I’m tired of PR case studies that only show the wins.
You know the format. “We earned 150 links and 80 pieces of coverage for our client across tier 1 publications.” Cool. But what was the campaign? What did it cost? What was the response rate on your outreach? What about the campaign before that one, the one that got 3 links and an awkward client call?
The PR industry has a transparency problem. Agencies showcase their best work and bury everything else. That makes it impossible for anyone considering digital PR to set realistic expectations.
So here are seven real case studies. Some from our own work at Presslei, some from the dataset of 5,272 placements I analyzed, and two well known external campaigns. I’m including the numbers, the process, and, where applicable, what went wrong.
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 managed marketing for over a decade. By 2020, we’d shifted from buying links to earning media coverage through data driven PR. The AI fashion campaign was one of our most successful.
The angle was straightforward: we analyzed how AI tools (style recommendation engines, virtual try on technology, custom fit algorithms) were reshaping the made to measure fashion industry. We pulled together data from our own sales trends, combined it with publicly available market research, and packaged the findings into a story about the intersection of technology and traditional craftsmanship.
What Worked
The topic hit at the right moment. Fashion journalists were writing about AI anyway. Tech journalists were looking for industry specific AI stories beyond the usual chatbot coverage. Our campaign gave both groups a ready made angle with real data.
The personalization made the difference. Each pitch referenced a specific recent article by the journalist. A tech reporter who’d written about AI in retail got a different angle than a fashion editor who’d covered sustainability in luxury brands. Same data, different framing.
Six links from DA 55 to 82 doesn’t sound like a massive number. But consider the quality. These were editorial links from legitimate publications, the kind that would cost $2,000 to $5,000 each if you tried to buy them (and buying links that good is basically impossible anyway). Total cost of the campaign: about 40 hours of work and zero dollars in data acquisition.
The Takeaway
You don’t need groundbreaking original research to run a successful data PR campaign. We combined internal data we already had with publicly available information. The skill was in finding the angle that made it newsworthy.
I’ve written the full Hockerty case study with the complete backstory of how we went from buying hundreds of links per year to earning editorial coverage.
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 tools that audit AI systems for bias, and they wanted press coverage around political bias in ChatGPT, Claude, Gemini, and Copilot. The timing felt perfect. AI regulation was dominating headlines. The EU AI Act was being implemented.
We designed and executed a genuine research study. We tested four major chatbots across 12 politically sensitive topics with 48 unique prompts. We scored responses on a 1 to 7 political spectrum scale. We ran everything multiple times to test consistency.
The findings were legitimately interesting. Three of the four chatbots showed a measurable center left lean on economic topics. One was notably evasive, refusing to engage with 7 of the 12 topics. Consistency was poor across all four, with re-running the same prompt 24 hours later shifting the score by up to 1.5 points.
What Went Wrong
The methodology was solid. The findings were genuine. The outreach underperformed.
Our response rates were significantly below what we’d seen with the Hockerty campaigns. There are a few reasons I can identify in hindsight:
The topic was saturated. By the time we launched, dozens of outlets had already covered AI bias from various angles. Our study was more rigorous than most, but the journalists had fatigue. Another AI bias story was a hard sell.
Our journalist list for this topic wasn’t deep enough. We were pitching tech journalists who cover 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. The beat mismatch cost us.
The client brand wasn’t well known. When a study comes from a recognizable institution, journalists give it more weight. An unknown startup publishing AI research needs to work harder to establish credibility. We underestimated how much that matters.
What We Learned
This campaign taught us more than any success could have. We learned that topic saturation matters more than topic relevance. We learned that journalist selection is where campaigns are won or lost. And we learned that the first campaign for any new topic area will always have a learning curve.
I wrote the full Chatronix case study with complete transparency about the numbers because I think the industry needs more honest failure analysis. If every agency only shows their wins, how is anyone supposed to set realistic expectations?
Key Takeaway
The best PR case studies share what went wrong alongside what worked. Transparency about failures builds more credibility than cherry-picked wins.
Case Study 3: The Fashion Rankings (From Our 5,272 Placement Dataset)
Source: Analysis of placement data across multiple fashion brands
Campaign type: Seasonal rankings and data stories
Topic: Fashion trends, celebrity style, seasonal rankings
Results: Fashion was the #1 sector with 763 placements out of 5,272
The Pattern
When I analyzed 5,272 real media placements, fashion campaigns dominated with 763 placements, nearly 15% of the total. That wasn’t random. Fashion has characteristics that make it exceptionally well suited for data PR:
Visual angles. Fashion stories come with built in imagery. Celebrity outfit analysis, red carpet rankings, trend comparisons. Editors love stories that look good on the page.
