How We Built an Inc. 500 #1 Fastest-Growing AdTech Startup in America

What the first wave of machine learning can teach AI startups about winning in a crowded market

When a technology is new, the best product wins. When the technology commoditizes, the best story wins. The tricky part is knowing which phase you’re in, because most founders figure it out too late.

I was inside one of those transitions. In July 2011, I joined AdRoll as the company’s first Head of Marketing. Small team in SOMA. Machine learning running behind the scenes, predicting which users would convert and bidding on ad inventory in real time. The technology was genuinely strong, and in the early days it was enough to grow on. But the market was catching up fast. There were dozens of retargeting companies, and their ML was getting better every quarter.

When I left in December 2012, AdRoll had over 10,000 global enterprise and SMB customers. The Inc. 500 ranked us the #1 fastest-growing marketing company in America, #7 overall, at 15,064% growth. Forbes named us one of America’s Most Promising Companies. The SF Business Times named us the fastest-growing company in the Bay Area.

The technology got us in the game. It didn’t win us the game. What won was figuring out the story at the exact moment the technology was leveling. And that’s the transition I’m watching AI startups struggle with right now.

What Did the Ad Tech Market Look Like in 2011?

To understand why AdRoll’s breakout matters for today’s AI startups, you need to understand how crowded and confused the ad tech market was in 2011. It was the wild west. Real-time bidding had just opened up the programmatic ad exchanges, and suddenly every company with a data science team could build a retargeting product. There were dozens of retargeting companies. Many of them had comparable technology. The underlying ML models were doing roughly the same thing: predicting which users were most likely to convert and bidding on ad inventory in real time.

Sound familiar? It should. This is exactly what’s happening in AI right now. The foundation models are available to everyone. The technology is commoditizing fast. Dozens of companies are building similar products on top of the same underlying capabilities. And they’re all struggling to explain why they’re different.

In 2011, the retargeting companies that led with technology, the ones whose pitch was “our algorithms are better”, mostly lost. Not because their algorithms were bad. Because “better algorithms” isn’t a message that a marketing director at a mid-size e-commerce company can evaluate, act on, or remember. The companies that won were the ones that translated the technology into a story the buyer could understand and trust.

What Was AdRoll’s Positioning and Why Did It Work?

When I arrived at AdRoll, the company was growing on the strength of its product, but the brand was undifferentiated. The pitch was essentially: we do retargeting, we use machine learning, we’re on all the major exchanges. This was true of at least ten other companies.

The repositioning work I led over the first two quarters was built around a simple insight that I almost missed: our customers didn’t care about machine learning. They cared about results. And they cared about simplicity. Most retargeting platforms at the time were complex, opaque, and required significant technical expertise to operate. AdRoll’s product was genuinely easier to use. But we weren’t talking about ease of use. We were talking about algorithms. We had to train ourselves to start leading with what mattered to the buyer.

We repositioned AdRoll as the retargeting platform that makes display advertising work for brands of all sizes. Not the smartest. Not the most advanced. The one that actually works for you. That shift, from “our technology is sophisticated” to “we make this simple and effective,” changed everything about how we showed up in the market.

The new positioning showed up in every touchpoint. The website was rewritten to lead with outcomes, not capabilities. The sales materials were rebuilt around customer results, not product features. The PR strategy focused on business growth stories, not technology stories. When we pitched Ad Age and AdExchanger and Inc., we didn’t lead with our ML stack. We led with growth and solving problems for businesses of all sizes. The technology was the proof. The story was about the customer.

How Did We Build a Category-Leading Startup in Eighteen Months?

The brand work happened on four fronts simultaneously, and the sequencing mattered.

First, content and thought leadership. We built a content engine that positioned AdRoll as the authority on retargeting and performance marketing. Not the vendor that sold retargeting. The company that taught the market how it worked. This is a distinction that most SaaS companies miss. When you educate the market, you become the reference point. When a marketing director googles “how does retargeting work,” and your content is what they find, you’ve won the conversation before the sales call starts. We increased blog traffic by 20x and social following by 15-25x across channels.

