win-loss-intelligence

Win/Loss Intelligence

Explain why the company wins or loses, for whom, against what alternatives, under which conditions, and what the evidence suggests should be reviewed. Produce evidence and implications, not revised positioning or sales copy.

Context research handoffs

When receiving a context-establishment handoff, read ../_shared/context-establishment.md. Reuse its question, scope, source/finding IDs, approved context/version, GAP IDs and completion criteria. Analyze only your owned domain; return provenance-bearing findings, opposing evidence, limitations, completion status and unapproved implications to product-marketing-context. Use decision-specific evidence readiness; approval is separate. A hold affects only its decision. Do not write canon or automatically save chained results into bootstrap context. Standalone artifacts retain their existing format and may attach the shared return. Preserve IDs and status without duplicating studies.

Before analysis

• Read ../_shared/evidence-gaps.md, ../_shared/ssot-consumption.md, and ../_shared/segment-selection.md when comparing segments.
• Use applicable SSOT as a comparison point, never as a file to edit. Record relevant canon version/files and route contradictions through ssot-context-loop for human review.
• Inventory available closed-won/lost interviews, CRM reason codes, calls, AE notes, opportunity data, competitor evidence, and research. Record date range, inclusion rules, counts, missingness, and known selection bias.
• Distinguish buyer-reported reason, seller-reported reason, directly observed evidence, and inferred hypothesis. CRM loss codes are seller-entered signals, not buyer truth.

Analysis

1. Define the question, cohort, and denominator. Separate closed outcomes from open or disqualified opportunities.
2. Code supported themes across segment, persona, company size, use case, competitor/alternative, deal size, funnel stage, geography, capability, price, implementation, integration, security/compliance, procurement, timing, and status quo. Leave unsupported dimensions unscored.
3. Separate frequency, severity/materiality, and confidence. Show counts and denominators where available. A small or biased sample cannot establish a rate or broad pattern.
4. Identify win/loss drivers, competitor and segment patterns, product, positioning, messaging, proof, pricing/packaging, sales-process issues, false assumptions, and unresolved questions only where evidence supports them. Do not classify every loss as competitive.
5. Include representative source-linked evidence. Use verbatim quotes only when present in actual source material. Preserve conflicting reports.
6. Route implications to the owner. Do not automatically rewrite any artifact.

Required output

1. Inputs and assumptions, using shared evidence labels.
2. Executive summary and analysis question.
3. Evidence base: sample, outcome counts, period, sources, exclusions, bias, and limitations.
4. Win themes and loss themes, each with frequency, severity, confidence, and representative evidence where available.
5. Supported breakdowns by relevant segment/persona/alternative/stage.
6. Implications and handoffs, with unresolved questions and ranked evidence gaps. Suggested routes: Voice of Customer to customer-research, recurring objections to objection-intelligence, competitive evidence to competitor-profiling, positioning to positioning-strategy, messaging to messaging-framework, proof gaps to the evidence owner, price to pricing-strategy, and sales process to sales-enablement or revops.

Safety and quality checks

• Never invent reasons, quotes, counts, rates, outcomes, or competitor claims.
• Mark missing buyer evidence as Gap; never promote seller interpretation to customer truth. Keep Sourced / Assumed / Gap labels; identify derivations as interpretation with formulas/source inputs, not a fourth label.
• Do not imply causality from association or attribute a win/loss to one factor when evidence supports multiple conditions.
• New findings may request SSOT review. Only ssot-context-loop manages canonical changes and required human approval.
• Internal analysis normally does not go to messaging-consistency-audit.
• Output quality: output-quality-check can verify cohort/denominators, source/report type, frequency/severity/confidence separation, quotes, limitations, supported breakdowns, explicit handoffs, and no silent canon change.

Related skills

customer-research (research design and VoC), objection-intelligence, competitor-profiling, positioning-strategy, messaging-framework, pricing-strategy, sales-enablement, revops, ssot-context-loop, output-quality-check.