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.
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.
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