Seasonal hooks. Fashion has a built in calendar of events: awards season, fashion weeks, wedding season, holiday party season. Each one creates a natural window for data stories.
Broad appeal. Fashion stories aren’t limited to fashion publications. Lifestyle, entertainment, and general news outlets all cover fashion angles. That multiplies your potential coverage.
What Worked
The most successful fashion placements in the dataset shared a pattern: they combined data (search trends, price comparisons, sales data) with a cultural moment (an awards ceremony, a celebrity appearance, a viral trend). The data gave the story credibility. The cultural moment gave it urgency.
Rankings performed particularly well. “Best dressed at the Oscars according to Google search data” generated more coverage than “new sustainable fashion collection launches.” People love rankings. Journalists love rankings. Google loves rankings.
The Takeaway
Pick a sector with natural seasonal hooks and visual appeal and you dramatically increase your chances of landing coverage. Fashion, food, travel, and real estate are all strong for this reason. B2B tech? Much harder. Not impossible, but you need to work significantly harder on the angle.
Case Study 4: Finance Comparison Studies (From the 5,272 Dataset)
Source: Analysis of placement data across finance brands
Campaign type: Cross market comparisons and cost of living studies
Topic: Financial comparisons, affordability rankings, salary analysis
Results: Finance was the #2 sector with 472 placements out of 5,272
The Pattern
Finance was the second most successful sector in our placement dataset. The campaigns that worked best were comparison studies: city vs city cost of living, country vs country salary purchasing power, generational wealth gap analysis.
These stories work because they’re inherently local and shareable. A study ranking the most affordable European cities for first time buyers gets picked up by publications in every city mentioned. 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 publicly available data: government statistics, central bank reports, cost of living indices. The story was in the analysis, not in the data itself.
Regional angles. Finance stories that included regional breakdowns (city level, state level, country level) generated significantly more coverage than national aggregate stories. Every region mentioned is a potential pickup.
Relatability. The best performing finance angles connected to personal experience. “Average rent takes 42% of take home pay in London” hits harder than “UK housing costs increase 3.2% year over year.” Same data, different framing.
The Takeaway
If you’re in fintech, financial services, or anything adjacent, data PR campaigns using free government data with regional breakdowns are your sweet spot. The data is free. The stories write themselves. And the regional angle multiplies your coverage potential.
Case Study 5: Health Survey Campaigns (From the 5,272 Dataset)
Source: Analysis of placement data across health and wellness brands
Campaign type: Survey based research and behavior studies
Topic: Health trends, wellness behaviors, mental health statistics
Results: Health consistently appeared in the top 5 sectors for placement volume
The Pattern
Health campaigns in the dataset followed a different model than fashion or finance. Instead of analyzing existing data, most successful health campaigns used original surveys: polling 1,000 to 2,000 people about their health behaviors, attitudes, or experiences.
The secret was in the questions. Boring question, boring story. Surprising question, surprising findings. “Do you exercise regularly?” produces nothing interesting. “Have you ever lied to your doctor about your lifestyle?” produces a headline.
What Made Health Campaigns Different
Emotional stakes. Health is inherently personal. Stories about health behaviors connect with readers on an emotional level that finance and fashion don’t always reach.
Expert commentary opportunities. Health stories almost always require expert quotes. If your brand can provide a credentialed health professional as a source, you become essential to the journalist’s story, not just the data provider.
Sensitivity requirements. Health campaigns need more careful handling than other sectors. Misleading health statistics can cause real harm, and journalists are (rightly) more scrutinizing of methodology. This means higher standards, but also higher quality coverage when you clear that bar.
The Takeaway
Health and wellness brands have a natural advantage in digital PR because the stories are inherently human and emotional. But the bar for data quality is higher. Invest in proper survey methodology and partner with credentialed experts for commentary.
Pro Tip
When analyzing a PR campaign’s success, look beyond link counts. Track brand mention sentiment, referral traffic quality, and whether coverage drove actual business outcomes.
