Episode 007

The trust problem with marketing claims

8 September, 2026
23.06
Group 1261153099
Becky Shepherd
Partnerships director Dragonfly AI
Group 1261153099 (1)
Tom Newbury
Senior account executive Dragonfly AI
Everrett Alatsis, customer & marketing insights executive
Everrett Alatsis
Customer & marketing insights executive
The trust problem with marketing claims
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The trust problem with marketing claims
Episode 007
Table of Content
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EXECUTIVE SUMMARY
  • A claim can be completely true – and still backfire. LifeLock's "one in four people experience identity theft" was accurate and research-backed. Consumers just heard it differently: "that's not me – I'll be the three out of four."
  • A claim score means nothing without a benchmark. Seventy-five percent believable, compared to what? Without competitor claims or category norms to measure against, a genuinely strong score and a "best of a mediocre bunch" score look identical.
  • Stacking claims doesn't add proof – it adds noise. Three strong stats in one message don't triple the impact; they just give consumers three competing reasons instead of one clear one. As Everett puts it: "one plus one plus one doesn't equal three, it just equals noise."
Everett Alatsis
Everett Alatsis
Customer & marketing insights executive
Transcript

Q: Can a marketing claim be true and believable, and still lead consumers to the wrong conclusion?

Everett: Yes, completely. At LifeLock, we had solid research behind "one in four people experience identity theft" – it was simple, clear, and believable, so we put it on our homepage and didn't look back. What we hadn't done was check how people were actually processing it. It took a third-party audit to find out that a meaningful number of consumers looked at that stat and thought, "one in four? That's not me – I'll be the three out of four." So instead of creating urgency, it did the opposite.

Q: How do you know if a claim's test score is actually good?

Everett: If a claim scores 75% unique and 85% believable, the question is: compared to what? It could be a genuinely strong claim, or simply the best of a bunch of mediocre ones. Where possible, I'll add in existing claims, competitor claims, or category norms, so there's something to measure against. I'd also test the claim on its own merit first – take the brand out of it entirely – then bring back the diagnostics on brand fit and differentiation. A score tells you how you performed. Context tells you whether it matters.

Q: How much proof is too much proof?

Everett: I've definitely seen that happen. A lot of companies fall into the trap of stacking claims – an email that says 90% agreed with this, 92% said that, 89% agreed with something else. Individually, each stat might carry weight, but put three together and you've created three independent, competing reasons rather than one strong one. One plus one plus one doesn't equal three, it just equals noise. I always say less is more – a single, focused claim beats a wall of stats and footnotes every time.

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