Analyzes sales conversations, call transcripts, and meeting notes to extract prospect intelligence for RFP responses -- including incumbent solutions, current processes, pain points, decision criteria, and stakeholder dynamics. Use this skill when a user wants to analyze call transcripts, meeting recordings, or conversational data to inform an RFP response. Also trigger when users say "analyze this call", "what did we learn from the meeting", "pull insights from Grain/Gong", "transcript analysis for the bid", "what are their pain points", or upload a transcript file. Works with MCP connections to Grain, Gong, or Chorus, or accepts raw transcripts, meeting notes, and conversation summaries.
Extracts actionable prospect intelligence from sales conversations, discovery calls, demo recordings, and meeting notes to inform stronger, more targeted RFP responses. Turns raw conversation data into structured intelligence about the prospect's current state, pain points, decision process, and what they actually care about.
The best RFP responses do not just answer the questions. They demonstrate understanding of the prospect's real situation -- the problems behind the requirements, the politics behind the evaluation criteria, the frustrations with their current approach. This intelligence lives in sales conversations, not in the RFP document itself.
If the user has an MCP connection to a conversational intelligence tool (Grain, Gong, Chorus, Clarity, Fireflies, etc.):
If no MCP connection is available, accept:
.txt files containing call transcripts.docx or .pdf transcript exportsIf full transcripts are not available:
Always ask the user what they have available. If they have an MCP connection, use it first since transcripts are richer than summaries.
Collect all available conversation data for the prospect. If using an MCP:
If using uploaded files, read all provided transcripts/notes.
Confirm with the user: "I found [X] calls/transcripts for [prospect]. I'll analyze these. Is there anything else I should include?"
Work through each conversation and extract intelligence across these categories:
Incumbent Solution & Current State
Pain Points & Frustrations
Decision Criteria & Priorities
Process & Timeline
Stakeholder Map
Competitive Intelligence
Organize the intelligence into a structured brief. Use direct quotes from transcripts wherever possible -- verbatim language from the prospect is more valuable than paraphrased summaries.
Output Structure:
## Prospect Intelligence Brief: [Company Name]
### Sources Analyzed
List of calls/transcripts reviewed with dates and participants
### Current State
- Incumbent solution and how they use it
- Current process workflow
- What is working (preserve these in your proposal)
- What is failing (address these directly)
### Pain Points (Ranked by Emphasis)
1. [Pain point] - Who mentioned it, how often, business impact
> "Direct quote from transcript"
2. [Pain point] ...
### The Trigger: Why Now?
What is driving the decision to change, and why now specifically
### Decision Criteria
What they said matters, in their words, mapped to likely evaluation weightings
### Stakeholder Map
| Name | Role | Priority | Sentiment | Key Quote |
For each key person involved in the decision
### Competitive Landscape (from Conversations)
What they revealed about other options they are considering
### RFP Response Recommendations
Based on this intelligence, specific recommendations for how to shape the RFP response:
- Lead with [X] because [stakeholder] emphasized it repeatedly
- Address [concern] directly because [context]
- Use their language: they say "[term]" not "[our term]"
- Avoid [topic] because [reason from conversations]
- Reference [their specific use case] rather than generic capabilities
After presenting the intelligence brief, ask the user:
"Do you want me to map these insights to specific sections of your RFP response? If you share the RFP questions or your draft response, I can show exactly where to incorporate this intelligence."
If they provide an RFP or draft:
.md file.md or .docx