Pipeline read you can trust
Assess every process step against defined criteria rather than optimistic self-reporting.
— Sales & Growth
Customer voice → churn signal monitor
Sentiment Analysis scores every row against the six things that make customers leave — Product, Support, Pricing, Onboarding, Reliability, Account management — only where each is mentioned.
- Sales & Growth
- Traceable reasoning
- Runs anywhere
3–4 weeks → ~40 minutes
For a full population, not a sample
No coding required
- Input
- CRM exports, deal notes or call records
- Output
- A scored view of each process step with reasons shown
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~3–4 weeks per run
— USE CASES
What people use Customer voice → churn signal monitor for
Patterns across the whole book
See what repeats across the end-to-end process instead of the loudest recent deal.
Action, not just insight
Each finding lands with a recommended next move and the evidence behind it.
What it works from
- CRM exports, deal notes or call records
- Your qualification criteria, ICP or scoring rules
What you get back
- A scored view of each process step with reasons shown
- A prioritised action list for the team
— HOW IT BEHAVES
How Customer voice → churn signal monitor produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Every row of the end-to-end process
Each row of your export is processed on the same basis, so no process step is skipped however long the table is.
The pattern charted
Movement across the end-to-end process is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings on the end-to-end process are written up as a document that reads like professional output, with each claim tied back to a process step.
Roll-up alongside process step-level detail
Detail rows are summarised into the grouped view of the end-to-end process without losing the underlying process steps.
Why this is expensive by hand
Reading the end-to-end process usually depends on what reps put in the CRM and what a leader remembers from calls. In practice it shows up as pipeline read you can trust: assess every process step against defined criteria rather than optimistic self-reporting. It is the kind of work that decides whether a recommendation survives scrutiny — and the kind that quietly eats 3–4 weeks of senior time whenever it comes round.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; a scored view of each process step with reasons shown comes out, alongside a prioritised action list for the team. What sits between input and output is the codified method: thresholds, sequencing and the points where a human confirms a call — all of it visible and editable in the Skill. The practical effect: 3–4 weeks of manual work becomes a ~40 minutes run, held to an identical standard on the tenth engagement as on the first.
Who it's for
- Revenue and commercial leaders
- Sales operations and enablement teams
- Customer success and account management leads
- Consultants advising on go-to-market
Run it in Skillsize — or export it anywhere
Customer voice → churn signal monitor exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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