Solutions
Data Cleanup
Cleaning the data once is a project. Keeping it clean is a configuration.
Dirty data is a symptom of an input design that permits it. We run the cleanup — duplicates, formats, invalid addresses, orphaned records, dead contacts — and then close the door: required-field rules, validation at entry, deduplication on create, and a monthly quality report that names the source of new defects rather than the person who typed them.
- 01
Duplicate detection and merge with survivorship rules
- 02
Format standardization for names, addresses and phones
- 03
Validation of email deliverability and contact status
- 04
Orphaned and stale record resolution
- 05
Entry-point validation to prevent recurrence
- 06
Monthly data quality reporting
FAQ
How bad is typical mid-market CRM data?
Duplicate rates in the low double digits are common, along with a large tail of contacts that have not been reachable for years.
Do you delete records?
Only under rules you approve, and archived rather than destroyed until you confirm the outcome.
Is enrichment worth it?
For firmographic fields used in routing or segmentation, often yes. For fields nobody reports on, it is expense without benefit.
CRM Migration
A cutover your sales team does not notice, and a reconciliation report finance can sign.
Reporting Automation
One number per metric, defined once, produced automatically, and agreed across departments.
Document Processing
Structured data out of unstructured paper, with the uncertain cases sent to a person.