Turn customer calls into a positioning and messaging refresh

Start by choosing 8-12 calls that represent different deal outcomes and lifecycle stages, not only the happiest customers. Include closed-won deals, closed-lost deals, active opportunities, onboarding calls, renewal discussions, and at least one call where the buyer pushed back hard. Export the transcript or call summary from Gong and capture metadata in Airtable: account segment, persona, company size, deal stage, outcome, product area, competitor mentioned, and call date. Mark whether each transcript is approved for internal analysis and whether any customer names or sensitive implementation details need redaction. The goal is to create a research sample that reflects the market conversation, not a highlight reel.

Before asking AI to summarize anything, define what you want extracted from the calls. Create fields in Airtable for buyer words, pain theme, desired outcome, switching trigger, objection, competitor comparison, confusing product language, proof requested, emotional intensity, evidence link, and confidence. Then open Claude, paste the prompt below, and use your sample metadata plus the schema fields as the input so Claude can refine the extraction rules before analysis starts. Copy the output from Claude back into Airtable or Google Docs as the approved extraction schema and redaction rules for the rest of the workflow. QA check: every field should have a clear definition, an example value, and a rule for when the field should be left blank.

Create a call-analysis extraction schema for a positioning refresh.

Current product category:
{{product_category}}

Target segments:
{{target_segments}}

Current positioning:
{{current_positioning}}

Sensitive details to avoid exposing:
{{privacy_rules}}

Create fields for:
1. Buyer words
2. Pain theme
3. Desired outcome
4. Switching trigger
5. Objection
6. Competitor comparison
7. Confusing product language
8. Proof requested
9. Persona and segment
10. Evidence link
11. Confidence score
12. PMM interpretation

Also create rules for what should be redacted before analysis.

Use Gong trackers or search to find moments where buyers discuss pain, urgency, budget, alternatives, implementation risk, proof, and decision criteria. Export the selected excerpts with transcript links and metadata, then open Claude and paste the prompt below with the excerpts attached in batches. Ask Claude to extract exact phrases first, then group them into themes only after the evidence is captured. Copy the output into Airtable with the source call, persona, deal outcome, supporting quote, and confidence score. Do not let the model rewrite rough customer language into polished marketing copy at this stage.

Analyze these call excerpts for positioning evidence.

Call excerpts and metadata:
{{call_excerpts_with_metadata}}

Extraction schema:
{{extraction_schema}}

Current positioning:
{{current_positioning}}

For each excerpt, return:
1. Exact buyer words worth preserving
2. Pain or outcome theme
3. Buying trigger or urgency signal
4. Objection or risk concern
5. Competitor or alternative mentioned
6. Confusing product language, if any
7. Proof the buyer asked for
8. Persona and segment relevance
9. Evidence strength from 1-5
10. Positioning implication

Do not invent themes. If the evidence is weak, mark it as weak.

Move the extracted themes into Google Sheets and score them using frequency, deal importance, target persona relevance, urgency, revenue relevance, proof availability, differentiation potential, and whether your product can credibly own the message. Open Claude and paste the prompt below only after the first human scoring pass, using the sheet export as input. Ask Claude to challenge weak scores, identify unsupported themes, and flag themes that look emotionally strong but commercially narrow. Copy the output from Claude back into the sheet as reviewer notes instead of automatically overwriting the scores. The PMM should select the top themes by balancing repeated evidence with strategic relevance.

Score these positioning themes using the criteria below.

Themes and evidence:
{{themes_and_evidence}}

Scoring criteria:
{{scoring_criteria}}

Business priorities:
{{business_priorities}}

For each theme, return:
1. Frequency score
2. Deal importance score
3. Persona relevance score
4. Urgency score
5. Differentiation potential
6. Proof availability
7. Credibility risk
8. Recommended priority: high, medium, low, or reject
9. Evidence note
10. Reviewer question to resolve

Be conservative. Do not over-rank a theme based on one quote.

Open Claude and paste the prompt below with the scored theme table, current positioning, product strengths, and links or excerpts that support each theme. Ask it to draft a Google Docs memo, but require every recommendation to cite supporting call evidence. Copy the output into Google Docs and structure it around what current messaging misses, revised audience pain, 3-5 message pillars, proof points needed, objection language, competitor framing, website copy recommendations, and sales narrative recommendations. Label anything without enough evidence as a hypothesis rather than a conclusion. The memo should be written for decision-making, not as a long research report.

Create a positioning refresh memo from these customer call insights.

Scored theme analysis:
{{scored_theme_analysis}}

Current positioning:
{{current_positioning}}

Product strengths:
{{product_strengths}}

Target segments:
{{target_segments}}

Supporting call evidence:
{{supporting_call_evidence}}

Create:
1. Executive summary
2. What current messaging misses
3. Revised audience pain statement
4. 3-5 message pillars with evidence
5. Proof points needed
6. Objection handling language
7. Competitor framing
8. Website copy recommendations
9. Sales narrative recommendations
10. Messaging risks and claims to avoid
11. Open questions for PMM, sales, or product review

Mark weakly supported ideas as hypotheses, not conclusions.

Share the memo with sales, customer success, support, and product using a focused review checklist. Ask reviewers whether the themes match live conversations, which phrases reps would actually use, which objections are missing, and where the memo overgeneralizes. Capture every comment in Airtable with reviewer, decision, evidence requested, and follow-up owner. Do not allow the review to become a full brand rewrite; this is a reality check on buyer evidence and commercial usefulness. The PMM should make final decisions and document which themes are approved, rejected, or marked for testing.

Convert the approved pillars into operational assets instead of leaving them in a strategy memo. Open Claude and paste the prompt below with the approved message pillars, rejected themes, buyer phrases, proof points, and usage rules from the PMM review. Ask for website hero options, product page section copy, sales talk tracks, objection responses, email snippets, ad angles, and FAQ answers. Copy the usable drafts into Airtable or Google Docs with the approved theme, source evidence, owner, status, and channel usage notes. Start rollout with the highest-impact surface, such as the main product page or the most-used sales deck, before changing every channel.

Turn these approved positioning themes into usable message assets.

Approved themes:
{{approved_themes}}

Buyer language to preserve:
{{buyer_language}}

Proof points:
{{proof_points}}

Brand voice:
{{brand_voice}}

Create:
1. Website hero options
2. Product page section copy
3. Sales talk track
4. Objection responses
5. Email snippets
6. Ad angle options
7. FAQ answers
8. Claims that need final review

Use customer language naturally, but do not copy sensitive or private details.

After rollout, monitor whether the approved messaging changes buyer behavior. Pull Gong tracker notes, sales feedback, reply quality, demo conversion, objection frequency, website conversion, and qualitative comments into a short measurement sheet. Open Claude and paste the prompt below with the before-and-after signals, then ask it to summarize what improved, what created confusion, and what needs another test. Copy the summary back into the positioning memo as a dated learning note and mark which messages should be kept, revised, or retired. Look for signal quality, not only volume: better questions, clearer fit, fewer repeated objections, or faster buyer understanding.

Analyze whether the new positioning improved buyer conversations.

Before-and-after call or funnel data:
{{before_after_data}}

Approved message assets:
{{approved_message_assets}}

Sales feedback:
{{sales_feedback}}

Website or email performance:
{{performance_data}}

Return:
1. Signals that improved
2. Signals that declined
3. Objections that changed
4. Buyer phrases that repeated after rollout
5. Assets that appear to be working
6. Assets that need revision
7. Recommended next test
8. Positioning memo updates

Focus on buyer response, not internal preference.