The Smartest Companies Are Hiring Economists to Break the News. Here's Why It's Working.

There is a job title quietly reshaping how the best companies in tech build their brands. It is not Head of Content or VP of Marketing. It is economist. And the companies hiring for it are not asking these people to build financial models or optimize pricing. They are asking them to tell stories.

Not marketing stories. News stories. The kind that get picked up by the New York Times, cited by the Federal Reserve, and surfaced by ChatGPT when someone asks a question about the economy.

Ramp hired Ara Kharazian as its lead economist. His work has been covered in the New York Times, Wall Street Journal, Financial Times, NBC News, NPR's Planet Money, Bloomberg, and The Guardian. Ramp's data has been cited by the Federal Reserve and is now in the Bloomberg Terminal. He writes a weekly Substack newsletter called Econ Lab and has turned Ramp's spend data into one of the most referenced proprietary datasets in business media.

Carta has Peter Walker running its Insights team, where he turns data from 29,000+ startups on the platform into reports on fundraising, valuations, equity compensation, and VC fund performance that the entire startup ecosystem reads.

LinkedIn has Karin Kimbrough as its Chief Economist, leading a team of economists and data scientists who publish research from the LinkedIn Economic Graph. She has been featured at the World Economic Forum, testified before Congress, and become one of the most visible voices in labor economics.

Redfin has Daryl Fairweather, PhD as its chief economist. Her insights have been featured on 60 Minutes, CBS Evening News, and in the New York Times and Washington Post. She has a book, a YouTube channel, and a public platform that reaches well beyond Redfin's customer base. Realtor.com has Danielle Hale doing the same. Experian has Chris Horymski.

These are not content marketers with new titles. These are economists, data scientists, and researchers who produce original analysis from first-party data that nobody else has access to. And the companies employing them are getting returns that go far beyond blog traffic.

Three Ways Companies Are Justifying the Investment

We keep hearing the same three arguments from teams that have made this bet. Each one tells a different story about what this kind of hire actually produces.

1. "Make my company look smart."

This is essentially how Ara Kharazian describes his job at Ramp. When he wrote about why he joined the company, he explained that the vision came from Ramp's head of communications, who wanted the company to be known for its data the same way it was known for its product and engineering.

The logic is simple. Ramp tracks over $100 billion in annualized business spend across 50,000+ companies. That is a dataset nobody else has. When Kharazian turns that data into a chart about AI adoption, corporate travel spending, or which SaaS vendors are growing fastest, it does something that no product marketing campaign could do: it makes everyone in Ramp's market, not just people in buy mode, see Ramp as an intelligent, authoritative company.

His own description of the role lays out the ambition: "make Ramp the most credible source on how companies spend and operate." A year in, Ramp data has been cited by the Federal Reserve, the Wall Street Journal, the New York Times, the Financial Times, CNBC, and Apollo's chief economist. The data is in the Bloomberg Terminal.

This is not a content play. It is a credibility play. And the credibility compounds. Every citation makes the next citation easier. Every journalist who uses a Ramp chart remembers where to go next time they need data on business spend.

2. Infiltrate private circles for earned media.

Peter Walker at Carta is a case study in what happens when data storytelling creates a person, not just a content library.

Walker built the Insights practice at Carta from scratch. His job is to find narratives inside Carta's dataset and tell them well. He does this through reports, LinkedIn posts, conference talks, and media appearances. The data covers fundraising rounds, equity splits, VC fund performance, and startup compensation, all drawn from the 29,000+ startups on Carta's platform.

But here is what Carta got that it probably did not plan for: Walker is now getting invited to speak at startup events, private VC dinners, and investor-only gatherings. He has become a brand ambassador across Silicon Valley, not because of a marketing campaign, but because he is the person in the room who brings data to the conversation.

That kind of access is almost impossible to buy. You cannot purchase a seat at a private VC dinner. You cannot sponsor your way into a founder's trust. But you can earn it by consistently being the person who shows up with the chart that changes the conversation. That is what Walker does, and Carta benefits every time he walks into a room.

3. Because if customers are not familiar with you when they start looking, you have already lost.

This is the one that connects to how buying actually works in 2026.

The Edelman-LinkedIn 2025 B2B Thought Leadership Impact Report found that 95% of decision-makers say thought leadership directly influences their purchasing decisions. But the buying journey does not start on your website. It starts months or years earlier, in the feeds and search results where your future customer is learning about their industry.