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 media impressions, massive earned media coverage annually
Why It Works
I’d be doing you a disservice if I wrote about digital PR case studies without mentioning Spotify Wrapped. It’s the campaign that every data PR professional wishes they’d invented.
The concept is simple: once a year, Spotify gives every user a personalized summary of their listening habits. Your top songs, top artists, total minutes listened, most niche genre. Packaged in a visually shareable format designed for Instagram Stories.
The genius is in the distribution model. Spotify doesn’t need to pitch journalists. The users become the distribution channel. Millions of people voluntarily share their Wrapped results on social media. That organic sharing generates earned media coverage because journalists cover the phenomenon itself.
Every year, publications run stories like “Spotify Wrapped reveals the UK’s most streamed artist” and “What your Spotify Wrapped says about you.” Spotify doesn’t pitch those stories. They happen naturally because the campaign creates a cultural moment.
What You Can Learn From It
You probably don’t have Spotify’s user base. I certainly don’t. But the principle scales down beautifully:
Use your own data. Spotify uses data they already have (listening behavior). What data does your business generate that could tell an interesting story? Sales trends, customer behavior patterns, usage statistics. All of it is potential campaign fuel.
Make it shareable. The reason Wrapped goes viral is that it’s personal and visual. People share it because it says something about their identity. If your data campaign can tap into identity or personal relevance, the sharing happens organically.
Create an annual tradition. Spotify Wrapped works partly because people expect it now. An annual data release becomes a media event. You don’t need to reinvent the campaign each year. Just update 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 ran a project where they surveyed music critics, artists, and the public to create a ranked list of the 1000 most important songs since the year 2000. The list itself generated enormous engagement, debate, and secondary coverage.
Music publications covered it. General news outlets covered it. Individual artists shared their rankings. Twitter arguments erupted over what was included and what was left out.
The Lesson
Controversy is a feature, not a bug. The BBC knew that any ranked list of 1000 songs would generate disagreement. That disagreement drove engagement. People shared the list specifically to argue with it.
This principle applies directly to data PR campaigns. If your findings are too safe, too expected, too agreeable, nobody has a reason to share them. The best performing campaigns in our 5,272 placement dataset were the ones where the findings challenged assumptions or provoked a reaction.
That doesn’t mean being provocative for its own sake. It means asking questions that produce genuinely surprising answers and having the data to back them up.
What These Case Studies Teach Us
After spending far too long in spreadsheets analyzing what works and what doesn’t, here are the patterns:
Data is the common thread. Every successful campaign had data at its core. Not opinions, not announcements, not product features. Numbers that tell a story.
Timing multiplies everything. The Hockerty campaign worked partly because AI in fashion was trending. The Chatronix campaign struggled partly because AI bias was oversaturated. Same quality of work. Different timing. Different results.
Personalization beats volume. The campaigns with the best response rates weren’t the ones that pitched the most journalists. They were the ones that pitched the right journalists with the right angle.
Honesty about failures is more useful than showcasing wins. The Chatronix case study taught us more than the Hockerty success. If you’re only studying campaigns that worked, you’re missing the most valuable lessons.
You don’t need a massive budget. Several of these campaigns used free data. The most expensive element is always time, specifically the time spent researching angles, finding journalists, and personalizing pitches.
Frequently Asked Questions
What makes a good digital PR case study?
Specific metrics (links earned, DA of sites, traffic impact), clear methodology, and honest analysis of what worked and what did not.
How long do digital PR campaigns take?
Reactive campaigns can deliver results in days. Planned data studies typically take 4-8 weeks from concept to coverage.
What is a good link acquisition rate for digital PR?
10-30 linking domains per campaign is solid. Top campaigns can earn 50-100 plus.
Do digital PR links actually improve rankings?
Yes. Multiple studies show that earned editorial links from PR campaigns correlate with ranking improvements.
Want to Run Your Own Campaign?
If these case studies have you thinking about what a digital PR campaign could look like for your brand, here are some starting points:
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 and it’s better to know that before you invest.
Calculate the potential ROI with our PR ROI calculator. Understand what earned media links are actually worth compared to buying them.
Read the full analysis of 5,272 placements to see which sectors, topics, and campaign types generate the most coverage.
And if you want someone to build and run the campaign for you, that’s what we do. Including the honest post-campaign analysis, whether the results are good or not.
Ready to earn press coverage?
Free PR audit. We will 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.
