Analyze · Win/Loss Analysis

Analyze Lost-to-Competitor Deals for Patterns

Diagnose where specific competitor agencies are beating you and what consistently tips deals their way.

foundermanagerAdvanced⏱ 3 hours
When to use
Use when you have 6+ losses where a competitor was named and you want a head-to-head readout per competitor, not just "we lost on price." Critical input before refreshing battlecards or competitive positioning.
The prompt
You are an analytics-minded sales leader for a digital marketing agency. You diagnose competitive losses based only on documented loss notes and you separate "what they did better" from "what we did worse."
Agency: [AGENCY_NAME] — [SERVICES] | Period: [PERIOD] | Data:
[COMPETITOR_LOSS_DATA]
(For each deal: company, service, ACV, competitor name, stated loss reason, any quoted buyer feedback, stakeholder titles.)
Group the losses by competitor. For each competitor with 2+ losses, identify: (1) the recurring narrative for why they win, (2) the deal shape where they beat us (industry, ACV band, service), (3) which of our gaps are real vs perception, (4) one positioning fix to test next quarter. Then flag any competitor mentioned only once as "single instance — monitor."

- Every competitor pattern must cite at least 2 deals and quote at least 1 buyer reason verbatim.
- Distinguish "real gap" (capability) from "perception gap" (messaging) — don't conflate.
- Don't speculate on competitor pricing or capabilities not mentioned in the input.
- No rep-bashing.

Output one section per competitor: header with deal count and total ACV lost, then 4 bullets (narrative / where they win / real vs perception gap / positioning fix to test). End with a "single instance" list.
Variables
  • [AGENCY_NAME] — Your agency name
  • [SERVICES] — Service lines covered
  • [PERIOD] — Date range analyzed
  • [COMPETITOR_LOSS_DATA] — Lost deals where a competitor was named, with loss reason and any quoted buyer feedback
Example input
Agency: Northstar Digital — SEO, Paid Search | Period: trailing 6 months
Losses with competitor:
BrewHaus | PS | $72k | AdVenture | "reporting felt thinner" | Demand Gen Mgr
MetroMattress | PS | $108k | AdVenture | "existing relationship" | Marketing Dir
Kite | PS | $54k | AdVenture | "more attribution depth" | CMO
Cedar & Sage | SEO | $48k | ContentHive | "more CPG experience" | Brand Director
Northwind | SEO | $60k | ContentHive | "they bundled content production" | VP Marketing
Lumen | Web | $32k | GridSquare | "better portfolio in lighting" | VP Marketing
Example output
AdVenture — 3 losses, $234k ACV.
- Narrative: positioned as the attribution/reporting depth specialist.
- Where they win: mid-market Paid Search deals, $50k–$110k ACV.
- Gap type: mix — "more attribution depth" is real; "reporting felt thinner" is perception (our reporting is comparable but presented less clearly).
- Fix to test: lead PS demos with a live attribution view and ship a redesigned monthly report template.

ContentHive — 2 losses, $108k ACV.
- Narrative: vertical specialist with bundled content production.
- Where they win: CPG-adjacent SEO deals where content velocity matters.
- Gap type: real capability gap on in-house content production.
- Fix to test: a vetted content production partner with co-branded SOW for CPG prospects.

Single instance — monitor: GridSquare (Web/Lumen).
Pro tips
  • Force reps to log the competitor name as a required field on closed-lost — without it, this analysis is impossible.
  • Separate "real" from "perception" gaps — perception gaps are cheap to fix; capability gaps need an investment decision.
  • Re-run after any competitive battlecard refresh to see if the loss narrative actually shifted.
Works with
ClaudeChatGPTGemini
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