How can you identify duplicate data in your CRM?

1. Scan for Similarities:Look for identical names, email addresses, or phone numbers. It's like finding twins in your contacts! 2. Smart Tools:CRM systems often have built-in duplicate detection. Activate it—it's your CRM's detective, uncovering those sneaky duplicates. 3. Regular Audits:Schedule regular check-ins. It's like dusting your CRM shelves to keep it tidy and efficient. 4. Consider limiting the master data integrity to one single department or person depending on organization size and need. Having a customer master manager that is responsible for ensuring all data is entered in the same format with the same attributes will help improve data integrity and sales reporting as well as forecasting.

Probably the easiest way is to match email, first and last name. What's more important is that it's done. You need a "clean" database to guard against internal conflicts and prospect overlap.

Durch eindeutige Kundenprofile werden doppelte Daten erkannt. Das Ziel besteht darin, Profile aus unterschiedlichen Datenquellen zusammenzuführen. In einer Gesamtl?sung mit CRM- und MarTech-L?sungen entsteht ein Profil für jeden Kunden, das alle relevanten Daten beinhaltet. An dieser Stelle werden Duplikate erkannt, wie zum Beispiel separate Profile aus Online- und Offline-Aktivit?ten. Dieses umfassende Bild eines einzelnen Kunden erm?glicht das Ableiten individueller Kundenbedarfe sowie das Vorhersagen von Verhalten, beispielsweise im Rahmen der Churn-Pr?vention.

Your CRM might not have a built-in feature for duplicate detection and record merge, or the feature might just not rise up to the standards (because, let's face it, that is sometimes the case...). Third parties come in very handy here, especially if you're working with large volumes of data; ifb that's the case (please) consider tools like Dedupely, Dropcontact, Insycle, to name a few, ahead of looking at manual deduplication methods. If you are using a CRM like Dynamics (which the third parties above do not integrate with), there are bespoke tools you can explore, like automerge or dq.

The best practice is to define the data strategy across the enterprise supported through third party tools embedded into your data platform along side to interbal tools. As internal tools will limit the deduplication only to the CRM application but policies, standards and controls needs to be implemented through out the value chain. Keep it simple but effective through data governance and master data management.

This is the most important aspect as continuous monitoring and reviw process is needed as part of enterprise information management strategy. Once data integration and infornation managenent pipelines are ready and in production, there needs to be proper post deployment monitoring measures to be implement with proper data checks. A data control tower should be implemented to ensure upstream and downstream data management.

I recommend that if your CRM doesn’t have a built-in data management tool, you get your data out into Excel so that you can more easily manipulate and review it.