win-loss-reasons

Synthesize win and loss reasons from sales transcripts, CRM notes, and deal evidence.

Updated Aug 28, 2026
One-click install
npx skills add https://github.com/nugiwabot/marketing-branding-selling-ads-skills --skill win-loss-reasons-nugiwabot
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: win-loss-reasons
Source: https://github.com/nugiwabot/marketing-branding-selling-ads-skills/tree/main/.agents/skills/win-loss-reasons
Command: npx skills add https://github.com/nugiwabot/marketing-branding-selling-ads-skills --skill win-loss-reasons-nugiwabot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Sales teams often misread why deals are won or lost, treating buyer-stated objections as proven causes and letting anecdotes drive strategy. This Skill separates stated reasons from evidence-backed patterns so decisions about positioning, pricing, and sales process rest on traceable deal evidence. ## Core Features & Use Cases - Evidence-graded analysis: Distinguishes buyer-stated reasons, observed evidence, patterns, inferences, and hypotheses across closed-won, closed-lost, and no-decision deals. - Competitor pattern analysis: Separates competitor involvement from competitor effectiveness without inventing claims about pricing, win rates, or product weaknesses. - Strategic feedback loop: Translates findings into labeled recommendations for positioning, offer, sales process, product, and channel decisions. - Use Case: After a quarter with 40 lost deals, feed the CRM notes and call transcripts into this Skill to produce a sourced table of loss reasons ranked by confidence, revealing that procurement delays—not pricing—drove most losses. ## Quick Start Analyze the attached sales call transcripts and CRM deal notes to identify the evidence-backed reasons we won and lost deals last quarter.

Frequently Asked Questions about win-loss-reasons

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze win-loss reasons from sales calls?

Gather sales call transcripts, CRM opportunity notes, and deal history, then capture each deal's outcome, stated reason, and observed evidence. Cluster equivalent reasons across deals and separate buyer statements from evidence-backed patterns before drawing conclusions.

What is the difference between a buyer-stated reason and a loss pattern?

A buyer-stated reason is what the buyer or CRM explicitly recorded, while a pattern is a recurring observation across multiple deals. A repeated stated reason shows recurrence but does not prove causality without supporting evidence.

Can win-loss analysis prove why a competitor won a deal?

A competitor named in a lost deal only proves involvement in the decision context. It does not prove the competitor won on price, product, or brand unless the transcript or deal evidence directly supports that conclusion.

What evidence sources are needed for win-loss analysis?

Useful sources include sales call and demo transcripts, CRM opportunity notes and stage history, deal desk or forecast notes, post-mortems, and customer feedback. The analysis works with whatever relevant evidence exists and flags data limitations.

Why is the most frequent objection not always the biggest problem?

Frequency does not equal causal importance. Deal value, stage, segment, fit, and evidence quality all affect weighting, so a rare objection in high-value deals may matter more than a common one in poor-fit deals.