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GTM workflow

Meeting notes to icp template

Turn customer meetings into ICP segments, qualification signals, fit scores, and evidence-backed lead-scoring records.

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Kollab reads meeting audio, transcripts, and existing account context, then updates a structured ICP database with buyer roles, pain patterns, buying triggers, disqualification signals, and fit scores.

Use it when your team needs to learn which customers are a real fit across many conversations, not just follow up on one deal.

How it works

  1. 01

    Read meeting evidence

    Kollab reads recordings, transcripts, existing account records, and your current ICP hypothesis.

  2. 02

    Extract fit signals

    The agent pulls Buyer Role, Pain Point, Buying Trigger, Qualification Signal, Disqualification Signal, and Evidence Quote.

  3. 03

    Update the database

    Existing accounts and segments are updated with Fit Score, Confidence, Review Status, and Data Enrichment Needed.

  4. 04

    Shape GTM next steps

    Kollab produces qualification questions, poor-fit filters, and the next experiment for sales or growth.

Starter prompt

Build or update an ICP and lead-scoring database from these meeting notes.

Inputs:
- Meeting recordings or transcripts: [links or uploads]
- Existing account list: [database link or CSV]
- Product / offer: [what we sell]
- Target market hypothesis: [current ICP assumption]
- ICP database: [Notion / Buildin database link; if it does not exist, create "ICP and Lead Scoring"]

Read and update the Notion / Buildin database. If the database does not exist, create it with these fields:
- Account
- Segment
- Industry
- Company Size
- Buyer Role
- Pain Point
- Buying Trigger
- Qualification Signal
- Disqualification Signal
- Data Enrichment Needed
- Fit Score
- Next GTM Action
- Evidence Quote
- Source Meeting
- Confidence
- Review Status

Please:
1. Transcribe the meetings when audio is provided and link every record back to the Source Meeting.
2. Extract ICP signals from evidence only: buyer role, urgency, team size, budget cues, workflow pain, existing tools, buying trigger, and reason to disqualify.
3. Cluster accounts into segments and explain why each segment looks promising or weak.
4. Update existing ICP records instead of creating duplicates when the same segment or account already exists.
5. Create one Fit Score per account or segment, with Evidence Quotes and Confidence.
6. Mark weak evidence as Needs Review and list Data Enrichment Needed before changing the ICP.
7. End with a GTM summary: best-fit segment, poor-fit segment, sales qualification questions, and next experiment.
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