Win/Loss Analysis
Analyze closed deals to identify winning patterns, loss reasons, competitive dynamics, and actionable sales process improvements.
You lost 12 deals last quarter and the CRM says 'lost to competitor' or 'no budget' — but those aren't real reasons. Win/loss analysis that digs into what actually happened reveals patterns your reps can't see from inside individual deals: pricing gaps, demo weaknesses, or competitors who win at a specific stage every time.
Who it's for: sales VPs diagnosing pipeline conversion issues, revenue operations analysts building win/loss dashboards, product marketing managers understanding competitive positioning, CROs presenting sales effectiveness analysis to the board, sales enablement leaders using loss patterns to improve training
Example
"Analyze our Q3 win/loss data for the enterprise segment" → Win/loss report: win rate trends by segment and deal size, top 5 loss reasons ranked by frequency and revenue impact, competitive win/loss breakdown by competitor, stage-by-stage conversion analysis showing where deals die, 6 pattern-based recommendations, and a competitive response playbook
New here? 3-minute setup guide → | Already set up? Copy the template below.
# Win/Loss Analysis
## Your Role
You are an expert sales operations analyst. Your job is to identify patterns in closed deals that reveal why deals are won or lost, competitive dynamics, and actionable process improvements.
## Core Principles
- Segment analysis by deal size, industry, and competitor
- Interviews reveal "why" — CRM codes only reveal "what"
- Present patterns, not individual rep performance
- Compare across time periods to identify trends
- Focus on actionable process changes, not blame
## Instructions
Produce: win pattern analysis, categorized loss reasons, competitive win/loss rates, sales process insights (cycle length, stakeholders, stage duration), segment-level analysis, and prioritized recommendations.
## Output Format
- **Win Patterns**: Attribute, frequency in wins vs. losses, correlation strength
- **Loss Categories**: Reason, frequency, percentage, preventability
- **Competitive**: Competitor, deals faced, win rate, common differentiators
- **Recommendations**: Change, expected impact, effort, priority
## Commands
- "Win/loss analysis" - Full analysis
- "Win patterns" - What winners have in common
- "Loss deep dive" - Categorized loss reasons
- "Competitive intel" - Head-to-head performance
What This Does
Analyzes won and lost deals to identify patterns — what winning deals have in common, why deals are lost, competitive win rates, and process improvements that increase close rates.
Quick Start
Step 1: Download the Template
Click Download above to get the CLAUDE.md file.
Step 2: Gather Deal Data
Compile CRM data, win/loss interview notes, and deal details for the analysis period.
Step 3: Start Using It
claude
Say: "Analyze our Q4 win/loss data. We closed 45 deals and lost 32. What patterns differentiate wins from losses?"
Analysis Framework
| Section | Content |
|---|---|
| Win Patterns | Common attributes of closed-won deals |
| Loss Reasons | Categorized reasons for lost deals |
| Competitive Analysis | Win rates against each competitor |
| Process Insights | Sales cycle, stakeholders, and stage patterns |
| Segment Analysis | Win rates by size, industry, use case |
| Recommendations | Process changes to improve close rates |
Tips
- Segment by deal size: Enterprise and SMB deals lose for different reasons
- Interview losses: CRM disposition codes tell you what; interviews tell you why
- Track competitive dynamics: Know your win rate against each competitor
- Time-box analysis: Compare quarter-over-quarter to spot trend changes
Commands
"Analyze win/loss data for [period]"
"What do our winning deals have in common?"
"Break down loss reasons by competitor"
"Recommend 3 process changes to improve close rates"
Troubleshooting
CRM data incomplete Say: "Flag deals with missing disposition codes. Analyze available data and note confidence level."
Too few deals for patterns Ask: "Extend the analysis period to 6 months for a larger sample."
Sales team pushback on findings Specify: "Present as deal-level patterns, not individual rep performance."