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Design an enrichment waterfall that stops wasting spend

Builds provider waterfalls per field — email, phone, firmographics — ordered for your specific ICP rather than someone else's template, with validation, stop conditions, and a shown-math cost model. It converts enrichment from a flat subscription habit into an engineered pipeline where every provider position is justified by coverage and price.

The prompt
You are a B2B data strategist who has benchmarked every major enrichment provider across regions, seniority levels, and company sizes, and you know the dirty secret: there is no best provider, only a best order for a specific ICP. Teams that copy someone else's waterfall pay for coverage they don't need and miss the data they do.

Design my enrichment waterfall. Output:

1. PER-FIELD WATERFALLS — separate ordered provider lists for work email, mobile number, and firmographics, because the right order differs by field. For each provider in each list: why it sits at that position (coverage for MY icp, cost, accuracy), and its trigger condition (only fires if previous provider missed or returned low confidence).
2. VALIDATION LAYER — how each field gets verified before use (email verification step, catch-all handling, phone format checks) and what happens to rows that fail.
3. COST MODEL — expected cost per fully enriched contact given typical hit rates at each stage, with the math shown.
4. STOP CONDITIONS — when the waterfall gives up on a row instead of paying every provider to confirm the data doesn't exist.
5. REVIEW CADENCE — which numbers to check monthly (per-provider hit rate, cost per found email) to detect provider decay.

Rules: never put two providers with near-identical sources adjacent (they miss the same records). Catch-all emails get flagged, not treated as found. If I name a provider you'd cut entirely, say so and show the math.

Before you design, interview me. Ask ONE AT A TIME, waiting for my answer each time:
1. Who exactly are you enriching — roles, regions, company sizes?
2. Which fields do you need, in priority order?
3. Which providers do you currently pay for, and roughly what does each cost you?
4. Where does the waterfall run — Clay, n8n, or a provider's native platform?
5. What is an acceptable cost per fully enriched contact for your economics?

Then produce the waterfall design with the cost model.

How to use it

  1. 1

    Copy the prompt into Claude, ChatGPT, or any LLM.

  2. 2

    Answer the interview with your real provider costs — the ordering logic is cost-times-coverage, so vague costs produce vague orders.

  3. 3

    Implement the waterfall in Clay or n8n with the trigger conditions exactly as specced.

  4. 4

    After 1,000 rows, feed actual per-provider hit rates back into the chat and let it reorder.

Best practices

  • Track hit rate by provider by segment, not just overall — a provider great for US SaaS can be dead weight for EU manufacturing.

  • Always include the validation layer; a 95% found rate means nothing if a fifth are catch-alls that will torch your bounce rate.

  • Renegotiate or cut the bottom provider quarterly; waterfall data gives you the leverage numbers.

  • For mobile numbers, set a strict stop condition — phone data is expensive and the marginal provider rarely pays back.

Example: what this looks like in practice

An ops lead at a 50-person recruiting firm enriches 4,000 UK and DACH contacts monthly, paying for Apollo, Prospeo, and Clay-native credits with no particular order. The interview surfaces that mobile numbers matter more than email for their senior candidates, and their ceiling is 60p per enriched contact. The design comes back with different orders per field — Prospeo first for email, a specialist first for DACH mobiles with Apollo demoted to last — a verification step that routes catch-alls to a low-priority sequence instead of the main campaign, and a stop condition after two phone misses. Modeled cost lands at 41p per contact versus their current 78p, and month-one actuals come within 15% of the model.

Best fit

Roles
RevOpsFounder / CEOSDR / BDR
Company size
Startup (1–10)SMB (11–50)Mid-market (51–500)
Audience
B2B
Industries
Any industry
Works with
Any LLM
Difficulty
Advanced

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Prompt FAQ

Frequently asked questions

A sequence of data providers queried in order, where each fires only if the previous one missed. Instead of paying one provider for mediocre coverage or all providers for everything, you pay the cheapest acceptable source first and escalate only for the gaps. Done well, waterfalls raise coverage 20-30 points while lowering cost per contact.

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