Analyze · Rep Performance Diagnostics
Compare Rep Performance Across Stages
See exactly which pipeline stage each rep is strongest and weakest at, so you stop generalizing about "good" or "bad" reps.
managerfounderIntermediate⏱ 1-2 hours of manual comparison
When to use
Use quarterly, or whenever you're considering reorganizing roles (e.g., splitting SDR/AE). It reveals that a 'weak' rep may actually be elite at one stage and tanking on another — letting you redesign workflows rather than swap people.
The prompt
You are a sales manager doing a fair, data-grounded diagnosis of rep performance at a digital marketing agency. You compare reps stage-by-stage to surface specialization patterns — you do not rank reps overall. Agency: [AGENCY_NAME] — [SERVICES] | Reps: [REP_LIST] | Period: [PERIOD] Stage-by-stage conversion data: [STAGE_PERFORMANCE_TABLE] Note on volume: [VOLUME_CONTEXT] For each rep, identify the 1 stage where they outperform the team and the 1 stage where they underperform. Then identify any "specialist" patterns (e.g., a rep elite at top of funnel but weak at close) that suggest role design changes. - Use stage conversion rates, not absolute deal counts (so a high-volume rep doesn't look better by default). - Only call out gaps where sample size is meaningful — flag low-volume reps. - Distinguish a stage weakness from low overall volume. - Tone is observational, not evaluative. No "best rep" / "worst rep" labels. - Don't recommend coaching or firing — diagnosis only. Output: 1. Per-rep card: Strongest stage | Weakest stage | Sample-size caveat 2. Cross-team patterns (e.g., everyone leaks at proposal stage) 3. Specialist candidates (reps whose profile suggests a different role split) 4. Stages with insufficient data to judge
Variables
- [AGENCY_NAME] — Agency name
- [SERVICES] — Services sold
- [REP_LIST] — Names of reps being compared (3-8 ideal)
- [PERIOD] — Reporting window
- [STAGE_PERFORMANCE_TABLE] — Rows = reps, columns = conversion rate at each stage
- [VOLUME_CONTEXT] — Note how many opps each rep had so small samples can be flagged
Example input
Agency: Northwind — SEO + paid | Reps: Marco, Priya, Dani | Period: Q1 2026 Stage table (% conversion): | Rep | Lead→Disco | Disco→Prop | Prop→Won | | Marco | 22% | 40% | 38% | | Priya | 35% | 55% | 27% | | Dani | 30% | 48% | 33% | Volume: Marco 80 leads, Priya 90, Dani 25.
Example output
Per-rep cards: - Marco: Strongest = Proposal→Won (38%). Weakest = Lead→Disco (22%, well below 30% team). Sample size OK. - Priya: Strongest = Disco→Proposal (55%). Weakest = Proposal→Won (27%). Sample OK. - Dani: Strongest = appears balanced. Weakest = inconclusive — only 25 leads (low confidence on all stages). Cross-team patterns: Top of funnel is generally healthy team-wide except Marco. Proposal→Won varies widely (27-38%), suggesting individual selling style matters more here than process. Specialist candidates: Marco's profile (weak top, strong close) and Priya's (strong middle, weak close) are mirror images. Consider testing a handoff where Priya does discovery+proposal and Marco closes. Insufficient data: All of Dani's stages — needs another quarter.
Pro tips
- Limit to reps with at least 20 opps in the period — anything less is noise.
- Run this before any major comp plan or territory change.
- Pair with the 'Identify Strong Plays From a Top Rep' prompt to confirm what the strong-stage rep is actually doing.
Works with
ClaudeChatGPTGemini
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