Article
Clean Data Before AI: Why a Messy CRM Makes AI Wrong
Everyone wants AI in the CRM. Almost nobody asks whether the data is fit for AI to read.
Why data decides the result
AI features read your CRM to summarise, predict and suggest. If the data holds duplicates, old contacts and deal stages nobody updates, the AI will draw wrong conclusions in a confident tone.
Five quick checks
- Duplicates: what share of contacts and companies appear more than once?
- Empty required fields: are lead source, owner and stage filled in?
- Stale data: how many open deals have not been touched in over 90 days?
- Inconsistent spelling: "PT ABC", "ABC, PT" and "abc" are three companies to the system.
- Free-text notes: does important information live only in the notes field?
Cleaning order
- Merge duplicates, starting with companies.
- Close or archive dead deals.
- Standardise pick lists for source, industry and stage.
- Make key fields mandatory.
- Decide who checks data quality every month.
Keep it from getting dirty again
Validation rules, dropdowns instead of free text, and duplicate checks at entry. A one-off clean-up without prevention only delays the problem.
When to ask for help
If the data comes from several systems or runs to tens of thousands of rows, audit first. See Zoho audit and migrating from Excel.