Kevin Rowe, CEO of PureLinq, spent two years rebuilding how his agency earns links. One client campaign came out of it with more than 1,000 earned citations, including coverage in The Wall Street Journal, Fortune, Axios, Fox Business, and Reuters.
Those citations came in slowly at first. The first month produced exactly one link, the client complained, and Kevin talked him into staying with it. Placements picked up when journalists stopped waiting on his pitches and started emailing to ask when the next dataset would be ready.
Getting there meant giving up on link building as a standalone tactic. Kevin’s argument is that one piece of original research can earn links, brand mentions, AI citations, and social distribution at the same time. The approach came out of a two-year study of media placements across finance, higher education, ecommerce, and B2B.
Watch the full session on demand to see both case studies and the numbers behind them.
Why Isn’t Link Building Working Anymore?
Kevin opened with a story he said he had never told publicly. Around 2020, PureLinq nearly shut down.
“Overnight I think I lost half of our business because link building just stopped working,” he said. “So I had to rethink everything about how off-page SEO strategies worked.”
He named three reasons it happened and built the front of the session around them. Most SEO teams hit the third one before they can name it, watching click-through rate drop in Search Console while their rankings hold.
He came back to one line all session. “Deserving is the biggest thing you could ever do,” he said.
Action item: Flag every post in your last quarter that a competitor could have published word for word. Then watch the three forces that broke link building, and see the research asset Kevin built to replace that content.
What Kind of Data Story Do Journalists Actually Cover?
Rebuilding around research raises an obvious question: what makes a dataset worth a journalist’s time? Kevin narrowed it to five, and he called that slide the most valuable in the deck. See all five data story angles.
His student loan study ran on two of them. The team pulled free federal data on student debt, and the study earned full feature stories in Fox News and Fox Business.
None of that source data was hard to get. “It’s really low hanging fruit and I think almost anybody can do it,” Kevin said.
Free data and a language model also make a bad study easy to produce. “AI slop is the biggest problem in research right now,” Kevin said. “If you send out slop to journalists and they catch you, and your data is wrong, they will probably stop working with you.”
How Do You Turn a Blog Into a Research Hub That Ranks in AI Overviews?
A good angle is worth little if you can only produce one a year. Kevin’s first case study covers a team publishing them on a schedule.
The client was a B2B brand with national reach and no physical locations, losing visibility to local competitors. Its blog ran on commodity content: how to collect debt, top three financing tips. So the team deleted it and rebuilt it as a research hub.
Month one produced one link. Placements climbed month over month from there, and how high that monthly count got is the reason the client stayed.
Somewhere in that stretch, journalists started emailing first. “They started to keep coming back to us,” Kevin said. “That’s the inbound side of this.” The Wall Street Journal eventually asked the team to update a dataset on its own.
A full hub is not the only way to run this. A second client, an online university in a regulated category, kept its existing blog, added a handful of studies alongside it, and put its own professors in front of the media, earning links from one-to-one pitching and a run of podcast bookings.
Action item: Pick one dataset your team can update on a repeating schedule, then check how often PureLinq publishes a new study before you set your own cadence.
Can You Still Get Clicks When AI Overviews Show Up?
All that coverage raises a fair objection: does ranking still pay when AI Overviews answer the query on the results page?
“We are not in the zero click world. 100% not,” Kevin said. “You can still get a ton of traffic from search organically.”
His numbers back it. Individual studies pull traffic from AI Overviews by themselves, and several hold position one for commercial keywords, not just informational ones. See the traffic those studies actually pulled.
Those rankings came from studies built with real math behind them. His team’s office real estate study ranked US financial districts by foreclosure risk and earned Axios Seattle, Barron’s, and Wall Street Journal coverage. See how they scored and weighted every district.
Putting a credentialed expert on the byline worked fastest. One client’s study, written by a plant science professor at Utah State University, ranks first for its target terms and gets cited as the primary data point in AI Overviews.
Kevin closed with two smaller changes he did not expect to matter: the image and headline tactics that lifted click-through rate inside AI Overviews.
Q&A: Most Helpful Questions from the Webinar
Kevin took live questions for the last stretch of the session. Short versions of four of them are below. Kevin’s full answers are in the recording.
Q: Do syndicated press releases help brand authority and SEO, or should we focus on our own data studies plus outreach?
Kevin answered: do not count on syndication networks for links. “I wouldn’t rely on that for the links. You want pickups,” he said, meaning the value shows up only when a journalist picks the story up and writes about it. He sees syndication as useful for exposure, not as a link strategy.
Q: If we publish original research on our own site, how likely is AI to cite it without any further distribution?
Kevin answered: possible, but slow. Genuinely unique, high-value research can rank and get cited with very little pitching, and his team has seen it happen with an academic study written by a university scientist. Without distribution, though, topic and keyword selection have to be far more deliberate.
Q: What link building strategy do you recommend for local service businesses like home remodelers or wedding photographers?
Kevin answered: go local with news and data. Find something happening at the city or state level, then find data relevant to it, the way his team surveyed homeowners with irrigation systems to learn what blocks outdoor water efficiency. Uncover a concern those residents share and local media has a reason to cover it.
Q: Are you seeing an increase in brand mentions or qualified traffic from LLMs?
Kevin answered: better conversion, low volume. Clicks arriving from ChatGPT convert at a higher rate than average, including on ecommerce, and ChatGPT is the largest measurable source of direct clicks among the AI platforms his team tracks. “It’s not even close to Google search with AI Overviews,” he said.
Watch the Full Webinar
The full session covers all five data story angles, the placement and traffic numbers from both case studies, the research hub architecture and publishing cadence, the inbound PR flywheel, the ranking methodology behind the studies holding position one, the image and headline tactics that lift click-through rate in AI Overviews, and the AI tools Kevin’s team uses to find the right journalist for a story.
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