Our First Campaign Missed Targets: Lessons

Most agencies only show you the wins: the 200+ placements, the viral data study, the homepage feature on TechCrunch. Nobody talks about the campaigns that underdelivered.

This is the story of Presslei’s first paid campaign. Our client was Chatronix, an AI auditing company. The topic was political bias in AI chatbots. The results were disappointing, and it taught us more about reactive PR than any success could have.

I’m sharing this because the PR industry has a transparency problem. If we’re asking clients to trust us with their money and their reputation, the least we can do is be honest about what works and what doesn’t.

The Brief

Chatronix came to us in late 2025 wanting press coverage on one angle: political bias in the major AI chatbots. The timing looked good. AI regulation was dominating headlines, the EU AI Act was rolling out, and governments were asking hard questions about how these systems shape public opinion.

We proposed an original research study instead of a press release or thought-leadership piece. Actual data journalists could cite.

The plan: test four major chatbots (ChatGPT, Claude, Gemini, Copilot) across 12 politically sensitive topics, from immigration to climate legislation to gun control, and score how their answers skewed left or right. Run it multiple times to check for consistency, then package the findings into something newsworthy.

Chatronix paid a deposit of EUR 644 and we got to work.

The Study

The data held up. The pitch didn’t. We spent about two weeks designing the methodology and running the tests. Each chatbot got the same 48 prompts (12 topics, 4 variations each), scored on a 1–7 political spectrum scale, 1 being strongly progressive and 7 strongly conservative.

The findings were genuinely interesting:

• Three of the four chatbots showed a measurable centre-left lean on economic topics, particularly wealth inequality and healthcare policy
• One chatbot was notably more evasive, refusing to engage with 7 of the 12 topics entirely
• Responses shifted depending on how the question was framed. The same topic asked as a policy question versus a moral question produced different political leanings from the same model
• Consistency was poor across all four. Re-running the same prompt 24 hours later could shift the score by up to 1.5 points

We had a solid dataset, clear quotable findings, and a clean study page with methodology, charts, and a two-minute summary any journalist could scan.

The Outreach

Final score: 87 journalists pitched, 6 responses, 0 placements. Not a single story published. Here’s exactly how that happened.

We compiled a target list of 87 journalists covering AI, technology policy, and digital rights: national tech reporters (Wired, The Verge, Ars Technica), political technology writers, and AI specialists at outlets like MIT Technology Review and VentureBeat.

Outreach ran about three weeks, in three waves:

Wave 1 (Week 1): 34 journalists, our top tier, personalised emails referencing their recent coverage. Open rate: 38%. Response rate: 3 replies. Zero commitments to cover.

Wave 2 (Week 2): 28 journalists, second tier, broader outlets. We tweaked the subject line and led with the single most surprising finding (the framing effect on political lean). Open rate dropped to 29%. Two responses, both “interesting but not for us right now.”

Wave 3 (Week 3): 25 journalists, including freelancers and newsletter writers. By now a major AI safety story had broken (a leaked internal memo from one of the big labs), and every tech journalist was chasing that instead. Open rate: 24%. One lukewarm response.

What Went Wrong

Here’s the honest breakdown.

1. We picked a crowded week and didn’t adapt.
The AI news cycle in late 2025 was relentless: a new model release, a new regulation, a new controversy, every week. Our study was interesting but not urgent. When the leaked-memo story broke in Week 2, we should have paused and waited for the cycle to cool. We pushed through instead. Mistake.

2. The study tried to say too much.
12 topics, 4 chatbots, multiple framings. The dataset was rich but the pitch was complicated. Journalists don’t want a buffet, they want one finding they can build a headline around. “AI chatbots give different political answers depending on how you ask” is a story. “Here’s a comprehensive analysis of political bias across 12 topics” is a research paper. We pitched the research paper.

3. Our subject lines were too safe.
“New research: Political bias in AI chatbots” tells you what’s in the email but gives no reason to open it. We should have led with the sharpest finding, every time.

4. We had no journalist relationships yet.
This was our first campaign, cold-emailing everyone. No journalist had heard of Presslei or Chatronix. That matters more than the industry admits. A pitch from an unknown agency about an unknown company faces a credibility gap that even good data doesn’t always close.

What We’d Do Differently

If I ran this exact campaign again today, here’s what would change:

Single finding, single headline. Pick the most counterintuitive result and build the entire pitch around that one data point. The full methodology lives on a study page for anyone who wants to dig deeper. The pitch email is one finding, one stat, one sentence.

Reactive timing, not proactive timing. Instead of launching on our own schedule, prep the data and wait. The moment a relevant story breaks (a chatbot gives a controversial political answer, a politician calls out AI bias), have the data ready to offer as expert comment within hours. That’s reactive PR done properly.

Warm before you pitch. We now spend time engaging with target journalists on social before ever sending a pitch: comment on their articles, share their work, build name recognition. Cold email to a warm contact converts better than cold email to a cold one.

Shorter outreach window. Three weeks is too long for one campaign. If the first wave doesn’t land, something’s wrong with the pitch or the timing. Two waves max, then regroup.

Exclusivity. For a data study like this, offering an exclusive to one top-tier outlet first beats blasting 34 journalists at once. Exclusives create urgency. Mass emails don’t.

What This Taught Us

This campaign shaped how Presslei works today. Every process we now follow, from how we structure findings to how we time outreach to how we write subject lines, traces back to what went wrong with Chatronix.

Three things changed:

First, we moved to reactive-first. We still build original data studies, but we design them to deploy in response to breaking stories, not as standalone pitches. Timing got dramatically better.

Second, we adopted a “one finding, one pitch” rule. Every campaign gets distilled to a single headline before outreach starts. If you can’t say it in one sentence, it’s not ready.

Third, we track journalist engagement before pitching. No cold email goes out without at least two prior touchpoints (social interaction, content sharing, event attendance). It takes longer to launch, but response rates are incomparably better.

Why I’m Publishing This

If an agency has never told you about a failure, either it’s hiding one or hasn’t done enough work to have one. There’s a version of this post where I spin the Chatronix campaign as a “learning experience” and bury the numbers. That would be easy, and nobody would question it.

But I started Presslei because I thought the PR industry needed more honesty. Agencies that only share success stories are doing prospective clients a disservice. You deserve to know what failure looks like so you can judge whether an agency actually learned from it or just hid it.

Chatronix trusted us with their budget and we didn’t deliver the results we promised. That stings. But the methodology, the study itself, and the outreach infrastructure we built during that campaign became the foundation for everything that came after.

If you’re evaluating PR agencies, ask them about their failures. If they don’t have any, they’re either lying or haven’t done enough work to have learned anything useful yet.

Keep Reading

• The campaign that did work: 2,296 placements for Hockerty
• What is reactive PR and how we do it now
• How much does digital PR actually cost?

Presslei is a reactive digital PR agency based in Zurich. We run data driven campaigns for tech and B2B companies. If you want to talk about what a campaign would look like for your business, honest conversation included, get in touch.

Sources: Google Trends · ONS

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.

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“Research-driven PR campaigns work because they give journalists something they genuinely need: original data that supports the story they’re already trying to tell.”

— Salva Jovells, Presslei