Six links from sites with Domain Authority 55 to 82, for about 40 hours of work and zero dollars in data costs. That’s Presslei’s Hockerty campaign, case study one below. Case study two, run for a paying client a few months later, used a far more rigorous methodology and still landed a fraction of that.
Same team, same process, wildly different outcomes. That gap is the part most PR write-ups skip. Agencies publish the wins and quietly drop the campaigns that underperformed, so anyone shopping for digital PR ends up with no real sense of what it costs or how often it actually works.
So this is seven case studies with the numbers and the failures left in. Two are our own campaigns at Presslei, one that worked and one that didn’t. Three come from a dataset of 5,272 placements earned by Search Intelligence, a UK digital PR agency, broken down by sector to see what actually drives coverage. The last two are Spotify Wrapped and a BBC songs study, included because the mechanics behind them are worth stealing even if you never ran them yourself.
Case Study 1: Hockerty AI Fashion Campaign
Client: Hockerty (custom menswear brand)
Campaign type: Data-driven proactive PR
Topic: How AI tools are changing custom fashion
Results: 6 backlinks from publications with DA 55 to 82
The Setup
Hockerty and Sumissura are custom clothing brands I co-founded and ran marketing for over a decade. By 2020 we’d moved from buying links to earning coverage through data-driven PR. The AI fashion campaign was one of the best examples of that shift.
The angle: AI tools, style recommendation engines, virtual try-on tech, custom-fit algorithms, were reshaping made-to-measure fashion. We combined our own sales trends with public market research and built a story around technology meeting traditional craftsmanship.
What Worked
The timing was right. Fashion journalists were already writing about AI. Tech journalists wanted an industry-specific AI story beyond the usual chatbot coverage. We gave both a ready-made angle backed by real data.
Personalization is what actually moved the needle. Every pitch referenced a specific recent article by that journalist. A tech reporter who’d covered AI in retail got a different framing than a fashion editor who’d covered sustainability in luxury brands. Same data, different angle for each inbox.
Six links from DA 55-82 sites cost about 40 hours of work and zero dollars in data acquisition. Editorial links at that quality would run you $2,000 to $5,000 each to buy, if you could buy them at all (you mostly can’t).
The Takeaway
You don’t need groundbreaking original research to run a good data PR campaign. We combined data we already had with public information. The actual skill was finding the angle that made it newsworthy.
Full backstory, including how we went from buying hundreds of links a year to earning editorial coverage: the complete Hockerty case study.
Case Study 2: The Chatronix Political Bias Study (The One That Didn’t Hit Its Targets)
Client: Chatronix (AI auditing tools)
Campaign type: Original research study
Topic: Political bias in major AI chatbots
Results: Underdelivered on link targets
The Setup
This was Presslei’s first paid client campaign. Chatronix builds AI-auditing tools and wanted press coverage on political bias in ChatGPT, Claude, Gemini, and Copilot. Timing looked perfect: AI regulation was dominating headlines and the EU AI Act was rolling out.
We ran a genuine study: four chatbots, 12 politically sensitive topics, 48 unique prompts, scored on a 1 to 7 political spectrum scale, repeated multiple times to check consistency.
The findings were real. Three of four chatbots showed a measurable center-left lean on economic topics. One dodged 7 of the 12 topics outright. Consistency was weak across the board — re-running the same prompt 24 hours later could shift a score by up to 1.5 points.
What Went Wrong
The methodology was solid. The findings were genuine. The outreach still underperformed, with response rates well below what we’d seen on the Hockerty campaigns.
Looking back, three things hurt us:
The topic was saturated. Dozens of outlets had already covered AI bias by the time we launched. Our study was more rigorous than most, but journalists were fatigued on the subject. A hard sell.
Our journalist list wasn’t deep enough for this topic. We pitched generalist tech journalists covering AI broadly. We should have gone narrower: policy reporters covering AI regulation, political journalists writing about tech’s influence on democracy, academic outlets that care about methodology. Beat mismatch cost us real coverage.
The client wasn’t a known brand. Journalists give more weight to a study from a recognizable institution. An unknown startup publishing AI research has to work harder to prove credibility, and we underestimated how much that matters.
What We Learned
This campaign taught us more than any win could have. Topic saturation matters more than topic relevance. Journalist selection is where campaigns are won or lost. And the first campaign in a new topic area always comes with a learning curve.
Full numbers and complete transparency in the Chatronix case study. Cherry-picked wins build a brand, but honest failures build credibility, and this one taught us more than Hockerty did.
