What does data cleansing include?
Data cleansing (also called data cleaning or data hygiene) involves six core activities. Deduplication: identifying and merging duplicate records (typical CRMs have 10-25% duplicates). Standardization: normalizing formats for job titles, phone numbers, addresses, and company names. Validation: confirming emails are deliverable, phone numbers are formatted correctly, and fields contain valid values. Removal: deleting records that are permanently invalid, outdated beyond recovery, or junk entries. Correction: fixing typos, updating outdated information, and resolving inconsistencies. Archival: moving inactive records out of active workflows to improve database performance.
What does data enrichment include?
Data enrichment appends new data points from external sources. Contact enrichment: adds verified work emails, direct phone numbers, current job titles, seniority levels, and LinkedIn URLs. Company enrichment: adds industry, employee count, revenue, technology stack, funding stage, and headquarters location. Behavioral enrichment: adds intent signals, job change alerts, funding events, and hiring indicators. Enrichment sources include data providers (ZoomInfo, Apollo, Clearbit), public records, web scraping, and proprietary databases. Waterfall enrichment queries 25+ providers per record for maximum coverage.
When should you cleanse vs enrich?
Cleanse when: your bounce rate exceeds 3%, duplicate records are above 5%, field formatting is inconsistent (VP Sales vs Vice President of Sales), or records have not been updated in 12+ months. Enrich when: records are missing email addresses or phone numbers, firmographic data is incomplete, you are preparing for outbound campaigns, or lead scoring requires more data points. Always cleanse before enriching. Enriching dirty data wastes money because you are paying to enhance records that may be duplicates or otherwise invalid.
What are the key metrics for each process?
Data cleansing metrics: duplicate rate (target under 5%), email validity rate (target 95%+), field completion rate (target 85%+), data freshness (target 65%+ updated within 90 days). Data enrichment metrics: fill rate per field (percentage of records successfully enriched), email deliverability rate after enrichment, phone connection rate, match rate (percentage of inputs that returned results). Track both sets of metrics to measure overall data quality improvement.
