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Market ResearchintermediatePro

Mine win/loss calls into market insights and messaging changes

Analyze sales calls, deal notes, and loss reasons to uncover why buyers choose, stall, or reject you, then turn findings into messaging updates.

What you will have

A market research workflow that converts real win/loss evidence into buyer themes, objection patterns, competitive insights, and messaging recommendations.

Setup time
3-5 hours
Time saved
8-12 hours per analysis cycle
Estimated cost
$100 to $600 per month
Tools used
6 tools

Why this works

Traditional market research often happens far away from the messy reality of deals. Win/loss calls contain the most useful language: buying triggers, perceived alternatives, risk concerns, budget objections, and trust gaps. This workflow uses AI to analyze actual sales evidence and turn it into messaging changes that reflect how buyers really decide.

Step-by-step workflow

Preview the workflow

The first 2 steps are open. Pro unlocks the remaining steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and implementation details.

1

Choose a focused deal sample

45 min

Select 10-20 recent deals from HubSpot: a mix of won, lost, stalled, and competitive deals. Keep the sample focused by segment, product line, region, or campaign source. Pull deal stage, ACV, competitor, loss reason, sales owner, closed date, and main buyer persona.

Output

A focused win/loss research sample with deal metadata and source links.

HubSpotAirtable
Pro tip

Do not mix enterprise strategic deals with self-serve SMB deals unless the research question requires it. Mixed samples produce vague insights.

2

Export the most relevant call evidence

1-2 hours

From Gong, pull call transcripts and summaries for discovery, demo, pricing, procurement, and late-stage objection calls. For each deal, select the two or three calls most likely to reveal buyer reasoning. Add transcript links, call type, attendees, and notes to Airtable.

Output

Curated call transcript set tied to each deal in the research sample.

GongAirtable
Pro tip

Late-stage calls usually reveal why the deal will be won or lost. Early discovery calls reveal the original pain, but not always the decision logic.

Pro workflow preview

Previewing 2 of 8 steps

Pro membership

Unlock the full workflow

Get the remaining 6 steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and weekly new workflows.

$9/month

Create a coding framework for buyer themes
Analyze calls deal by deal
Cluster themes across wins, losses, and stalls
Turn insights into messaging recommendations
Review findings with sales before publishing changes
Ship messaging changes and measure impact
See Pro plan
3Create a coding framework for buyer themes
Locked
4Analyze calls deal by deal
Locked
5Cluster themes across wins, losses, and stalls
Locked
6Turn insights into messaging recommendations
Locked
7Review findings with sales before publishing changes
Locked
8Ship messaging changes and measure impact
Locked

Expected results

Deals analyzed

10-20 deals

This sample size is practical for a focused analysis cycle and large enough to reveal repeated themes without creating research bloat.

Messaging changes identified

5-15 recommendations

The workflow converts call evidence into a prioritized backlog of asset, sales deck, battlecard, and website improvements.

Time saved

8-12 hours

AI accelerates transcript review, coding, clustering, and recommendation drafting while humans validate the final conclusions.

Research quality

Evidence-backed themes

Findings are tied to actual call language and CRM deal outcomes rather than internal opinions about why deals are won or lost.

Related workflows

Continue with workflows that share a similar GTM motion, category, or tool stack.