mardab96 Proposal Win Loss Review
Use the shared quality bar in ../references/output-standard.md and ../references/skill-design-principles.md when those files are available.
Use this skill when
- the user shares lead source, CRM stage, sales note, form, landing page or campaign data tied to proposal win loss review.
- the next decision could change targeting, qualification, scoring, follow-up, sales handoff or budget.
- lead volume looks acceptable but SQL, opportunity, closed-won, rejection or response-speed data raises doubt.
Do not use this skill for broad lead-generation advice without source, CRM, sales or qualification evidence. Use it when a real B2B lead quality decision is on the table.
Required input
- business model, ICP, offer, ACV or deal value range, sales cycle and main conversion goal.
- ad, landing page, lead form, CRM, call note, email or campaign data relevant to this diagnostic.
- time window, traffic source, lead volume and downstream outcomes where available.
- what decision the user is trying to make next: create, fix, scale, pause, brief sales or investigate.
- If an input is missing, continue with a clearly marked assumption instead of inventing data.
Analysis workflow
- Collect won/lost proposal notes, source, segment, deal size, competitor, objections and close reason.
- Cluster win/loss reasons into fit, pain, pricing, authority, timing, proof, implementation, competitor and trust.
- Map repeated loss reasons back to lead source, ad promise, page promise and qualification step.
- Identify which upstream messages attract deals you can actually win.
- Recommend targeting, proof, offer, qualification or sales collateral changes.
Decision rules
- If the data does not connect to revenue, pipeline, qualified leads or conversion quality, label the recommendation as a hypothesis.
- If platform metrics and downstream data disagree, trust the downstream source for business quality and platform data for delivery mechanics.
- If the issue could be tracking, offer, audience, page or follow-up, do not collapse it into one cause without evidence.
- Do not recommend more budget until lead quality, follow-up and tracking confidence are separated.
Output format
| Finding | Evidence | Lead quality impact | Recommended action | Confidence |
|---|---|---|---|---|
| Specific diagnostic claim | Data, screenshot, report, note or missing-data marker | Business or signal consequence | Smallest useful next step and owner | High / Medium / Low |
End with:
Decision:fix / test / monitor / ask for data / do not act yetApproval needed:yes/no and what would change if approvedMissing data:only the inputs that would materially change the recommendation
Practical example
User: "Here are CRM stages, source data and sales notes for proposal win loss review. What should we change before the next campaign move?"
Assistant should: find the pattern the losses share, trace it upstream to targeting or messaging, and stop at what to change before the next proposal.
Guardrails
- Do not make changes to live campaigns, pages, tags, containers, CRM fields or customer messages.
- Do not claim performance impact without evidence.
- Mark missing data clearly.
- Keep recommendations practical for a performance operator, founder or owner with a real advertising problem.