The problem

• Different enrichment sources = different answers.
• Clearbit says “VP Sales.” Apollo says “Head of Growth.” LinkedIn says “CRO.”
• Garbage in → garbage out for your CRM.

Step 1: Run Multi-Source Enrichment

• Pull contact/company data from 2–3 APIs.
• Typical stack: Clearbit + Apollo + LinkedIn scrape.
• Store results in separate columns.

Step 2: Identify Conflicts

• Use Clay formulas to flag mismatches.
• Example: if job_title_A ≠ job_title_B.
• Add a “Conflict Detected” column = Yes/No.

Step 3: Use Agentic AI to Resolve

• Prompt Claygent: “Given these 3 job titles, which is most accurate for a B2B prospect in Sept 2025? Return single title.”
• Add context (last updated date, source reliability).
• AI outputs “Final Title.”

Step 4: Clean for Salesforce

• Only push “Final Title” to CRM.
• Keep raw enrichment data in Clay for audit.
• Write notes like: “Resolved from 3 conflicting sources.”

Step 5: Automate at Scale

• Run daily dedupe jobs.
• Update existing records instead of creating duplicates.
• Add logic: if AI confidence <70%, send to SDR for manual check.

Why this matters

• Sales hates bad data.
• SDRs waste time calling the wrong people.
• Deduplication boosts conversion and keeps Salesforce clean.

Pro tips

• Weight LinkedIn higher for job titles, Apollo higher for emails.
• Use AI to normalize formatting (VP Sales vs Vice President, Sales).
• Track % of conflicts resolved automatically vs manual.

Outcome

• Clean, trusted lead lists.
• Fewer bounced emails.
• SDRs spend time selling, not cleaning data.
• Clay becomes your “truth layer” between APIs and Salesforce.

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