VOICE OF CUSTOMER
Hear the buyer.
Then write the page.
Turn recorded conversations into evidence your team can use. Keep the buyer’s words, separate interpretation, and bring their priorities into your messaging and qualification rules.
- Discipline
- Buyer research
- Context
- US executive search firm
ILLUSTRATIVE BUYER LANGUAGE
From a sales conversation to a traceable piece of evidence
The calls were recorded. Nothing was done with them.
Sales calls were recorded, and nothing was done with them. Messaging on the site and in outreach was built on what the team believed buyers cared about, and the team's belief was mostly right and entirely unverified. The calls held the buyers' own words for what was broken, what they wanted, what they were afraid of, and what had convinced them, and nobody had gone in to get them.
The task: extract what buyers said, in their words, from every recorded call. Keep only what a buyer actually said, code it so sales can find the right evidence at the right moment, and use it to rebuild the ICP on evidence instead of assumption.
Six steps from a recording to a fit weight.
Extraction, two tiers, removal with a reason for every row, coding on five frameworks, a playbook for sales, and an ICP the scoring engine runs on. Not one quote appears on this page.
Extraction
A pipeline that reads call transcripts and pulls candidate quotes.
Two-tier filtering
A human-curated set treated as trusted, and a larger AI-filtered set that gets re-filtered rather than trusted. The two overlapped almost completely, so duplicates were collapsed with the curated version winning.
Removal with reasons
Anything that wasn't a buyer speaking came out, and every removal got a disposition: third-person write-ups, vendor marketing language, filler and logistics, ambiguous speaker. Seller inferences, things the firm's own people said about buyers, went into a separate bucket rather than the bin, because they're useful and they're not the same thing as a buyer's words.
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The audit, as it was written down. Every row in is accounted for.
# The source audit, 21 April 2026. Every row in is accounted for. Total rows in (both files) 638 tier_a_manual, human-curated 109 tier_b_ai, AI-filtered 529 Cross-file duplicates (manual reappears in AI) 109 Within-AI-file duplicates 5 Removed, third-person write-ups 8 Removed, vendor marketing copy 14 Removed, filler and logistics 30 Removed, ambiguous speaker 4 Seller-inferred, kept separately 101 Unique retained buyer-voice quotes 367
Coding
Five established frameworks, applied in sequence: hierarchical voice-of-customer coding into primary and secondary themes, six-phase thematic analysis, the jobs-to-be-done forces of progress (push, pull, anxiety, habit), category entry points for triggers, and evaluation criteria in the customer's own words. Each quote carries its force, its funnel moment, its content type, its themes, its emotional register, a confidence grade, and a quotability score.
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What every quote carries. The quotes themselves are not on this page and never will be.
# One row per quote in the bank. Every quote carries all of these. quote_id stable id verbatim_quote the buyer's words, unedited. Never leaves the firm. source_file tier_a_manual or tier_b_ai evidence_confidence how sure we are it is a buyer speaking forces_tags PUSH, PULL, ANXIETY, HABIT, in any combination funnel_moment where in the decision it was said content_type CRITERION, TRIGGER, ATTRIBUTION, COMPARISON, EMOTION primary_theme one of 23 secondary_theme one of 153, under its primary emotional_register how it was said likely_moments where sales could use it quotability_score how well it stands on its own
The playbook
The bank organised so sales can locate evidence by moment: what's broken, what they want, what they fear, what keeps them where they are, what triggered the search, how they evaluate, and what they say worked afterwards. Plus a collaborative section for sales to log what landed and what fell flat.
The ICP
Rebuilt from the bank as an evidence-graded classification. Those definitions are the title, revenue, industry and geography weights in the scoring engine, which is how one piece of work ends up running inside another.
Every row in, accounted for.
Snapshot: 21 April 2026. These are corpus sizes, not business volumes, so the counts stay.
The playbook to sales. The ICP into the engine.
Sales gets the bank organised by moment and a section to write back into. The ICP definitions become the title, revenue, industry and geography weights in the scoring engine. Stack: Fathom, Claude Code, Excel, Markdown. Built with Amr: the coding and the bank were the two of us; the extraction pipeline, the ICP and everything downstream is mine.
Any firm that records its calls and hasn't read them has this sitting there. Getting it out is a pipeline. Deciding what it means is the work.
What’s getting in the waySpecific examples from your public website.
What it means for the buyerWhy each issue is worth your attention.
What I would fix firstA clear order of priorities for you or your team.
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