Data Deduplication
Data deduplication identifies duplicate records in your database and merges them into single, authoritative entries. It goes beyond exact matching to catch near-duplicates where names are spelled differently, companies use multiple domains, or the same person appears with different email addresses.
Duplicates create real business problems. Sales reps call the same prospect twice. Marketing sends the same person three emails. Reports overcount pipeline by 15-20%. And every integration or import makes it worse because each system brings its own copy of the same contacts.
How We Find and Merge Duplicates
- Fuzzy name matching. John Smith, Jon Smith, J. Smith, and Jonathan Smith are probably the same person. Our matching handles nicknames, abbreviations, middle names, and common misspellings.
- Company normalization. Acme Corp, ACME Inc., Acme Corporation, and acme.com all point to the same company. We normalize before matching so variants get caught.
- Cross-field matching. Different email but same phone number? Different name but same LinkedIn URL? We match across multiple fields to catch duplicates that single-field matching misses.
- Intelligent merge rules. When we find duplicates, we do not just pick one and delete the rest. We merge the best data from each record: the most recent email, the most complete address, the most accurate job title.
- Confidence scoring. Every potential match gets a confidence score. High-confidence matches merge automatically. Low-confidence matches get flagged for your review so we never merge records that should stay separate.
After Deduplication
- A single source of truth for every contact and company in your database
- Accurate pipeline and revenue reporting without inflated counts
- Sales teams that never accidentally contact the same person twice
- Marketing campaigns that send one message per person, not three
- Clean data for integrations so new tools start with accurate records
Common Questions
How do you handle duplicates where each record has different data?
We merge them intelligently. If Record A has the best email and Record B has the best phone number, the merged record gets both. We use recency, completeness, and source reliability to decide which value wins when there is a conflict. You get a report showing what was merged and why.
What if your system merges two records that are actually different people?
Low-confidence matches are always flagged for human review rather than auto-merged. We set confidence thresholds conservatively. It is better to leave a potential duplicate unflagged than to merge two real people. You can also set custom rules for your specific data.
Can you deduplicate across multiple systems?
Yes. Send us exports from Salesforce, HubSpot, your marketing platform, and your support tool. We deduplicate across all sources and deliver a unified file that you can use as your master record set. Cross-system deduplication catches duplicates that no single system can see.
Related: All Data Cleaning | Data Cleaning Services | Crm Data Cleaning | Phone Formatting