Why records decay
Customer data goes out of date even when nobody does anything wrong. People change jobs, move, switch email addresses and close accounts. Staff enter details differently, import files from several sources, and create second records for people who are already listed. Left alone, a database slowly becomes less reliable, and once people stop trusting it they stop using it.
Data hygiene is the set of routines that slows this decay. It is mostly small, repeated habits rather than occasional big clean-ups.
What bad data costs
The effects are practical and often subtle.
- Emails go to the wrong person or bounce, which can harm sending reputation. The effects on delivery are explained in the discussion of email bounces.
- Two staff members contact the same person without knowing.
- Reports overstate the number of customers because of duplicates.
- Segments are wrong, so people get irrelevant messages.
- Time is wasted searching and double-checking.
These costs are hard to measure precisely, so avoid inventing a figure. Simply noticing where bad data causes wasted effort in your own business is a sound reason to act.
Prevent problems at the point of entry
It is easier to keep data clean than to clean it later.
- Use consistent formats. Decide how to write phone numbers, countries and job titles, and use dropdowns where you can.
- Mark required fields sparingly. Require what you truly need, and no more. Too many required fields push people to type junk.
- Search before creating. Make it a habit to look for an existing record before adding a new one.
- Validate on forms. Basic checks for an email format catch obvious typos.
- Record the source. Knowing where a record came from helps you judge how reliable it is.
- Collect less. Every extra field is something else to maintain, a point developed in the article on contact fields.
Deduplication
Duplicates are the most common problem. They arise from imports, from different spellings of a name, and from people using more than one email address.
A reasonable routine:
- Find likely duplicates. Many tools offer a duplicate report; otherwise sort by email address, then by name and company.
- Decide on a master record. Usually the one with the most complete history.
- Merge carefully. Check that notes, deals and activity are combined and that nothing important is overwritten.
- Be cautious with similar names. Two people with the same name at the same company are not necessarily the same person.
- Back up first. Take a copy or export before any bulk merge, as merging cannot always be undone.
Schedule this monthly or quarterly, depending on how many records you add.
Regular updates
Choose rhythms that fit your size.
- Weekly: fix obvious errors you spot, update the status of active deals, and log new contacts.
- Monthly: review duplicates, look at records with missing key fields, and check the bounce and unsubscribe lists.
- Quarterly: check for contacts with no activity for a long time and decide what to do with them.
- Yearly: review the field list, the tags and the retention rules.
Email lists need a similar routine of their own, covered in how to keep your email list clean under the heading of list hygiene. If your CRM and email tool are separate, make sure unsubscribes and bounces flow back to the CRM.
Give records an owner
Data that belongs to everyone is looked after by no one. Assign responsibility at two levels.
- Record owner: the person responsible for each customer relationship. They update details when they speak to the customer.
- Data steward: one person (even part-time) who runs the routines above, keeps the field list and handles questions.
Write down who does what. When a team member leaves, reassign their records rather than leaving them orphaned.
Retention and deletion
Keeping everything forever is not neutral. Old records can be inaccurate, and holding personal data longer than necessary may breach privacy rules in some places. Decide how long you keep different kinds of record, for example inactive leads versus customers with legal or accounting obligations, and what happens at the end. Requirements vary by country and change; this is general information, not legal advice. The practical side of responding to people who ask to see or delete their data is covered in the article on data subject requests.
Keep a small log
Note what you did and when: merges, bulk edits, imports and deletions. If something goes wrong later, the log helps you work out why. It also makes the routines easier to hand over.
Start small
If your data is already messy, do not try to fix everything at once. Pick the most valuable segment, such as current customers, clean it first, and apply the entry rules to all new records from now on. Accurate data is a continuing effort rather than a finished state, and the aim is records good enough to rely on, not perfect ones.