Diagnose Why a Rep is Missing Quota

You are a sales manager doing a fair, data-grounded diagnosis of a rep's performance at a digital marketing agency. You diagnose causes — you do not coach or prescribe fixes in this step.
Agency: [AGENCY_NAME] — [SERVICES] | Rep: [REP_NAME] | Tenure: [TENURE_MONTHS] months | Quota: [QUOTA] | Attainment: [ATTAINMENT_PCT] | Period: [PERIOD]
Data:
[REP_PIPELINE]
[ACTIVITY_DATA]
[BENCHMARK_TEAM_AVERAGES]
Diagnose the single most likely reason [REP_NAME] is missing quota this period, plus 2 secondary contributing factors, each backed by specific numbers from the data.

- Cite specific data points (counts, conversion rates, dollar amounts) — never opinion.
- Distinguish clearly between a skill gap, a pipeline gap (top-of-funnel volume), and an effort gap (activity levels).
- Compare to [BENCHMARK_TEAM_AVERAGES] where possible to avoid blaming the rep for market conditions.
- Tone is constructive and clinical. No character judgements like "lazy" or "not coachable."
- If data is missing to confirm a hypothesis, say so explicitly.

Output:
1. Headline diagnosis (1 sentence, name the primary gap: skill / pipeline / effort / mix)
2. Ranked root-cause hypotheses (Primary + 2 Secondary), each with: hypothesis, supporting evidence (numbers), confidence (High/Med/Low)
3. Data gaps to fill before final judgement

• [AGENCY_NAME] — Your agency's name
• [SERVICES] — Core services sold (e.g., SEO, paid social retainers)
• [REP_NAME] — First name of the rep being diagnosed
• [TENURE_MONTHS] — How long the rep has been in seat
• [QUOTA] — Period quota in MRR or new business $
• [ATTAINMENT_PCT] — Their actual % of quota hit
• [PERIOD] — The period being analyzed (e.g., Q1 2026)
• [REP_PIPELINE] — Pipeline export: stage, value, age, last activity
• [ACTIVITY_DATA] — Calls, emails, meetings booked, proposals sent
• [BENCHMARK_TEAM_AVERAGES] — Team-average activity + conversion rates for comparison

Agency: Northwind Digital — SEO + Google Ads retainers | Rep: Marco | Tenure: 9 months | Quota: $25k new MRR | Attainment: 48% | Period: Q1 2026
Pipeline: 14 open deals, total $38k MRR, avg age 47 days, 6 deals with no activity in 14+ days.
Activity: 112 calls (team avg 180), 38 discoveries booked (team avg 42), 9 proposals sent (team avg 14), discovery→proposal 24% (team 33%).

Headline diagnosis: Primary gap is EFFORT at the top of funnel, with a secondary SKILL gap converting discoveries into proposals.

Ranked hypotheses:
1. Primary — Effort gap (Confidence: High). Marco made 112 calls vs team avg 180 (-38%). Discoveries booked are close to average (38 vs 42), so connect rate is fine — raw dial volume is the constraint.
2. Secondary — Skill gap at discovery→proposal (Confidence: Medium). 24% conversion vs team 33%. Suggests qualification or value-framing weakness, but sample size (38) is moderate.
3. Secondary — Pipeline hygiene (Confidence: Medium). 6 of 14 open deals have no activity in 14+ days. Inflates pipeline value but may mask true coverage.

Data gaps: Need call recordings from discoveries that did NOT convert, and lead-source breakdown to rule out a lead-quality issue before confirming the skill gap.

• Always paste the team averages alongside the rep's numbers — without a benchmark Claude will over-index on absolute figures.
• Run this BEFORE the 1:1, not during. The diagnosis should shape your questions, not be read aloud.
• If attainment has been low for 2+ periods, also paste prior-period data so Claude can spot a trend vs a one-off.