Case Study 3: Fashion Rankings (From the 5,272-Placement Study)
Source: Search Intelligence’s dataset of 5,272 UK digital PR placements, analyzed by Presslei
Campaign type: Seasonal rankings and data stories
Topic: Fashion trends, celebrity style, seasonal rankings
Results: Fashion was the #1 sector, 763 of the 5,272 placements
The Pattern
Fashion campaigns dominated the dataset with 763 placements, nearly 15% of the total, and that’s not random. Fashion has structural advantages for data PR:
Visual angles. Celebrity outfit analysis, red-carpet rankings, trend comparisons all come with built-in imagery. Editors love stories that look good on the page.
Seasonal hooks. Awards season, fashion weeks, wedding season, holiday party season: fashion runs on a built-in calendar, and each date creates a natural window for a data story.
Broad appeal. Fashion stories aren’t limited to fashion outlets. Lifestyle, entertainment, and general news all cover fashion angles, which multiplies your potential coverage.
What Worked
The strongest fashion placements in the dataset combined real data (search trends, price comparisons, sales data) with a cultural moment (an awards show, a celebrity appearance, a viral trend). The data gave the story credibility. The moment gave it urgency.
Rankings outperformed everything else. “Best dressed at the Oscars according to Google search data” beat “new sustainable fashion collection launches” every time. People love rankings. Journalists love rankings. Google loves rankings.
The Takeaway
Pick a sector with natural seasonal hooks and visual appeal and your odds of coverage go up dramatically. Fashion, food, travel, real estate all have this built in. B2B tech doesn’t, so you’ll need to work a lot harder on the angle.
Case Study 4: Finance Comparison Studies (From the 5,272-Placement Study)
Source: Same 5,272-placement dataset, finance sector
Campaign type: Cross-market comparisons and cost-of-living studies
Topic: Financial comparisons, affordability rankings, salary analysis
Results: Finance was the #2 sector, 472 of the 5,272 placements
The Pattern
Finance ranked second in the dataset, and the campaigns that worked best were comparisons: city vs. city cost of living, country vs. country purchasing power, generational wealth gap analysis.
These stories work because they’re local and shareable. Rank the most affordable European cities for first-time buyers, and every city mentioned picks it up. The city that ranks #1 runs it as good news. The city that ranks last runs it as a “something must be done” story. Same data, different framing, double the coverage.
What Made Finance Campaigns Succeed
Free data sources. Almost every successful finance campaign in the dataset used public data, things like government statistics, central bank reports, cost-of-living indices. The story lived in the analysis, not in proprietary data.
Regional angles. Stories with city-level or country-level breakdowns generated far more coverage than national aggregates. Every region named is a potential pickup.
Relatability. “Average rent takes 42% of take-home pay in London” beats “UK housing costs increase 3.2% year over year.” Same data, framed around a person instead of a percentage.
The Takeaway
If you’re in fintech or financial services, free government data plus a regional breakdown is your sweet spot. The data costs nothing, the stories write themselves, and the regional angle multiplies your coverage.
Case Study 5: Health Survey Campaigns (From the 5,272-Placement Study)
Source: Same 5,272-placement dataset, health and wellness sector
Campaign type: Survey-based research and behavior studies
Topic: Health trends, wellness behaviors, mental health statistics
Results: Health consistently placed in the top 5 sectors by volume
The Pattern
Health campaigns followed a different model than fashion or finance. Instead of analyzing existing data, most successful health campaigns ran original surveys, polling 1,000 to 2,000 people about their behaviors, attitudes, or experiences.
The question is the whole game. “Do you exercise regularly?” produces nothing. “Have you ever lied to your doctor about your lifestyle?” produces a headline.
What Made Health Campaigns Different
Emotional stakes. Health is personal. It connects with readers on a level finance and fashion don’t always reach.
Expert commentary. Health stories almost always need an expert quote. Provide a credentialed source and you become essential to the journalist’s story, not just a data provider.
Higher bar for accuracy. Misleading health stats can cause real harm, and journalists scrutinize methodology harder here. That means more work up front, but better coverage once you clear the bar.
The Takeaway
Health and wellness brands have a natural edge because the stories are human and emotional. But the data-quality bar is higher: invest in real survey methodology and pair it with credentialed experts.
Pro Tip
Don’t just count links. Track brand mention sentiment, referral traffic quality, and whether the coverage actually moved the business.
