TAM & Enrichment Architecture

Map the addressable market of U.S. beauty and wellness businesses — hair salons, nails, spa, massage, makeup, lash, brow, skin/facial, waxing, barber and tanning — and architect a data pipeline capable of reaching a target of 90,000 phone numbers.

• Target businesses were constrained to a single retail location, roughly 2–50 employees, across two technology segments (specific and general).
• No single data provider covered the market cleanly — each had different strengths, blind spots and cost structures.
• Phone number availability varies significantly by provider and can't be assumed uniform.
• Enrichment at this scale carries real cost — credit spend needed to be modeled, not ignored.

Rather than pick one provider and accept its coverage gaps, I treated this as a source-comparison problem: run the same segment definition through Openmart, Apollo and Clay, measure what each returned after strict exclusions, and use the comparison to decide where each source should sit in the pipeline.

Apollo was used first where it was the cheaper source. Openmart filled gaps where Apollo's coverage was thin. Clay sat on top as the orchestration layer — audiences, segments and deduplication — so the same company was never enriched twice across sources. The order mattered as much as the source selection: cheap and reliable first, secondary routes only where needed.

After strict exclusions, the three sources returned meaningfully different TAM sizes:

Openmart's broad, niche-by-niche searches exceeded 150,000 companies before deduplication — useful for reach, but it needed heavy overlap cleanup before it was usable. The estimated model settled on roughly 108,000 companies requiring enrichment to responsibly approach the 90K phone-number target, after accounting for expected phone availability and deduplication across sources.

The assessment also modeled provider economics directly: roughly 452,000 Apollo credits and 32,500 Clay credits, plus per-company enrichment costs depending on the source used — not just a company count, but a cost-aware plan for reaching it.

This was an architecture and assessment exercise — it demonstrates how I evaluate data providers and design a practical, cost-aware enrichment pipeline, not a claim that 90,000 phone numbers were delivered. SalesCaptain reviewed the submission and progressed the conversation to an interview.

• TAM size depends heavily on which provider is asked and how exclusions are defined — a single-source number is rarely the real market.
• Sequencing providers by cost and coverage, with an orchestration layer for deduplication, beats picking one "best" source.
• Enrichment economics (credits, per-record cost, expected yield) belong in the architecture decision, not as an afterthought.