Data Check & Clean Up

A foundation you trust.

Before processes and AI work on your data, we clean up: merging sources, resolving duplicates. GDPR-compliant, and without bringing your operations to a halt.

Request a free data check → Parallel infrastructure · your system stays live
  • $12.9M Cost per year is what poor data quality costs a company on average. Gartner 2020
  • 22.5% Data decay of your contact records lose their validity every year: job changes, relocations, renamings. HubSpot, Database Decay
  • ×100 Cost of errors Preventing costs 1, correcting 10, doing nothing 100 per record. A rule of thumb, not a measurement. 1-10-100 rule, Labovitz & Chang 1992
  • 4% GDPR fine ceiling of global annual turnover can fall due for violations. Deletion deadlines and consent hang on the state of your records. GDPR, Art. 83
How it works

Four steps to a clean dataset

We work on a copy in a parallel test instance. Your live system stays untouched until you sign off.

  1. 01

    Legal footing & scope

    Before we see a single line of your data: NDA and data processing agreement. Then we decide together which sources and records go into the check.

    NDA DPA
  2. 02

    Transfer & analysis

    A copy of your records goes into a test instance on EU servers. There we analyse duplicates, gaps and stale entries, and run the clean-up. The original stays untouched.

    Test instance Clean-up
  3. 03

    Validation & sign-off

    You see every intervention: what was merged, corrected or archived, with samples and a report. Nothing goes live without your sign-off.

    Corrections Report
  4. 04

    Implementation

    The cleaned dataset goes into your system, documented and with rules that prevent new sprawl: required fields, duplicate checks, clear ownership.

    Data live
In detail

What happens in the clean-up

  • Duplicates Merged, not deleted. The most complete version wins, the history is kept.
  • Formats Standardised. Phone numbers, addresses, salutations and company names follow one standard.
  • Stale records Checked and decided. Update, archive or delete in line with the GDPR, by rules you sign off.
  • Enrichment From open sources. Company register, website and public directories fill the gaps in your records.
  • Structure Fields that mean something. Required entries, pick lists and ownership instead of free-text sprawl.
  • Report Traceable. What was found, changed and recommended is in a report your management can read.
What comes after

Clean data is the beginning

  • CRM & processes

    More deals through data

    On the clean dataset we build pipeline, required fields and follow-ups. The CRM starts working.

    To CRM Services →
  • AI & automation

    Make your data usable

    Processes run on their own, and AI works on a foundation that fits.

    Learn more →

Trust your data again.

Tell us where your data sits and what bothers you about it. We will tell you what a check finds at your company.

Request a free data check

No-obligation intro call · personal reply · no ticket queue