# Modern Win-Loss Analysis

Purpose: Use this file when Compete must explain why deals were won or lost, identify repeated decision factors, or feed market learning back into strategy.

## Contents

- core pillars
- evidence hierarchy
- benchmarks
- interview techniques
- hybrid data model
- feedback loop

## Four Pillars

| Pillar | Meaning | Effect |
|---|---|---|
| direct buyer feedback | talk to actual decision-makers | richer than CRM fields alone |
| cross-functional design | sales, marketing, and product shape the study | reusable insights across teams |
| continuous program | not a one-off project | stronger ROI over time |
| organizational buy-in | executive sponsorship and adoption | insights influence multiple teams |

Program effectiveness signals:
- continuous programs: `85%` positive ROI
- project-based efforts: `55%` positive ROI

## Evidence Hierarchy

| Tier | Source |
|---|---|
| Highest | third-party buyer interviews |
| High | direct buyer interviews by your team |
| Medium | target surveys |
| Low | CRM competitor fields and seller recollection |

Rule:
- use CRM as supporting evidence, not as the sole explanation for a win or loss

## Benchmarks

| Metric | Signal |
|---|---|
| teams reporting win-rate improvement | `63%` |
| programs running `2+ years` with improvement | `84%` |
| higher chance of `10%+` improvement with third-party interviews | `38%` |
| executive visibility | `98%` |
| healthy B2B win-rate band | `20-35%` |
| strong performance | `35%+` |

## Interview Techniques

### Five Whys

Use this to turn surface reasons into root decision drivers.

```text
Why did they choose the competitor?
-> Because the feature set felt stronger.
-> Which feature mattered most?
-> Dashboard customization.
-> Why did that matter?
-> It automated weekly executive reporting.
-> Root need: reporting automation.
```

### Laddering

Move from feature -> consequence -> personal value.

| Level | Question | Example answer |
|---|---|---|
| Attribute | What mattered? | API flexibility |
| Consequence | What did that enable? | easier integration |
| Value | Why did that matter personally? | better team productivity and recognition |

## Hybrid Win-Loss Model

Use a mixed evidence approach:

- buyer interviews for depth
- surveys for breadth
- CRM for structure and coverage
- AI conversation analysis for scale and pattern detection

Pattern rule:
- repeated feedback `3` times or more requires action planning

## Decision Factor Template

```markdown
## Win/Loss Decision Factor Analysis

| Factor | Weight | Us | Competitor |
|---|---:|---:|---:|
| Price / TCO | ___% | | |
| Feature fit | ___% | | |
| UX / Ease of Use | ___% | | |
| Support | ___% | | |
| Integration / API | ___% | | |
| Brand / Trust | ___% | | |
| Security | ___% | | |
| Sales Experience | ___% | | |

### Qualitative Insights
- Final decision-maker: [...]
- Evaluation period: [...]
- Competitors considered: [...]
- Root need from Five Whys: [...]
- Value insight from Laddering: [...]
```

## Feedback Loop

Win/loss findings should feed:

- battle card updates
- Spark feature ideation
- pricing and packaging review
- Growth messaging adjustments
- SHARPEN calibration

Mapping to Compete:

| Compete phase | Win/loss contribution |
|---|---|
| `MAP` | reveals unknown competitors or substitutes |
| `ANALYZE` | quantifies real decision factors |
| `DIFFERENTIATE` | strengthens strategic positioning |
| `SHARPEN` | validates prediction quality against real outcomes |
