31% Of CRM records deduped, completed, or corrected

01The problem

Every firm that has run a CRM for a few years has the same database. The same company exists three times under slightly different names. Half the contact records are missing a phone number or an email. Deals sit in stages nobody uses anymore, left over from an old process or a rushed migration.

The cost is quiet but constant. Reps call people a colleague already called. Reports overcount pipeline because duplicates each carry their own deal. Automations fire on records with empty fields and do nothing, or worse, do the wrong thing.

The usual answer is a cleanup project: export everything, fix it in a spreadsheet, import it back. It works for about a month. Then the same forms, the same imports, and the same manual entry put the mess right back, because nothing changed about how bad data gets in.

02What we built

We treated data quality as infrastructure. Instead of one pass over the database, we built a set of processes inside the brokerage's HubSpot that run on every record, every day.

• Dedup rules. Records are matched on more than exact name: domains, phone numbers, and normalized company names. Confident matches merge automatically, borderline ones queue for a human decision.
• Enrichment. Incomplete records get their missing fields filled from the sources the firm already has: form submissions, email activity, and connected data. A record with a name and nothing else becomes a record someone can act on.
• Validation at the door. We built test kits for every intake form and ran each one end to end, checking that every field lands where it should. Bad data gets rejected or flagged at entry instead of discovered months later in a report.
• Migration gap analysis. We audited what the migration from the old system had dropped or mangled, then repaired those records rather than leaving them to rot.
• Workflow documentation. Every automation touching the data is documented, so the team knows what runs, when, and why, and the next change does not quietly break the last one.

03What changed

By the time the system had run through the full database, 31% of records had been deduped, completed, or corrected. Nearly a third of what the team was working from every day had been wrong in some way.

The more important change is what happens next month. Dedup plus enrichment run continuously, so new duplicates merge and new gaps fill without anyone scheduling a cleanup. The database is kept clean automatically, as a property of the system rather than an act of willpower.

Downstream, the effects compound. Pipeline reports count each deal once. Reps trust the record in front of them. Automations act on complete data, which means they can be trusted with more of the process.