• 506 6133 8358
  • john.mecke@developmentcorporate.com
  • Tronadora Costa Rica

Win/Loss Analysis

AI‑Accelerated Win/Loss Analysis for Pre‑Seed & Seed SaaS

Know precisely why you win and lose deals—then translate those findings into immediate product, pricing, and GTM moves.

Why leaders choose this analysis

  • Answers the questions your board, sales, and marketing teams will ask—on one page each.
  • Benchmarks competitors’ win themes, pricing, objections, and buyer jobs using real conversations and signals.
  • Translates findings into immediate GTM, product, and pricing actions with measurable next steps.

What you get

  • Executive Brief (10 pages): crisp synthesis of why you win/lose, segmented by persona, industry, and deal size.
  • Deal‑Level Coding: structured tags for drivers, blockers, pricing, decision criteria, and competitor mentions.
  • Buyer Jobs & Narratives: clear articulation of Jobs‑to‑Be‑Done and proof‑points pulled from interviews and transcripts.
  • Pricing Insights: perceived value, packaging friction, discount dynamics, and early price sensitivity readout.
  • Messaging & Objection Handling: tested talk tracks and email copy derived from real buyer language.
  • Playbook & Next‑Quarter Plan: prioritized actions for product, sales, and marketing with owners and metrics.

How it works (10‑day sprint)

1) Discovery (Days 1–2)

  • Deal export & pipeline triage
  • Interview list & outreach templates
  • Hypothesis log (win themes, risks)

2) Research Sprints (Days 3–7)

  • Buyer & evaluator interviews (won & lost)
  • Call recordings/transcripts mining
  • Competitor pattern capture

3) Synthesis & Readout (Days 8–10)

  • Executive Brief & win/loss dashboard
  • Enablement assets & talk tracks
  • Road‑mapping & next‑quarter plan

Our AI‑accelerated method

  • Conversation Intelligence: rapid diarization, redaction, and topic modeling over sales calls and interviews.
  • Thematic Coding at Scale: LLM‑assisted labeling of drivers, blockers, pricing friction, and competitor mentions—human‑verified.
  • Synthetic Panel Pre‑Tests (optional): simulate buyer interviews to pre‑surface hypotheses before human interviews.
  • Evidence‑First Synthesis: direct quotes, call snippets, and artifacts linked to each finding.

Who this is for

Founders and product leaders at pre‑seed and seed‑stage SaaS companies who need defensible answers to: What truly drives wins? Why do we lose? How should we adjust product, pricing, and messaging now?

Deliverables

  • Executive Brief (PDF + Google Slides)
  • Win/Loss Dashboard (Notion/Sheets)
  • Interview Notes & Clips (redacted as needed)
  • Messaging & Objection Playbook
  • Pricing Insights Memo
  • Next‑Quarter Action Plan with owners, milestones, and KPIs

Timeline & Pricing

Standard sprint: 10 business days from kickoff. Fixed‑fee engagement with optional add‑ons (extra interviews, competitor deep‑dives, pricing study). Request a quote based on your pipeline size and interview targets.

Frequently Asked Questions

How many interviews are included?

Typical sprints include 8–12 buyer/evaluator interviews (mix of won and lost). We’ll tailor volume to your pipeline and deal complexity.

Can you work with our call recordings and transcripts?

Yes. We ingest call recordings (Zoom, Gong, Chorus, Meet) and apply conversation intelligence to accelerate coding—then humans verify findings.

What if we have very few closed deals?

We can combine prospect interviews, lost‑deal interviews, and synthetic panel pre‑tests to generate early signals while you build pipeline.

Do you provide scripts and outreach templates?

Yes—email sequences, recruiter briefs, consent language, and incentives guidance are included.

About John C. Mecke

30+ years in enterprise software. Managing Director at DevelopmentCorporate.com. Specializes in competitive analysis, win/loss, ICP/PMF, and pricing for early‑stage SaaS.

  • Former product & GTM executive
  • Hands‑on researcher and advisor
  • Clients across US, UK, MENA

Trusted by

Leaders at early‑stage SaaS firms, research platforms, and data‑driven product teams.