If they have never seen your name, never read your data, never encountered your perspective on a topic they care about, you are starting from zero when they enter the market for a solution you sell. You are not on the shortlist. You are not even in the consideration set.

An in-house economist producing original research changes that dynamic entirely. The work reaches people who are nowhere near a purchase decision. It reaches reporters. It reaches investors. It reaches the people who influence the people who buy. And it does this repeatedly, week after week, building familiarity and trust in a way that no demand generation campaign can replicate.

Why This Works Better Than Any Other Form of Earned Media

Reporters want stories that come with a chart.

This is the part that most marketing teams underestimate. Journalists are not looking for pitches. They are looking for data. They need a source they can cite, a number they can put in a headline, and an expert they can quote for context. An in-house economist with access to proprietary data gives them all three in a single email.

Redfin's Daryl Fairweather has been on 60 Minutes and CBS Evening News. That is not because Redfin has a great PR team (although it probably does). It is because Fairweather can walk a producer through housing market data that nobody else has and explain what it means in plain language. She is the source, not the pitch.

LinkedIn's Karin Kimbrough has spoken at the World Economic Forum and the OECD. She publishes the "Data at Work" newsletter on LinkedIn itself, where she translates labor market data from the Economic Graph into insights that millions of professionals read. Her title is Chief Economist, but her function is closer to editor-in-chief of a labor market publication that happens to be owned by LinkedIn.

The Wall Street Journal reported that LinkedIn job listings mentioning the term "storyteller" doubled over the past year. Over 50,000 listings in marketing alone. Google is hiring a customer storytelling manager. Microsoft is recruiting a senior director of narrative. Notion merged its internal comms, external comms, social media, and influencer functions into a single "storytelling team" of 10 people.

The reason is not hard to find: traditional media is shrinking. There are 17,000 fewer journalists working today than there were in 2000. Print newspaper circulation has dropped 70% since 2005. Google referral traffic to publishers dropped 33% in the year to November 2025. The old playbook of getting press coverage and letting reporters tell your story is disappearing.

But the companies that produce original data have reversed the flow. They are not pitching reporters for coverage. Reporters are coming to them for data.

The AI Search Layer Makes This Even More Valuable

Everything above was true before AI search became a factor. Now there is a second, compounding reason to invest in this kind of work.

A Semrush analysis of 325,000 prompts across ChatGPT Search, Google AI Mode, and Perplexity found that LinkedIn is the second most-cited domain across all three platforms, trailing only Reddit. Profound's data showed that for professional queries, LinkedIn is now the #1 most-cited domain across every major AI search engine.

On ChatGPT Search and Google AI Mode, 59% of citations come from individual creators, not company pages. Articles between 500 and 2,000 words get cited the most. The most-cited authors publish consistently, more than five times in a four-week window.

Now think about what an in-house economist does. They publish original research, usually on LinkedIn and a company blog, on a regular cadence. The posts include charts. The analysis is substantive. The author is a named individual with credentials. That is the exact kind of content AI search engines are pulling into responses.

Every time Kharazian publishes a Ramp spending report, every time Walker drops a Carta fundraising analysis, every time Fairweather writes about housing market trends on Redfin's blog, they are not only reaching today's audience. They are training tomorrow's AI models on who the authoritative source is for that topic. And once an AI model starts citing you, the citations reinforce themselves, because these models weight sources they have already relied on.

The companies that build this practice now are not just winning earned media. They are becoming the default source that AI tools reference when someone asks a question about their category. That advantage gets harder to catch up to with every passing month.

The Playbook Is Clear, and It Is Still Wide Open

The formula is not complicated:

Take proprietary data that nobody else has. Hire someone who can turn that data into stories. Give them the freedom to publish consistently. Let them build a public profile. Let reporters, conference organizers, and AI search engines find them.

The hard part is not the formula. It is the commitment. This is not a campaign with a start and end date. It is a permanent investment in being the smartest company in the room on topics that matter to your customers.

Ramp described the vision clearly: the big banks had all started their own think tanks covering American consumers, partly as a brand-building operation following the financial crisis. ADP's payroll data became an essential complement to government labor statistics. Zillow became where people actually go to make decisions about housing. Nobody had done the same for business spend.

That is the opportunity sitting inside every company with a meaningful dataset. Housing data, labor data, spend data, equity data, credit data, hiring data, every one of these is a potential newsroom waiting to be built.

And right now, most of these newsrooms do not exist yet.