Second, PR that told a growth story. We secured 145 unique placements in outlets including Ad Age, Adweek, Inc., The New York Times, Wall Street Journal, Forbes, TechCrunch, and GigaOm. These weren’t product announcements. They were business stories: the fastest-growing ad company, the Inc. 500 ranking, the customer growth, the Facebook Exchange partnership. Every press hit reinforced the narrative that AdRoll was the company winning in this space. Not the company with the best technology. The company winning. That’s a different message, and it’s the one that convinces prospects to get on a demo.

Third, demand generation that matched the positioning. I built the product marketing and lead generation strategy around Facebook Exchange retargeting and dynamic ad products, areas where we had genuine product differentiation and where the market was moving fast. This wasn’t spray-and-pray demand gen. It was tightly aligned with the positioning: we’re the company that makes the newest, most powerful ad formats accessible to businesses of all sizes. The strategy secured AdRoll’s market leadership by acquiring more customers on Facebook Exchange than any competitor.

Fourth, sales enablement. New materials increased cold sales responses by 6x. The sales team had been pitching technology to people who wanted outcomes. When we gave them materials that led with customer results and backed them with technology proof points, the conversion rate changed.

What’s the Parallel to AI Startups Right Now?

Everything I just described is happening again, right now, in AI. I sit in meetings with AI founders and hear the same pitches I heard from ad tech companies in 2011. The parallels are so precise they’re almost eerie.

Commoditizing technology. In 2011, every retargeting and adtech SaaS company had ML-powered bidding. In 2026, every AI startup has access to the same foundation models. The technology gap that existed two years ago has narrowed to months, sometimes weeks. The companies that lead with “our AI is better” are making the same mistake that the retargeting companies made when they led with “our algorithms are smarter.”

Buyer confusion. In 2011, marketing directors couldn’t tell the difference between ten retargeting companies. In 2026, enterprise buyers can’t tell the difference between ten AI assistants or ten AI analytics tools. The pitches sound identical. The demos look similar. The differentiator isn’t in the product. It’s in the story.

Feature-first messaging: The retargeting companies that lost talked about their technology stack. The AI startups that are struggling right now talk about their model architecture. Customers don’t buy architecture. They buy outcomes. The companies that figure out how to talk about outcomes in language the buyer already understands are the ones that will break through.

The education opportunity: AdRoll won in part because we taught the market how retargeting worked. Most marketing directors and small to medium size business operators in 2011 didn’t understand programmatic advertising. By educating them, we became the trusted guide. The AI startups that figure out how to educate their buyers, not just pitch them, will build the same kind of authority. The market is confused. The company that clarifies the confusion becomes the default choice.

What Are the Lessons That Transfer Directly?

After watching the ad tech cycle play out and now watching the AI cycle unfold, I think there are five lessons that transfer directly.

The technology is necessary but it’s not the story. AdRoll’s ML was strong. So was everyone else’s. What separated us was that we stopped talking about the ML and started talking about what it did for people. AI startups need to make the same shift, and most of them haven’t.

Simplicity wins in crowded markets. The retargeting company that made the technology accessible to a marketing director with no technical background beat the one with marginally better algorithms. The AI tool that a product manager can use without calling engineering will beat the one with a more powerful model that requires a data scientist to operate.

Educate, don’t pitch. When you teach the market how your category works, you become the reference point. When you pitch your product, you become one of twenty options. The content and communications investment we made at AdRoll paid for itself many times over because it positioned us as the authority, not just a vendor.

Customer stories outperform product stories. Every piece of press we placed, every piece of content we created, every sales conversation that converted, led with what customers achieved. Not what our product could do. Not how our technology worked. What happened for the people who used it. AI startups are drowning in product marketing and starving for customer marketing.

Build the brand before you need it. By the time we were named the #1 fastest-growing marketing company, the brand recognition was already built. The ranking confirmed what the market already believed. If we’d tried to build the brand after the ranking, we’d have been one of hundreds of companies claiming to be fast-growing. The brand work has to come first, because it’s what makes everything else land.

What Happened to Ad Tech After the Commoditization Wave?

Here’s the part of the story that matters most for AI founders, and the part nobody tells. Commoditization wasn’t the only thing that hit ad tech. Regulation came next, and it was brutal.

