Data Quality - Best Practices

Clean data, better decisions. Garbage in, garbage out. Poor data quality leads to missed payments, duplicate clients, inaccurate reports, and bad business decisions.

The 4 Pillars of Data Quality

Pillar	Definition	Example
Completeness	All required fields filled	Client has name, email, phone
Accuracy	Data reflects reality	Email is valid, phone is correct
Consistency	Same format across records	"John Smith" not "JOHN SMITH"
Uniqueness	No duplicate records	One client, one record

Impact of Poor Data Quality

Problem	Business Impact
Missing email	Email reminders and documents cannot reach the client
Wrong phone number	WhatsApp reminders cannot reach the client
Duplicate clients	Payments, notes and history are split across two records
Inconsistent naming	Clients are harder to find by search and look careless in what they receive

Data Entry Standards

Naming Conventions

• Good: John Smith, Jane Doe-Williams, Dr. Michael Johnson
• Bad: john (no last name), JANE DOE (all caps), Smith, John (last, first)

Email Validation

• Must be a valid address in the form name@example.com
• No spaces
• ClientFlow refuses an address that is not in a valid email format when you save. It cannot tell whether the mailbox exists, so re-read the address for typos.

Phone Number Format

Enter 7 to 15 digits. Spaces, dashes, dots and brackets are cleaned up for you, and a leading + is kept. Include the country code so a WhatsApp message can reach the number:

• +1-555-123-4567 (US)
• +90-555-123-4567 (Turkey)

Finding Data Quality Issues

Spotting Problems

There is no data quality dashboard or automatic report. These are the tools you do have:

• Duplicates banner: when ClientFlow finds clients that look like the same person, a banner on the Clients page shows how many possible duplicate groups there are (same email, same phone or similar name)
• Filters: in the Clients list, filter by status, tags or "Last seen" to find records that need attention
• Export: export your clients to CSV (Starter and above) and sort the spreadsheet by empty email or phone columns

Fixing Data Quality Issues

Merge Duplicate Clients

1. On the Clients page, click "Review" on the duplicates banner (it appears only when ClientFlow finds possible duplicates)
2. Each group shows why it matched: same email, same phone or similar name
3. Choose the record to keep
4. Click the merge button and confirm

Payments, appointments, notes and tasks from the other records move to the record you keep, and the merged records are archived. A merge cannot be undone, so check the group before you confirm.

Archive Inactive Clients

To tidy clients who no longer come, open the client and set Status to Inactive or Archived. A common rule of thumb is no appointment and no payment for a year. Use the status filter on the Clients list to see them again when you need to.

Preventing Future Issues

Conventions Worth Keeping

There is no validation-rule screen to switch on. These are habits to apply as you enter data:

• Email: one address per client, checked for typos before saving
• Phone: store the full number including the country code
• Amount: record what was actually received, to two decimals

Duplicates on Import

When you import clients you choose how duplicates are handled — skip, update or merge — so importing is safer than re-keying records by hand.

Maintenance Schedule

• When you add a client: Check the name, email and phone
• Weekly: Look at the duplicates banner and merge anything that is really the same person
• Monthly: Set clients who have stopped coming to Inactive or Archived
• Quarterly: Export your clients (Starter and above) and scan for missing emails or phones, and tidy up your tags

Next Steps

Look after your data to get:

• Reliable reports - Trust your numbers
• Messages that arrive - Reminders reach the right person
• Professional image - Consistent, accurate records
• Fewer records to correct - One record per client is easier to keep accurate

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Read time: ~10 minutes | Difficulty: Advanced