Business Model Comp Matching

Use This Skill When

• The user needs a defensible peer set for valuation, strategic benchmarking, or debate prep.
• Industry labels are too broad because the target has mixed segments, unusual monetization, or a different customer base.
• A standard comp list obscures differences in margin structure, capital intensity, or go-to-market motion.
• The analysis must explain why some well-known "peers" should be excluded or downgraded.

Required Inputs

• Target company name, ticker, and short business description.
• Revenue mix by product, segment, geography, and customer type if available.
• Monetization model such as subscription, transaction, licensing, ads, usage-based, or services-heavy.
• Margin profile, growth profile, and capital intensity markers if available.
• The purpose of the peer set: valuation, moat analysis, operating benchmark, or investment memo support.

Workflow

1. Define the target profile in business-model terms: buyer, use case, pricing unit, revenue recurrence, implementation burden, gross margin profile, and sales motion.
2. Identify candidate peers based on operating resemblance first, not on SIC code, index membership, or common sell-side shortcuts.
3. Compare each candidate on the main comparability dimensions:
   • Revenue mix
   • Customer size and vertical exposure
   • Pricing architecture
   • Gross margin and opex structure
   • Sales cycle and distribution model
   • Capital intensity and cash conversion
4. Classify peers into core comps, partial comps, and reference comps.
5. Explicitly call out breakpoints where comparability fails, such as services mix, hardware exposure, geographic distortion, or materially different end-market cyclicality.
6. Tailor the final recommendation to the user's purpose. A peer set for valuation should be tighter than a peer set for strategic context.

Output Requirements

• Write in a precise buy-side research tone: analytical, skeptical, and explicit about trade-offs.
• Use a tiered structure with clear labels rather than a flat peer list.
• For each peer, explain the match in 2 to 4 concrete comparability points, not generic adjectives.
• State where comparability breaks and whether that weakness matters for the current use case.
• Prefer directional language like closest, acceptable with caveats, or use only as a reference, instead of false precision.

Output Template

Quality Checks

• Confirm every proposed peer shares the same core revenue engine, not just the same broad industry label.
• Check that customer type and deal motion are addressed; SMB and enterprise models are rarely interchangeable.
• Verify that margin profile and services content are discussed where they materially affect comparability.
• Make sure at least one clear reason is given for excluding or downgrading obvious-but-weak peers.
• Ensure the peer classification reflects the user's purpose rather than pretending one list fits every task.

Guardrails

• Do not select peers based only on market cap, popularity, or common screeners.
• Do not ignore segment mix when a conglomerate or multi-product company is involved.
• Do not present reference comps as valuation anchors.
• Do not force exact comparability when the business model genuinely lacks clean public matches; say so explicitly.
• Do not rely on management self-description alone if disclosed economics point to a different operating model.

Example Prompts

• Build a proper comp set for Adyen and explain why some payment names are only partial comps.
• Match the closest public peers for a vertical SaaS company with payments attached and heavy implementation revenue.
• I need a valuation-ready peer list for Cloudflare; separate core comps from conceptually similar but economically weak matches.