Skill: HG Peer Cohort Selection
Peer comparisons that don't get torn apart in the deal review for comparing Siemens to Apple.
Overview
Peer-comparison briefs that survive a CRO's challenge. Claude builds the peer set on four axes (industry, employee band, revenue band, geography) instead of leaning on a single misleading industry code, and acknowledges niche cases where there are no clean peers rather than forcing a comparison.
Use cases
Defensible peer-comparison briefs
When a CRO asks 'why are these the peers', the brief shows NAICS-4 + 5,000–25,000 employee band + same revenue tier + EMEA region — four axes aligned, all visible. The conversation moves past 'is this comparison valid' to 'what does it tell us'.
Honest 'no peer set' calls
Some companies sit in a niche that doesn't produce 5+ comparable peers. Claude says so explicitly ('the closest comparables are…') instead of stretching the cohort across industries to fill the table.
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HG Peer Cohort Selection
When to use
- A workflow is producing a peer-comparison brief.
- A prompt is selecting "similar companies" and risks picking obvious-but-wrong matches.
- An author is choosing a peer set for benchmarking.
The four-axis rule
A defensible peer cohort needs four axes:
- Industry — NAICS-4 (industry group). 6-digit NAICS is too narrow; 2-digit is too coarse. Examples:
- "Process Control Instruments Manufacturing" (NAICS 334513) — too narrow; Siemens has subsidiaries that all sit in this code, others don't.
- "Manufacturing" (NAICS 31-33) — too coarse; bundles consumer goods with heavy industry.
- "Computer & Electronic Product Manufacturing" (NAICS 3344) — NAICS-4 — right grain.
- Employee band. Use buckets: 1-50, 50-250, 250-1000, 1000-5000, 5000-25000, 25000-100000, 100000+. Adjacent buckets are usually fine; jumping more than one bucket is not.
- Revenue band. Bucket similarly. A 1000-employee professional-services firm and a 1000-employee SaaS company have wildly different revenues and shouldn't be compared on a spend axis.
- Geography. Region (Americas / EMEA / APAC) is usually enough. Country can be too narrow (excludes obvious peers in adjacent regulatory environments). Multi-region companies need a "primary HQ" decision.
A cohort with at least 3 axes aligned is defensible; 4 axes aligned is ideal.
Why naive industry codes mislead
Siemens AG (NAICS 334513, 316,000 employees, EMEA) and Honeywell International (NAICS 334513, 99,000 employees, Americas) sit in the same 6-digit NAICS but differ by 3× on employees and operate in different regulatory environments. A peer comparison citing both is technically correct and practically misleading.
Conversely, two companies in different 6-digit NAICS may be functionally identical — a mid-market SaaS company in NAICS 511210 ("Software Publishers") and one in NAICS 541512 ("Computer Systems Design Services") are both modern B2B SaaS by every meaningful measure.
Decision rule: start from NAICS-4, not NAICS-6. If the cohort is too small, drop to NAICS-3. Do not start broad and narrow.
When to expand the cohort
- The strict 4-axis filter returns < 5 candidates → drop the geography axis (Americas + EMEA together).
- Still < 5 → drop revenue (keep employees + industry + geography).
- Still < 5 → consider that the company is in a niche category and acknowledge it ("there are no clean peers; the closest comparables are…").
Never expand by changing NAICS — that defeats the purpose.
Common pitfalls
- "Similar industry" without specifying which 4 digits. "Siemens and Apple are both technology companies" is true at NAICS-2 and useless at NAICS-4.
- Skipping the revenue axis when comparing on spend. Two companies with the same employee count and a 5× revenue gap have totally different IT-spend baselines.
- Including the target company in its own peer set. Obvious in writing, easy to do in a fuzzy match.
Reference
hg-insights-api.md#firmographichg-firmographic— confidence bands on employees + revenue