# Conversion Copywriting and Voice of Customer > Conversion copywriting and voice-of-customer (VOC) research. Not prose craft — evidence gathering and message strategy for the copywriter or PM before the prose gets written. Covers VOC research sourc Parent: [Writing and Documentation](https://llms-explorer.com/tree/writing-and-documentation/) · 5 facets · 17 facts · page: https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/ ## Overview - Conversion copywriting and voice-of-customer (VOC) research. Not prose craft - evidence gathering and message strategy for the copywriter or PM before the prose gets written. Covers VOC research sources (customer reviews, support tickets, sales-call transcripts, Reddit and community threads, G2/Trustpilot, exit surveys); the they-say/we-say gap analysis (how customers describe the problem vs how the marketing team describes it); Jobs-to-be-Done message extraction (functional, emotional, and social JTBD from customer language); building a message hierarchy (primary claim, proof, objection handlers); post-purchase and "what almost stopped you" surveys to surface objection inventories; hypothesis-driven copy testing (what to A/B test - headline, value prop, CTA, lead, hero image - and why); Eugene Schwartz stages of awareness applied to VOC; the HiPPO ("highest-paid person's opinion") problem in copy decisions. Route prose framework questions (AIDA, PAS, CTA wording) to content-and-marketing-writing; A/B test statistics to da-analytical-methods; persuasion theory to applied-psychology. — [source](https://llms-explorer.com/sources/mdb-context-hub/conversion-copywriting-and-voice-of-customer/#overview) ## Where this helps - Before writing any new landing page, ad, or email, when the team's internal language for a problem doesn't match how customers actually describe it in their own words. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Deciding what to A/B test next — headline, value prop, CTA, lead, hero image — based on evidence from customer language rather than internal opinion or the highest-paid person's preference. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Building a message hierarchy for a launch or campaign where the primary claim, its proof, and the objections it needs to preempt all need to trace back to real customer evidence. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Diagnosing why existing copy underperforms by checking whether it's still targeting an earlier Schwartz awareness stage than the actual audience has reached. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* ## How to apply this - Pull raw customer language from reviews, support tickets, sales-call transcripts, and community threads such as Reddit, G2, and Trustpilot, and quote it directly rather than paraphrasing, to preserve the they-say voice. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Run a they-say/we-say gap analysis by placing the company's internal description of the problem next to the customer's own words side by side, and rewrite toward the customer's phrasing where they diverge. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Send a post-purchase what-almost-stopped-you survey to build an objection inventory the message hierarchy's proof and objection-handler sections can directly answer. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Extract functional, emotional, and social Jobs-to-be-Done from customer language separately, since a message that only answers the functional job often misses the emotional or social reason someone actually converts. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* ## Antipatterns - Skipping VOC research and writing copy from internal assumptions about what customers want, which is exactly the they-say/we-say gap this discipline exists to close. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Letting the highest-paid person's opinion override customer-language evidence when deciding what to test or ship, defeating the purpose of gathering the evidence in the first place. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Treating VOC research as a one-time exercise instead of an ongoing input, when customer language and the objections customers raise shift as the product and market evolve. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Confusing this discipline with prose-writing craft itself — VOC research supplies the evidence and message strategy, but frameworks like AIDA or PAS and sentence-level writing are a separate step. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* ## Limitations - VOC research surfaces what customers say, not necessarily what statistically drives conversion — a hypothesis generated this way still needs an actual A/B test to confirm it moves the metric. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - Sources like reviews and support tickets are self-selected, which can skew toward the most satisfied or most frustrated customers rather than the median buyer. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - A message hierarchy built from VOC evidence for one audience segment or awareness stage may not transfer cleanly to a different segment or a more or less sophisticated market. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* - This discipline explicitly does not cover the statistics of interpreting an A/B test result or the underlying persuasion theory — those live in separate, dedicated references. — [source](https://llms-explorer.com/tree/conversion-copywriting-and-voice-of-customer/) *(AI-suggested, synthesized from this pack's existing facts — not extracted from a source document.)* ## Context files - [Conversion Copywriting and Voice of Customer](https://llms-explorer.com/downloads/sources/mdb-context-hub/conversion-copywriting-and-voice-of-customer.md)