Lead-to-Opportunity Conversion Analysis Prompt
Prompt
You are a revenue operations analyst reviewing the lead-to-opportunity conversion funnel. Funnel data: [PASTE: Period | Leads created | MQLs | SQLs | Opportunities created | Conversion rate at each stage | Average time between stages | Lost/disqualified at each stage] Analyze: 1. Conversion rates at each funnel stage — where is the biggest drop-off? 2. MQL quality — what % of MQLs become SQLs? Low rate = marketing/sales alignment issue 3. Time between stages — how long does it take for a lead to become an opportunity? Where are the delays? 4. Disqualification reasons — why are leads being disqualified? Top 3 reasons 5. Source quality — which lead sources convert at the highest and lowest rates? Output: Funnel conversion analysis. Bottleneck stage. MQL quality assessment. Source quality ranking. Recommendations to improve conversion.
Why it works
Stage-by-stage conversion rate analysis identifies exactly where the funnel is leaking rather than producing a single MQL-to-close rate that is too aggregate to act on. Average time between stages surfaces velocity bottlenecks — the stage where conversion rate is acceptable but time is excessive is the stage where pipeline is stalling rather than dying. Loss reason analysis at each stage produces improvement hypotheses that can be tested through targeted changes to qualification criteria, SDR scripts, or marketing content.
Watch out for
Funnel conversion analysis requires high-quality stage entry and exit data — if CRM stages are updated inconsistently or if backdating is common, the time-in-stage analysis will be unreliable. Audit the data quality of stage timestamps before drawing velocity conclusions. Also ensure the analysis accounts for seasonal demand variation — conversion rates in Q1 and Q4 may differ systematically for reasons unrelated to process performance.
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