Enrichment and Data QA

Define minimum data, cut noise, and improve personalization quality.

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Learning Goal

• List minimum fields (lead + account).
• Create an enrichment/QA checklist.
• Audit 15 leads and fix errors.

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Why It Matters

• Noisy data = poor personalization and conversion.
• Enrichment gives context (risk/trigger).
• QA keeps lists usable.

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Explanation

Minimum fields

• Account: industry/problem trigger, size, country, tech.
• Lead: role, seniority, email/LinkedIn, relevant signal (post/project).

QA checklist

• Duplicates, missing key fields, bad domain.
• Relevant signal present (trigger)?

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Examples

Good: Account + lead fields filled, trigger noted, no duplicates.

Bad: Only email, no role, no trigger, duplicate contact.

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Guided Exercise (10–15 minutes)

1. Write the minimum field list (account + lead).
2. Create the QA checklist (dupes, domain, trigger).
3. Audit 15 leads and fix errors.

Independent Exercise (5–10 minutes)

Write 3 rules for what you will not send (e.g., no role, no trigger, bouncy domain).

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Self-check

• Minimum fields defined.
• QA checklist ready.
• 15 leads audited and fixed.
• 3 exclusion rules written.

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Optional Deep Dive

• Data quality: https://www.hubspot.com/data-quality
• Enrichment example: https://clearbit.com