Clean, complete and current.
Customer data ages after onboarding. Within a year up to 20% of your records can be wrong.
Duplicate and incorrect records blur your customer view and your reporting.
Wrong addresses cost money in campaigns, delivery and acceptance.
Cleaning data through manual exports or an external party is slow and a risk in itself.
Clean at the source
DQ keeps your data clean, complete and enriched. It corrects and completes, de-duplicates, and keeps records current through real-time and batch validation. Validation runs through a closed community model, in which companies check each other's data without sharing it. Processing happens in-place, inside your own systems. No stale files, no FTP, no manual exports.
Clean, complete and always current.
One clean view
Deduplicate and correct records for one trustworthy customer view, with less noise in your systems and cleaner reporting. One record per customer, no more conflicting duplicates.
Complete profiles
Fill gaps from validated sources, with address and geo data via GeoInsights. Incomplete profiles become complete ones, ready for acceptance, marketing and service.
Never ages unnoticed
The community keeps records current in real time, without ever sharing your data. Companies validate each other’s records in a closed model, so your file never ages unnoticed.
Validated in a closed, compliant model.
DQ validates through a closed community model and processes in-place, with a well-documented API, built and run in-house.
How UNICEF keeps its donor data accurate and complete
UNICEF Netherlands relies on clean, current donor data to reach every donor with the right message. DQ by CDDN keeps that database accurate, real-time connected to Microsoft Dynamics 365.
CDDN thinks along, responds fast, and understands exactly the level of care an organisation like UNICEF requires.
Real-time
Connected to Microsoft Dynamics 365
Always current
A continuously accurate donor database
GDPR-proof
Validated in a closed, compliant environment
From audit to clean, kept clean.
Intake
We discuss where your data hurts today.
Data audit
We measure your file's quality: duplicates, errors, gaps.
Implementation
We set up cleansing, enrichment and validation, in‑place.
Optimisation
We keep the data clean and adjust as you go.
Frequently asked questions.
Does my data leave my own environment?
One-time cleanup or ongoing?
Does it integrate with my CRM?
What can DQ enrich?
Who owns the data?
See how clean your data really is.
Request a data audit and we'll measure your file.
Request a data audit