// CRM data cleaning
Keep your CRM clean without a manual cleanup project.
Standardize fields, validate contact data, and remove duplicates before records ever reach your CRM — or clean what's already in it.
Who this is for
- RevOps and sales-ops teams responsible for CRM accuracy
- Marketing-ops teams whose routing and scoring depend on clean fields
- Analytics teams whose reports break on duplicate and malformed records
- Developers syncing app data into Salesforce, HubSpot, or a warehouse
The problem
CRMs decay. Reps enter data differently, imports stack up duplicates, and formats drift over time. Dirty CRM data breaks reporting, misroutes leads, and erodes trust in the numbers.
Where it goes wrong
Rep-entered inconsistency
Ten reps enter company names ten ways (Acme, Acme Inc, ACME INC.). Reports group them as distinct accounts and territory routing sends the same company to different owners.
Import pile-up
Every list import adds another layer of duplicates. Without a match step at write time, contact counts inflate and activity history splits across records.
Format drift over time
Phone and date formats that were fine two years ago no longer match your current conventions, quietly breaking integrations that expect a single shape.
How it works
Point Zapinner at your records
Send records on the way into your CRM, or batches exported from it, to the Repair and Guard endpoints.
Standardize and validate
Fields are normalized to a consistent shape and contact data is validated, so every record follows the same rules.
Catch problems before they land
Guard validates records against your expectations and rejects or flags the ones that would pollute the CRM.
Write back clean records
Clean, deduplicated records flow into your CRM with a clear record of what was changed and why.
How Zapinner solves it
Clean at the boundary and in place
Use Guard on records entering the CRM to reject malformed ones at the door, and Repair on exported batches to clean what's already there. Both return a structured, per-field account of what passed, failed, or changed.
Deterministic normalization
Normalize canonicalizes the core contact fields — name, email, phone, company — into one consistent format. Because it's deterministic, the same messy value always resolves to the same clean value across every import.
Match before you write
Deduplication at write time turns cleanup from a recurring project into prevention: check whether a record already exists before inserting, and update instead of creating a duplicate.
Validate records before they enter the CRM
curl -X POST https://zapinner.com/api/v1/guard \
-H "Authorization: Bearer $ZAPINNER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"records": [
{ "company": "Acme Inc", "email": "sales@acme.com", "phone": "704-555-1234" }
],
"expect": { "email": "email", "phone": "phone" }
}'
# -> per-record pass/fail with the specific reason any field was rejectedReliability & security
Every change is explainable
Repair returns a changes array and Guard returns per-field pass/fail with reasons, so a cleanup is reviewable — not a black box that silently rewrote your CRM.
Idempotent and safe to retry
Requests carry a request_id and the core operations are deterministic, so re-running a batch produces the same result rather than compounding changes.
The outcome
Reporting you can trust, leads routed correctly, and far less time spent on manual cleanup.
Frequently asked
- Can I clean data already in my CRM, or only on the way in?
- Both. Export a batch and run it through Repair to clean existing records, and put Guard in front of new writes so the CRM stops accumulating new problems.
- Does Zapinner connect directly to Salesforce or HubSpot?
- Zapinner is an API. You call it from your sync job or integration and write the clean records back with your existing CRM client, which keeps you in control of what gets written.
- How do you decide two records are the same account?
- Matching scores records on normalized identity fields and returns a confidence value. You choose the threshold at which records merge versus go to human review.