Analyze · ICP-Fit & Lead-Quality Analysis

Diagnose Why ICP-Fit Leads Aren't Converting

Diagnose why your A-tier agency leads are stalling or losing so you can fix sales execution, not blame the leads.

foundermanagerAdvanced⏱ 4-6 hours of pipeline forensics
When to use
Use when win rate on A/B leads drops below your benchmark or when the team complains 'good leads aren't closing.' Output isolates whether the problem is discovery, proposal, pricing, or rep — instead of letting everyone blame marketing.
The prompt
You are an analytics-driven head of marketing for a digital marketing agency, diagnosing why qualified pipeline isn't closing.
Agency: [AGENCY_NAME] — [SERVICES]
ICP: [ICP_DEFINITION]
A/B-tier deals (last 90d, won + lost + stalled):
[DEAL_LIST] — each row: deal, owner, ICP_bucket, source, stage_reached, outcome (won/lost/stalled), loss_reason, sales_cycle_days, last_activity_days_ago
Diagnose why our ICP-fit (A/B) leads aren't converting and isolate whether the failure is discovery, proposal, pricing, or rep execution.

- Calculate stage-by-stage conversion rates for A/B deals only.
- Cluster loss/stall reasons into themes — max 6.
- Show win rate by rep on A/B deals — flag reps >15pp below team average.
- Do not blame leads; lead quality is held constant (A/B only).
- Recommend ONE highest-leverage fix, not a list — focus.

1) Stage conversion funnel (A/B only). 2) Loss-reason theme table. 3) Win rate by rep on A/B deals. 4) Root-cause hypothesis. 5) ONE highest-leverage fix.
Variables
  • [AGENCY_NAME] — Your agency's name
  • [SERVICES] — Services offered
  • [ICP_DEFINITION] — Current ICP
  • [DEAL_LIST] — A/B-tier deals from CRM with stage, outcome, loss reason, rep
Example input
Agency: PixelForge — Webflow + CRO for SaaS
ICP: B2B SaaS, Series A–B, 30–200 staff
22 A/B deals last 90d:
Discovery → Proposal: 18/22 (82%)
Proposal → Negotiation: 9/18 (50%)
Negotiation → Won: 5/9 (56%)
Won overall: 5/22 (23%)
Loss reasons: 'price too high' x6, 'going in-house' x3, 'timing' x3, 'lost to competitor (Webflow agency X)' x4, 'no response' x1
Win rate by rep: Rina 4/8 (50%), Pat 1/8 (13%), Marcus 0/6 (0%)
Example output
A/B Funnel:
Discovery → Proposal: 82%
Proposal → Negotiation: 50% ← biggest drop
Negotiation → Won: 56%
Total: 23%

Loss themes:
| Theme | Count |
| Price objection | 6 |
| Competitor (specifically Agency X) | 4 |
| Going in-house | 3 |
| Timing | 3 |
| Ghosted | 1 |

Win rate by rep (A/B only):
Rina 50%, Pat 13%, Marcus 0%. Team avg: 23%. Pat and Marcus both >15pp below.

Root-cause hypothesis: The funnel collapses at Proposal→Negotiation, driven by price objections and losses to a specific competitor. Two of three reps can't defend price on ideal-fit deals. This is a value-articulation and competitive-positioning problem at proposal stage, not a lead-quality problem.

Highest-leverage fix: Build a 1-page 'Why us vs Agency X' battlecard and run a 60-minute proposal-clinic roleplay with Pat and Marcus this week. Re-measure proposal→negotiation rate in 30 days.
Pro tips
  • Only run on A/B deals — including C/D contaminates the diagnosis.
  • If one rep is way above average, shadow their proposal calls before changing process.
  • Re-run in 30 days to confirm the fix moved the proposal→negotiation rate.
Works with
ClaudeChatGPTGemini
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