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“One customer saved five hours” can become “save five hours every week” surprisingly easily as a claim moves from a case study into a sales deck, then into an AI draft.
The wording becomes cleaner. The meaning changes.
The original statement describes one customer's experience. The new version sounds like a promise to every buyer. That difference matters even if both sentences look reasonable in isolation.
An approved-claims document gives your team a place to preserve those boundaries.
For each claim, record the approved wording, evidence, date, relevant audience or conditions and the wording that would overstate it. Include product limitations and the person who can approve a change.
ChatGPT can help build the first draft from existing material:
Create a draft approved-claims register from these product documents, case studies and research: [attach].
For each potential claim, include:
- Proposed wording.
- Exact supporting source and passage.
- Who or what the evidence covers.
- Important conditions and limitations.
- A stronger version the evidence would not justify.
Separate established product facts, individual customer outcomes and broader research findings. Mark unsupported claims for review instead of filling the gaps.
Then check this piece of copy against the register: [paste]. Highlight wording that changes the scope or certainty of the evidence.
Have the relevant owner approve the register before treating it as authoritative.
It will not guarantee every future draft is correct. It gives you something concrete to review against, and it makes it easier to catch the small wording changes that turn useful proof into an exaggerated promise.
Happy prompting!
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