Messaging Framework From Customer Language
Four documents and three sheets that count your customers' words against your company's, then put a numbered verbatim behind every line.
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Language Frequency Analysis
Their word against ours, counted
| Concept | What customers say | Uses | What we say | Their uses |
|---|---|---|---|---|
| The core problem | flying blind on stock | 31 | real-time inventory visibility | 0 |
| What good looks like | know what we actually have | 27 | single source of truth | 0 |
| The blocking constraint | we are not ripping out the ERP | 14 | integration-friendly architecture | 0 |
| The finance friction | finance does not believe our number | 9 | auditability | 1 |
| The loss event | shrinkage | 7 | inventory variance | 2 |
| Improvement | no customer term found | 0 | optimise | 1 |
The line that ends the argument
Customers said “single source of truth” zero times across forty-six sources. The messaging document it replaced used it four times, and the homepage still uses it twice.
Two verdicts nobody expects
Keep the jargon. “Shrinkage” survives at seven uses because customers genuinely say it. Replacing it with plain language would be an error the count already ruled out.
Make no claim. Speed to value has three mentions, two of them negative. The framework says nothing about it, and says so in writing.
Every count is split by source type and marked for whether it was unprompted, because in a sales call the rep speaks first.
Larkfield's messaging document says "unified inventory intelligence platform" and "single source of truth". Across forty-six sources, thirty sales calls, eight interviews, six months of support tickets and eight public reviews, customers said "single source of truth" zero times. They said "we are flying blind" or a close variant thirty-one times, nine of them using that exact phrase. Both wordings were available to whoever wrote the document. Only one of them came from a transcript.
This is why messaging arguments do not resolve. Two people argue from taste, taste has no tiebreaker, and the more senior preference wins. A count has a tiebreaker. Zero uses in forty-six sources against thirty-one is not a matter of opinion, and nobody disputes it without reading the transcripts, which nobody does. So the frequency sheet is filled before the framework, because a framework written first gets defended with evidence found afterwards.
Then the words go somewhere public, and a customer quote on a page is an endorsement under 16 CFR Part 255. An excerpt has to fairly reflect what was said, and a user testimonial rests on somebody who still is one. So every verbatim here carries its full surrounding passage rather than the pull quote, its consent scope by surface, and the date its user status was last confirmed. It installs into the marketing workspace beside the Search Console keyword map and the rest of the template library.
What's in the pack
Language Frequency Analysis
Their term against yours with counts split by source type, marked for whether each use was unprompted, and a verdict per concept.
Claim to Evidence Map
One row per claim per surface, with a status that includes remove, so unsourced copy comes off live pages rather than staying.
Proof Point Register
Every verbatim with its full surrounding passage, consent scoped by surface, and the date the speaker's user status was last confirmed.
Messaging Framework
Claims ordered by count rather than by preference, each carrying verbatim numbers, with the old wording and its zero beside it.
Voice of Customer Appendix
The passages at length, grouped by what they evidence, plus a written note on every claim the corpus could not support.
Verbatim Usage Standard
The four checks before a quote goes public, built on what the FTC's endorsement guides actually require.
Rollout Note
What to present in what order, what each team changes on Monday, and the answers to the four objections you will get. Route anything sales keeps hearing into the objection library instead of drafting a one-off answer here. Before the rollout meeting, run the headline claim through a message test rather than trusting whichever version the room prefers.
How to use it
- 1
Open in River, or take it blank
Open the pack in River and send your transcripts, or download the Word documents and CSV sheets and count by hand.
- 2
Send whatever you have
Sales calls, interviews, a ticket export, your own public reviews, lost-deal notes. Six transcripts produce a real finding.
- 3
Read the widest gap
Two numbers: how often customers used their phrase, and how often they used yours. That comparison is the whole argument.
- 4
Trace what is already live
Every claim on your homepage and in your deck gets a status. Most teams find one nobody can source and one quote from a churned customer.
Frequently asked questions
Is this template free?
Yes, with no account, no card and no email gate on the download. Edit with AI is the optional half: River reads your transcripts, runs the counts, and fills the framework with verbatim numbers behind each line. Every pack sits in the template library.
How many transcripts do I need?
Six sales calls produce a finding worth acting on. Forty produce one nobody argues with. The document you are replacing was almost certainly built on none, so the comparison is not against perfect research, it is against a workshop.
What if I have no call recordings at all?
Your corpus exists anyway. Public reviews of your own product are unprompted and quotable. Support tickets are the most honest source you have. Lost-deal notes count too, and re-reading those rather than trusting the loss reason field is where the positioning pack starts. Begin with whichever you can reach today.
Why keep jargon customers use?
Because the test is the count, not the plainness. The worked example keeps "shrinkage" at seven uses because customers genuinely say it. Replacing a customer's own word with a simpler one you invented is the same error as the original, in the other direction.
Why does a template care about FTC guides?
Because the point of this pack is putting customer words in public, and a quote on a page is an endorsement. The guides require that an excerpt fairly reflect what was said and that a user endorsement rest on somebody who was, and still is, a real user.
Won't this just produce dumbed-down copy?
It produces longer copy, more often than shorter. The worked example's problem statement is twice the length of the phrase it replaced, because a sentence the reader recognises as their own situation beats a compressed one they have to translate. Take the counted language into a homepage rewrite with a claim-to-proof map next.
What does Edit with AI actually do?
It signs you up, installs this pack as a private workspace, and starts counting. Send the transcripts and your current messaging document, and the widest gap between the two comes back with a full verbatim passage beside it.
Find out how often customers say your headline
Take the Word documents and CSV sheets blank, or open this exact pack in River and send it six sales call transcripts.
Edit with AI