GDPR went into effect in Europe in May 2018. California followed with CCPA in 2020. Apple rolled out App Tracking Transparency in 2021, which effectively dismantled third-party cookie tracking on iOS. Google announced the deprecation of third-party cookies in Chrome. The entire foundation of the ad tech industry, the ability to track users across sites and build behavioral profiles, got regulated and restricted in a span of about five years.

The companies that survived weren’t the ones with the best technology. They were the ones with the strongest customer relationships, the clearest positioning, and enough brand equity to pivot when the rules changed. AdRoll survived and is still operating, now called NextRoll. Many of its 2011 competitors didn’t. The ones that bet entirely on technical superiority in a tracking-dependent model had no cushion when the regulatory environment shifted under them.

AI is heading toward the same cycle, just faster. The EU AI Act is already in force. The FTC is investigating AI companies. Copyright lawsuits are reshaping how training data can be used. The compliance and regulatory pressure on AI startups over the next three years is going to compress margins and narrow the space for aggressive growth. The companies that have invested in brand, community, and customer trust will have the flexibility to adapt. The ones that have invested only in technology will not.

This is why I keep pushing AI founders to build the soft assets now. Not because they’re nice to have. Because they’re the only things that survive when the technology gets commoditized by foundation models and then further constrained by regulation. Story, community, trust, and narrative authority don’t care about model updates or policy changes. They compound regardless.

Why Does This Matter for AI Founders Right Now?

The window for AI startups to establish category leadership is closing fast. The foundation model providers are integrating features that startups sell as standalone products. The enterprise incumbents are acquiring AI capabilities. The venture money is getting more selective. The companies that haven’t figured out their story by the end of 2026 will be competing on price in a market where the technology is approaching commodity.

This isn’t speculation. I watched it happen in ad tech. The retargeting companies that didn’t establish a differentiated brand by 2013 spent the next five years grinding in a commoditized market with shrinking margins. The ones that built the brand early, AdRoll among them, had the positioning, the press relationships, the customer trust, and the market narrative to sustain leadership even as the technology leveled out.

AI is on the same trajectory. The technology will level. The models will converge. What won’t converge is the story. The brand. The community. The trust. Those are the assets that compound, and the companies that build them now will be the ones still standing when the commodity shakeout hits.

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If this resonated:

For AI founders: If your technology is strong but your market position isn’t matching it, the problem is almost always story. I work with AI startups through Wondr Venture Studio on positioning, narrative strategy, and go-to-market. DM me if you want to talk through it.

For investors: If you’re watching portfolio companies struggle with traction despite strong technology, the pattern is remarkably consistent. I’ve seen it before and I know how to fix it.

For everyone: Subscribe for case studies and essays on AI strategy, brand building, and the decisions that compound. Or share this with an AI founder who’s leading with technology when they should be leading with story.

About the Author:
Maly Ly is the Founder & CEO of Wondr, an AI-native social and discovery platform, and the founder of a growth lab advising early-stage startups. She is a founder, growth executive, and operator who has helped scale multiple startups to breakout growth and unicorn status across AI, Web3, aerospace, SaaS, and consumer tech.

Her experience includes leadership roles at category-defining companies such as AdRoll—named the Inc. 500’s #1 Fastest Growing Marketing Company—and Relativity Space, which reached a $2.3 billion valuation and became the second most valuable private space company after SpaceX. She has also held leadership positions at Eventbrite, Sojern, YouCaring (later acquired by GoFundMe), and SecurityPal AI, and earlier in her career helped launch top-selling products for franchises including Star Wars, Tomb Raider, and Nintendo.

Beyond tech, Maly spent two decades producing art, music, and  corporate and underground events, while leading digital campaigns for global brands including Mercedes-Benz, Aston Martin, Burberry, and Williams Sonoma. She is also a Certified High Performance Coach.

Her work has been recognized by Forbes, Fast Company, and Direct Marketing News with its Hall of Femme honor. She and her work have been featured in The New York Times, The Washington Post, CNN, NPR, Forbes, The Tonight Show, and The Ellen Show.

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