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A Win/Loss Analysis Playbook reads every closed deal, decomposes the patterns behind wins and losses across segment and competitor, and turns those patterns into specific changes to qualification, pitch, and process.
The Challenge
When a deal is lost, the CRM disposition typically lands on "price", "timing", or "went with competitor". These labels are short, they make the close-out form go away, and they hide the actual story underneath. The same loss reason on 200 deals can mean 200 different problems.
Most teams that do win/loss work focus on losses. Wins get attributed to "great execution" without surfacing which sales activities, content interactions, or buying-side signals actually correlated with the outcome. The lessons from wins disappear with the next quarter.
Without aggregating across deals and joining CRM data with activity, content, and competitive intelligence, the structural patterns stay invisible. The same losses keep repeating because nobody has surfaced the systemic story.
How eyko Solves It
A Win/Loss Analysis Playbook reads closed-won and closed-lost deals, joins them with activity and content data, and surfaces the patterns that predict each outcome. The output is a ranked list of structural changes (qualification, pitch, competitive prep) that move win rate against the dimensions that matter most.
Win rate sits at 26%, down 4 points QoQ. Losses to Competitor X are concentrated in the mid-market segment (68% of competitive losses). Deals that included a technical evaluation step win at 1.8x the rate of deals that skipped one. Average discount on won deals is 11% versus 19% on lost deals, indicating that discounting is not buying win rate, it is just trading margin.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
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FAQ
Everything you need to know about Win Rate Drivers (Past 4 Quarters).
Win/Loss Analysis is an AI-driven analysis of closed-won and closed-lost deals that surfaces the structural patterns behind each outcome. The Playbook joins CRM disposition data with activity, content interaction, and competitive intelligence, then runs feature-importance analysis to identify which drivers move win rate. The output is a list of changes to qualification, pitch, and process ranked by expected win rate impact.
The Playbook reads from CRM (closed opportunities, stage history, dispositions), sales engagement platforms (activity logs, content interactions), conversation intelligence tools (call transcripts and notes), and any competitive intelligence sources you maintain. The richer the activity-level data, the more precisely the Playbook can attribute outcomes to specific drivers.
The Playbook clusters losses by named competitor and segment, then surfaces the patterns that distinguish each cluster: which content was sent, which competitive features came up in transcripts, which buyer roles were engaged, and what discounting was tried. The output is a per-competitor differentiation profile with the specific battlecard and prep changes that target the loss pattern.
Yes. The Playbook runs a feature-importance analysis across closed-won deals to identify which activities, stages, and content interactions are most strongly correlated with the outcome, controlling for segment and deal size so the result is not just a proxy for who the customer is. Activities that move win rate become recommended steps; activities that do not become candidates for removal from the standard motion.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
