Expert knowledge for digital decisions
How to Maintain High Data Quality in CRM Permanently?
Short answer
The Three Levers
Few Mandatory Fields. Every additional mandatory field creates placeholder entries. Three well-filled fields are more valuable than twelve with "xxx".
Input Checks. Formats for phone and email, duplicate warnings, selection lists instead of free text for everything that needs to be analyzed.
Responsible Person. Not full-time – but someone who decides how something is recorded and regularly checks it.
What Deteriorates on Its Own
| Data Type | Becomes Obsolete Approximately |
|---|---|
| Contact Person | 20–30 % per year |
| Phone Numbers | slower, but steadily |
| Company Data | with every company rebranding |
These numbers vary strongly by industry – the point is: Doing nothing is not a neutral option.
What Should Run Regularly
- Monthly: Duplicate search with template for verification
- Quarterly: Review contacts with no activity
- Annually: Clean up selection lists, remove unused fields
The Trick with the Trigger
Data maintenance as a separate task is postponed. Data maintenance during a trigger works: Whoever calls a customer confirms the address and contact person simultaneously. A small system hint when a dataset has not been confirmed for a long time works better than any cleanup action.
How to Recognize Poor Data Quality
When someone before an analysis says: "But there are still many old things in there." From this point on, no one believes any numbers anymore – and the system loses its purpose.
Key facts
- Three Levers
- Few mandatory fields, input checks, responsibility
- Most Effective Trick
- Maintenance during a trigger instead of as a separate task
Sources
All external claims are backed by traceable sources.-
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Ouhud CRM Ouhud GmbH