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Data storytelling is one of the best ways to get cited in AI search right now — but how do you create stories strong enough to actually get picked up by media outlets?
At Stacker's Cited 2026 summit, I sat down with Ara Kharazian, Lead Economist at Ramp, and Kelly Soderlund, Head of Insights at Samsara, to discuss how data storytelling can move beyond corporate self-service and have a real impact.
Here's how these storytellers teams built their operations up from scrappy and experimental to the big time — and how, done at scale, data storytelling can function as a product in its own right.
What are the virtues of great data storytelling?
Some of the qualities behind strong content programs might surprise you. Ara and Kelly said their work has a sense of responsibility, independence, and bravery.
Data storytelling as a responsibility
Many brands are sitting on a treasure trove of data that they need to learn to make full use of.
"The first step is recognizing that you have data that can contribute to an important conversation," Kelly said. "Samsara collects 25 trillion data points every year from the physical world. I almost feel like we have a responsibility to tell journalists and the public what's happening on the ground."
Independence and impartiality in branded data storytelling
Every executive loves the idea of getting customer data into top-tier outlets, Ara said.
"But once they realize what it actually requires — hiring someone with editorial independence, giving them freedom to publish without everything getting watered down, sometimes talking about politics — that's when people get nervous."
Still, he said that the executives who really understand the importance of data storytelling also realize these strategies might not be as risky as they think, "and the upside can be enormous if it's done well."
Stacker's conversations with publishers back this up: Brand editorial has to hold itself to the same standards as traditional journalism in order to earn widespread distribution.
Kelly said she gauges impartiality by asking herself: Is it truthful? Is it honest? Am I being transparent? She said she discloses any biases in the data upfront, being clear about how she approached the analysis. Because company data is inherently shaped by a brand's own customer base, she stress-tests her conclusions with third-party validation, checking that what she's seeing in the product data actually reflects a broader trend.
At Ramp, the relationship with traditional media is symbiotic rather than competitive, Ara said.
"We benefit from their coverage and distribution, and I think they benefit from having access to a unique dataset they can cite," he said.
How bravery can pay off
Kelly said one of the first data storytelling pieces she worked on at her previous employer, Hipmunk, was about data that showed Trump Hotel bookings had plummeted during the 2016 presidential campaign. She said the story "absolutely blew up," with media coverage and interest from major news outlets.
"It was one of those high-risk, high-reward moments where I could really see the power of data storytelling and what happens when you have access to a unique dataset that reveals something larger about the world," she said.
Executive buy-in is necessary for a data storytelling program to work, Kelly added — but "you create buy-in through success."
What makes a great story?
There's more than one way to build a story that resonates with both readers and LLMs. Here are a few approaches that work:
Reacting to news — and creating it in the process
Newsjacking is a familiar PR tactic. It involves inserting a brand's point of view into the day's news story. But Kelly's team at Hipmunk took the idea a step further with the Trump Hotels story above. It wasn't a cookie-cutter brand exercise, but a genuinely newsworthy finding that came from proprietary data.
Using data to challenge narratives
When she worked at Navan during the height of the Covid pandemic, Kelly said that many claimed business travel was dead because large enterprises had stopped sending employees on the road. But Navan's customer data told a different story: Startups were still traveling to meet customers and close sales. To find the nuance, the team overlaid week-over-week business travel data with Covid case counts from the CDC, and found that travel dipped when case counts spiked — then rebounded as cases fell. The story offered proof that traveling when case counts were low wasn't as taboo as the prevailing narrative suggested. As Kelly put it, recognizing that you have data relevant to a live conversation lets you "influence a narrative — or at least provide another perspective based on what you're seeing."
Using data to fill a gap
Ara pointed to the company's flagship research project, the Ramp Index, which measures the share of firms that use and pay for AI. It's an "extremely simple metric," he said, "but it wasn't otherwise available." With AI generating enormous buzz — and enormous confusion for small businesses trying to figure out where to start — the index gives Ramp a concrete way to speak to uneven AI adoption.
Rather than cover every possible content angle, Ramp takes a deliberately narrow approach to the stories it pursues. Ara filters new ideas through two questions: “Will this content actually help businesses on our platform make better decisions?” and “What do we want to be known for?” Those two questions cut out a lot of noise and help refine the brand's research pillars.
These storytelling leaders show that great data stories aren't marketing ploys — they require editorial independence, intellectual honesty, and the willingness to publish something risky when the numbers back it up. But underneath the strategy, it still comes down to curiosity: as Kelly put it, the real work is opening up a huge spreadsheet and hunting for the diamonds in the rough.
Ken Romano heads up the distribution and product teams at Stacker. He previously led product teams at The Associated Press and The Nielsen Company.
