critically, trying new marketing technology doesn’t threaten anyone’s job security.

Footprint rebuilt their product as a marketing automation platform for retail. Same underlying technology, completely different buyer, completely different value proposition. The shift from “replace your team’s judgment” to “help your team execute faster” changed everything.

The Arbitrage Window

Even with a better product-market fit, Footprint faced a classic startup problem: how do you generate pipeline fast enough to survive? The answer came from recognizing an arbitrage opportunity most B2B companies missed.

“We basically said, we’re going to create a demand gen engine that is all about Facebook,” Eli explains. This was 2013-2014, when Facebook ads were still underpriced relative to B2B customer value. “Back in 2013-2014, Facebook ads were incredibly cheap and incredibly effective.”

The unit economics were straightforward: “We could put a dollar in and get $3 out consistently. That was the engine that helped us grow from zero to about 10 million in ARR.”

While competitors were grinding through enterprise sales cycles and conference circuits, Footprint was scaling through paid acquisition. The strategy had a shelf life—channel arbitrage windows always close—but it bought them time to build everything else they needed.

The Distribution Breakthrough

As Footprint grew past their initial success, Eli discovered something more valuable than their product features: a three-sided network that competitors couldn’t replicate.

Every retailer buys products from major CPG brands—Procter & Gamble, Unilever, Estee Lauder, Coca-Cola. Those brands need to reach retail customers to drive sales. But they’re separated from customer data by the retailers themselves. “All of our customers buy products from CPG brands,” Eli explains. “Those brands want to sell more products through our retailers.”

The insight: Footprint could become the connective tissue. “We realized we could go to these brands and say, hey, we have software deployed at 400 retailers. We can run a campaign on your behalf across all 400 of those retailers simultaneously.”

This created a flywheel that fundamentally changed their business model. Retailers wanted Footprint because CPG brands would help fund their marketing spend. CPG brands wanted access because Footprint gave them a direct line to retail customers at scale. And Footprint captured value from both sides. “It’s a differentiated distribution motion that is not replicable by any of our competitors,” Eli notes.

The beauty of this model is its defensibility. Competitors can copy Footprint’s product features in six months. They can’t replicate a network of 400 retail relationships and dozens of CPG partnerships that took years to build.

Scaling With Conviction

Footprint’s Series B marked the inflection point from survival to scale. “That was really the point at which we said, okay, we’ve figured out product market fit, we’ve figured out our initial go-to-market motion, now we need to scale everything,” Eli reflects.

The $35M round enabled three specific bets: expanding into retail media networks, building out the CPG co-marketing business, and moving upmarket into enterprise retail. Each required different capabilities than the scrappy startup that survived on Facebook arbitrage. “We had to hire a bunch of senior execs who had done it before,” Eli explains. “People who had scaled sales teams from 10 to 100, people who had built out marketing organizations.”

Today, Footprint sits at over $100M in ARR, growing 30-40% year over year. Some customers spend multiple millions annually. The company serves 400 retailers, with meaningful concentration in their top 25 accounts—a signal that their land-and-expand motion works.

Building the AI-Native Future

Eli’s current bet is the biggest yet: rebuilding Footprint’s entire platform as an AI-native product. “We basically are rebuilding the entire product as an AI native product,” he says. But this isn’t about adding chatbots or copilots—it’s about fundamentally changing what the product does.

The thesis: retail marketers don’t want better tools for building campaigns. They want outcomes. “Instead of having someone go in and build a campaign, they tell our AI, here’s what I’m trying to accomplish, and the AI builds the campaign for them,” Eli explains. The platform handles segmentation, content generation, channel selection, and optimization automatically.

This represents enormous execution risk. Rebuilding a $100M ARR platform could introduce bugs, alienate existing customers, or create migration problems. But Eli sees it as necessary to maintain optionality. “The thing that I always come back to is optionality. You want to make sure you have optionality in your business.”

The bet is that AI doesn’t just improve existing workflows—it obsoletes them entirely. If Eli’s right, Footprint becomes the system of record for retail marketing intelligence, where the platform understands customer behavior, predicts outcomes, and executes automatically. If he’s wrong, they’ve spent years rebuilding something customers were already happy with.

Either way, it’s the kind of bet that defines whether Footprint becomes a billion-dollar platform or gets disrupted by someone else willing to make it. For a company that pivoted with six months of runway, big bets feel familiar.