In this article
Before cleaning: know how bad it is
Export contacts, companies and deals and look. Count the duplicates by phone number and by company name; the records with no owner; the deals with no activity for six months still open; the required fields blank; the phone numbers with and without country codes; the contacts with no company and companies with no contacts. Half an hour with a spreadsheet gives the size of the job and the order to do it in.
Decide who does the cleaning — the CRM champion with a fortnight of half days, or a service if the volume is large — and who signs off what gets deleted, because deletion is the step nobody wants to own.
Define ownership, standards and required fields
Ownership: every record type has an owner role — deals belong to the salesperson, companies to the account owner, the contact database to the coordinator — and every record has a named owner. A record nobody owns is a record nobody maintains. Standards: how a company name is written — the legal name, as on the GST certificate, with the trading name in another field; how phone numbers are stored — ten digits with the country code, no spaces; how addresses are structured; which pick-list values exist for industry, source and stage, and no free text where a list should be. Written on one page, and configured into the CRM as validation where it can be.
Required fields: the few a decision depends on at each stage — a contact needs a phone and a company; a deal needs a value, a stage, an owner and a next action; a company needs an industry and a city. Everything else is optional. A record is complete when those are filled, and the CRM should say so.
Deduplicate, normalise, validate and archive
Deduplicate first, by phone and email for contacts and by name and GST number for companies, merging into the record with the most history and keeping every activity. Most CRMs have a merge tool; use it record by record for the important accounts and in bulk for the tail. Normalise second: phone numbers to one format, company names to the standard, free-text industries mapped to the pick-list, dates in one form. A spreadsheet pass with find-and-replace does most of it; the rest is manual. Validate third: the important records checked against reality — a call to confirm the contact is still there, the accounts system for the legal name and address, the website for the industry — starting with the top accounts and the live deals.
Archive last: deals with no activity in six months closed as lost with a reason of “no response”, contacts nobody has spoken to in three years and companies with no activity moved to an archived state rather than deleted — visible if needed, out of every view and report otherwise. Deleting is rarely necessary; archiving is what makes the working views clean.
Prevent future decay through workflows and governance
Data decays at the point of entry, so the fixes go there: validation on the phone field, pick-lists instead of free text, duplicate detection when a record is created, required fields enforced by stage, automatic formatting where the CRM allows. Integrations that write in — the website form, WhatsApp, email — mapped to the right fields so they do not create a second record for an existing customer. And ownership rules: a record without an owner is assigned automatically; a deal with no activity for sixty days flags the owner; a contact who has left is marked, not deleted.
Governance is one person and a monthly half hour: duplicates created this month, records missing required fields by owner, stale deals, the pick-lists that grew. The numbers go to the team as a group, and the person whose records are consistently incomplete gets help, not a memo. Once a year, a proper re-validation of the top accounts.
Checklist · use it here or print it
CRM data-cleaning checklist
Three groups: set the standard, clean to it, and stop the decay. A clean-up without the third group is repeated in a year.
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Mistakes, measures, and what clean data does
The mistakes: cleaning without a standard, so the mess returns in a quarter; deleting instead of archiving; merging duplicates and losing the history; cleaning everything at once rather than the live records first; no validation at entry; and no monthly check, so the job is done again in two years. A safeguard: after cleaning, pick twenty customers at random and check the record against a phone call — that is the real completion test.
Measure by duplicate rate, required-field completeness by owner, stale open deals, and — the outcome — whether the team uses the CRM’s views instead of asking each other. Clean data makes the pipeline number believable, the morning list right, the marketing source report honest and the reactivation list usable. This is the data-cleansing and governance work we do — the standards page, the cleaning in order, the validation at entry, the integration mapping, and the monthly governance routine handed to your champion — and the free audit starts with the duplicate count from your export.
Questions owners ask
How long does cleaning a CRM take?
A fortnight of half days for a few thousand records with a standard written first; longer if the standard has to be argued about. The live records — top accounts and open deals — come first and take a few days.
Should we delete old records?
Archive rather than delete: out of the views and reports, still there if a customer returns. Delete only true duplicates after merging, and spam. Deleted history cannot be recovered.
How do we stop duplicates coming back?
Duplicate detection at entry, integrations mapped to existing records by phone or email, pick-lists instead of free text, and a monthly duplicate check. Most duplicates are created by the website form and WhatsApp writing in unmapped.
Who should own data quality?
One person — the CRM champion or the coordinator — with a monthly half hour and the authority to change fields and pick-lists. Every record also has an owner responsible for its completeness.
What is the minimum standard?
One page: how names, phones and addresses are written, which pick-lists exist, and which fields are required at each stage. Configured into the CRM as validation wherever the product allows.
What does GullySales do?
The export analysis, the standards page, the cleaning in order — deduplicate, normalise, validate, archive — validation and integration mapping at entry, and the monthly governance routine set up with your champion. Scoped in the free audit and priced in writing.