Skills RevOps

Win/loss evidence in support conversations

Formal win/loss programmes interview a small, self-selected slice of deals, usually months later, mediated by the account team's memory. Support conversations contain a much larger, contemporaneous, unmediated record of the same subject — customers naming competitors, describing what they cannot do, and explaining what they are switching to and why.

RevOpsRevenue signalAnalysisAny helpdeskRead-only
Installnpx rulebase-skills install cx-win-loss-from-support

When to use it

Reach for this when someone says any of these — they are the phrases the skill itself triggers on:

  • what competitors do customers mention
  • why do customers switch away
  • find feature gaps customers ask about

How it works

The method, in the order the skill runs it. The full procedure — tables, worked examples and the edge cases — is in the skill itself.

  1. What the sample actually is

    Three biases, all in the same direction.

  2. Four extractable signals

    1. Competitor mentions. Who is named, in what context, and how the volume trends. Context is the whole value — a competitor mentioned because the customer is migrating from them means something opposite to one mentioned as an alternative they are evaluating. Classify by context, not by count, or the analysis will report your strongest migration source as your biggest threat.

  3. The interpretation trap

    Competitor mention volume is not competitive threat. It tracks the competitor's marketing spend, their brand recognition, and how often their name comes up in normal conversation — not how often they beat you.

  4. Route the findings by owner

    The output splits four ways, and pushing it all to product wastes most of it: Product, Sales and marketing, Pricing, Support and knowledge.

Related skills

Free and open source, and vendor-neutral — it reads the conversations from whichever helpdesk you already run. Browse all 149 skills · connect your helpdesk over MCP · source on GitHub

Review every conversation. Act on what it finds.

AI for customer operations, built for financial services. Specialist agents chase every issue to resolution and every stalled customer to activation.

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