Data operations determine whether your GTM engine runs smoothly—or constantly breaks.
Step 1: Data Cleaning
Before using any dataset:
- Remove invalid emails
- Normalize job titles
- Standardize company names
- Validate domains
Dirty data kills campaigns silently.
Step 2: Deduplication
Duplicates cause:
- Double outreach
- Confused sales teams
- Inflated metrics
Deduplicate by:
- LinkedIn URL
- Company + role combinations
Step 3: Enrichment
Enrichment turns raw data into actionable intelligence:
- Company size & revenue
- Tech stack
- Hiring trends
- Social links
But enrich after cleaning, not before.
Step 4: CRM-Ready Structuring
Map fields clearly:
- Lead vs Account fields
- Contact ownership
- Source tagging
- Campaign attribution
Bad imports create long-term reporting chaos.
Step 5: Continuous Data Hygiene
Data decays fast. Best teams:
- Revalidate quarterly
- Remove inactive contacts
- Update role changes
- Track engagement decay
Key Takeaway
Data Ops is not backend work—it’s revenue infrastructure.