Win-Loss Provenance and Practice-Based Rules

Externally sourced

• B2B average win rate 19-21% (Ebsta x Pavilion GTM Benchmarks, 2025 edition; 655K opportunities, $48B pipeline; checked September 2026, still the latest full dataset). Used only to size the unexamined-decision pool, not to predict program impact.

Deliberately excluded

Vendor-published claims of the form "win-loss programs lift win rates by X%" circulate widely without published methodology and were excluded under this library's benchmark standard. The divergence between CRM loss fields and interviewed loss causes is likewise reported across win-loss vendors and practitioners but lacks a citable controlled dataset; the skill states the mechanism (attribution incentive, single-cause dropdowns) rather than a fabricated percentage.

Practice-based rules (validate against your own program)

• The 2-6 week interview window (post-sting, pre-revisionism).
• The neutral-interviewer rule and its rationale (buyers soften the truth to the person they rejected).
• The one-week transcript-mining SLA per decided deal.
• Weighted multi-driver coding over single-cause fields.
• The both-outcomes sampling rule, and win interviews as the differentiator truth source.
• The quarterly cross-functional readout with quote-anchored findings.
• The customer arena lane: format lineage is the lean service-management klantarena (group session, customers talking, cross-functional team listening); composition (5-8, mixed including a skeptic, segment-pure), the listening rule, the chronological journey spine, the product-or-process double tag, and the 1-2 per segment per year cadence are practice-based operating rules from running these sessions in B2B settings.

After two quarters, the program generates its own evidence: compare interviewed-cohort loss causes against CRM fields for the same deals and keep the divergence table as your local proof.