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DE-2 · Data & Enrichment · 125 XP · ~20 min
Every data provider has gaps. Apollo misses some companies. Hunter can’t find certain email formats. ZoomInfo is expensive and patchy in EMEA. No single source will enrich 100% of your list. Waterfall enrichment solves this by running multiple providers in sequence — Provider A first, then Provider B if A returns nothing, then Provider C. You only pay for successful enrichments, and you maximize coverage without redundant spend.

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How Waterfall Enrichment Works

The concept is simple: try the cheapest or most accurate source first. If it returns a result, stop. If it returns nothing, fall to the next provider. 
Row → Provider A (try first)
        → Result found? → Use it. Done.
        → No result? → Provider B
                          → Result found? → Use it. Done.
                          → No result? → Provider C
                                            → Result found? → Use it. Done.
                                            → No result? → Flag as "not found"
The order you sequence providers matters. Put your most accurate (or most affordable) source first, your broadest coverage source last.

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Building a Waterfall in Bitscale

In Bitscale, a waterfall is a series of enrichment columns with conditional logic. Step 1: First-pass enrichment column Add an API enrichment column calling Provider A (e.g., Hunter.io email finder):
  • Input: {{first_name}} {{last_name}} {{company_domain}}
  • Output: email address or null
Step 2: Fallback enrichment column Add a second enrichment column that only runs if Step 1 returned null: 
If {{provider_a_result}} is empty or null, use this enrichment. Otherwise return {{provider_a_result}}.
Connect this column to Provider B (e.g., Snov.io). Step 3: Final fallback + status column After all providers, add a status column: 
Given these enrichment results:
- Provider A: {{provider_a_result}}
- Provider B: {{provider_b_result}}
- Provider C: {{provider_c_result}}

Return the first non-empty result, or "not_found" if all are empty.
Also return the source that provided the result.

Output format: {"email": "result_or_not_found", "source": "provider_name_or_not_found"}

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Waterfall Priority Frameworks

Different use cases call for different provider ordering:

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For Email Accuracy (minimize bounces)

  1. NeverBounce / ZeroBounce verified emails (highest accuracy, narrowest coverage)
  2. Hunter.io (good coverage for SMB/mid-market, domain-pattern matching)
  3. Apollo.io (broad coverage, slightly lower accuracy)
  4. People Data Labs (backup for hard-to-find contacts)

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For Coverage (maximize list size)

  1. Apollo.io (largest contact database)
  2. Hunter.io (strong for tech companies)
  3. LinkedIn Proxycurl (professional profiles)
  4. ContactOut (good for senior executives)

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For International Contacts (EMEA/APAC)

  1. Prospeo or Findymail (strong EU coverage)
  2. People Data Labs (global)
  3. Hunter.io (lower international coverage but reliable)
  4. Manual research fallback

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The Credit Economy

Waterfall enrichment is also a credit optimization strategy. Here’s why: Without waterfall: You call Provider A for every row → pay for successful AND failed lookups. With waterfall: Provider A fills 60% of rows cheaply. Only the remaining 40% fall to Provider B. Provider C handles the final 15%. You spend credits proportionally to results. Cost comparison example (1,000 rows):
ApproachProvider AProvider BProvider CTotal CostFill Rate
Provider A only1,000 credits——$5060%
Provider A + B only600 + 400400 credits—50+50 + 24 = $7485%
Full waterfall600 + 400400 + 240160 + 64~$9595%
Getting from 60% to 95% fill rate costs only ~90% more in this example — often worth it if your ICP is well-defined.

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Handling Waterfall Results

After the waterfall runs, you need a clean master column and a confidence score: Master email column: 
Return the best available email from this list, in priority order:
1. {{provider_a_email}} (use if not empty)
2. {{provider_b_email}} (use if not empty)
3. {{provider_c_email}} (use if not empty)
4. Return "not_found" if all empty

Return ONLY the email address or "not_found".
Email confidence column: 
Given:
- source: {{email_source}}
- validation_status: {{validation_status}}

Assign a confidence score:
- high: validated email from a verified source
- medium: unverified email from a reliable source
- low: catch-all domain or risky status
- none: not_found

Return ONLY: high, medium, low, or none
Only send to high and medium confidence rows. Put low confidence on a separate, lower-volume sending track.
Quick Check: What’s the fundamental logic of a waterfall? What determines the priority order of providers? What does “credit economy” mean in the context of waterfall enrichment?

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DE-2 Challenge: Build a 3-Provider Waterfall (+125 XP)

Build a Bitscale waterfall enrichment grid for a list of 50+ contacts using at least 2 enrichment providers (can use trial accounts or test APIs). Requirements:
  • 3-step waterfall (Provider A → Provider B → fallback)
  • Master email column pulling from waterfall results
  • Email confidence column (high/medium/low/none)
  • Source attribution column (which provider filled this row)
  • Fill rate summary: how many rows each provider filled (can be a note in your submission)
  • Cost comparison: what it would have cost to run all rows through Provider A only vs. waterfall

Submit DE-2 Challenge →

Share your grid link + fill rate summary + cost comparison. +125 XP on approval.

Next: DE-3 — Data Cleaning at Scale →

Raw data is always messy. DE-3 covers the cleaning layer that standardizes, deduplicates, and normalizes data before it enters your workflow.