Case Study 6: Spotify Wrapped (The Gold Standard)
Brand: Spotify
Campaign type: Personalized data storytelling at scale
Topic: User listening behavior, annual review
Results: Billions of social impressions, massive earned media every year
Why It Works
No digital PR case study list is complete without Spotify Wrapped. It’s the campaign every data PR person wishes they’d invented.
The concept: once a year, Spotify hands every user a personalized summary of their listening, top songs, top artists, minutes listened, most niche genre, packaged for Instagram Stories.
The genius is the distribution model: users are the distribution channel. Millions of people voluntarily post their Wrapped results. Journalists then cover the phenomenon itself — no pitching required.
Every December, publications run “Spotify Wrapped reveals the UK’s most streamed artist” and “What your Spotify Wrapped says about you.” Spotify never pitched those stories. They happen because the campaign creates a cultural moment on its own.
What You Can Learn From It
You don’t have Spotify’s user base. Neither do I. But the principle scales down fine:
Use data you already have. Spotify uses listening behavior it already collects. What does your business generate that could tell a story? Sales trends, customer behavior, usage stats are all campaign fuel.
Make it shareable. Wrapped goes viral because it’s personal and visual. People share it because it says something about who they are. Tap into identity or personal relevance and sharing happens on its own.
Make it annual. Wrapped works partly because people now expect it. An annual data release becomes a media event — you don’t reinvent the campaign each year, just refresh the data.
Case Study 7: The BBC 1000 Songs Study
Organization: BBC
Campaign type: Data journalism and audience participation
Topic: The most important songs since 2000
Results: Massive audience engagement, hundreds of pieces of secondary coverage
Why It Matters for Digital PR
The BBC surveyed music critics, artists, and the public to rank the 1000 most important songs since 2000. The list alone generated huge engagement, debate, and secondary coverage.
Music publications covered it. General news covered it. Artists shared their own rankings. Twitter argued over what got left off.
The Lesson
Controversy is a feature, not a bug. The BBC knew any ranked list of 1000 songs would spark disagreement, and that disagreement drove the sharing. People posted the list specifically to argue with it.
Same principle applies to data PR. If your findings are too safe or too expected, nobody has a reason to share them. The strongest campaigns in the 5,272-placement dataset were the ones where the findings challenged an assumption or provoked a reaction.
That doesn’t mean being provocative for its own sake. It means asking questions with genuinely surprising answers, and having the data to back them up.
What These Case Studies Teach Us
A few patterns hold up across all seven campaigns, no matter the sector or the budget:
Data is the common thread. Every successful campaign had data at its core, not opinions, not announcements, not product features, but numbers that tell a story.
Timing multiplies everything. Hockerty worked partly because AI in fashion was trending. Chatronix struggled partly because AI bias was oversaturated. Same quality of work, different timing, different results.
Personalization beats volume. The best response rates didn’t come from pitching the most journalists. They came from pitching the right journalists with the right angle.
Honesty about failure teaches more than showcasing wins. Chatronix taught us more than Hockerty did. If you only study campaigns that worked, you’re missing the most useful lessons.
You don’t need a big budget. Several of these campaigns ran on free data. The real cost is always time: researching angles, finding journalists, personalizing pitches.
Two more numbers worth knowing before you start: a solid campaign lands 10 to 30 linking domains, and the strongest performers above cleared 50 to 100+. On timeline, reactive pitches can land coverage within days, while a planned data study like Chatronix or the fashion rankings usually takes four to eight weeks from concept to published coverage.
Want to Run Your Own Campaign?
If these case studies have you thinking about what this could look like for your brand, start here:
Test your angle with our PR campaign idea generator. It’ll help you brainstorm data-driven story concepts.
Check your readiness with our PR readiness assessment. Not every brand is set up for reactive PR, better to know before you invest.
Calculate the potential ROI with our PR ROI calculator. See what earned media links are worth compared to buying them.
Read the full analysis of the 5,272-placement study to see which sectors, topics, and campaign types earn the most coverage.
Want someone to build and run it for you? That’s what we do, including the honest post-campaign breakdown, whether the results are good or not.
Ready to earn press coverage?
Free PR audit. We’ll tell you exactly what campaigns would work for your brand.
About the Author
Salvador Jovells
Founder of Presslei. 12+ years in ecommerce SEO across international markets. After a decade of link buying for Hockerty and Sumissura, I reverse-engineered 5,272 earned media placements and founded a reactive PR agency that builds authority through data-driven stories journalists actually want to publish. Based in Zurich.
