Does your CRM application contain incomplete, outdated or duplicate customer data? Undoubtedly, because data quality degrades quickly. People change jobs, people and companies move, streets sometimes change names or are renumbered, companies merge or close down, organizations change their commercial name, etc.
If there is no systematic approach, the data quality in your CRM application can go badly wrong. And poor data quality is harmful to your marketing, sales and services.
In case of poor data quality in CRM:
Result: you lose the 360° view of your customers and that’s harmful for your CRM strategy.
We can say that data quality is everyone’s business. It is certainly the case that every employee must contribute to correct data in CRM. Nevertheless, we recommend giving specific employees in your organization the role of “data manager”. Then you givethese employees access to the necessary technical tools to work on data quality.
In addition to the technical tools, an action plan is also needed. Please note that for this action plan there is no “one-size-fits-all” because the correct action plan differs from organization to organization.
Below we provide an overview of measures that can be part of an effective action plan in the fight against poor data quality.
You can automatically assist employees for data entry by:
💡 Extra tip for mandatory entry fields: try to find the right balance so that your employees are not blocked from creating accounts or contacts in CRM. For example, you can automatically adjust mandatory entry fields according to the user profile and the step in the business process. For example, limit the mandatory data when creating a “sales prospect” in B2B to first name, name, email address, position and company name. Once this prospect becomes a customer, you can also automatically make the billing address and company number mandatory.
Make your end users aware of the importance of data quality:
If an end user doesn’t follow the agreements, we advise to adjust the security rights of that specific user.
Also, always think about who you want to give the rights to:
Always pay attention to give rights to delete data. Avoid that data quality management would lead to data loss. That is why we recommend being extremely careful with Delete permissions.
Duplicate data results in confusion and an incomplete customer view if the related data is spread across two or more customer records. The solution against duplicates is: prevention and remedy.
Preventive steps are:
Even if everyone does their best… “duplicates happen” ;-). How do you solve duplicate data? By regularly performing duplicate detection in your CRM application and merging the duplicates found (i.e. merge duplicates). If you are merging the duplicate records, choose the master record to which all related data should be relinked. At the level of the record itself, you can even choose at field level which information you want to appear on the merged record.
A powerful tool to keep the quality of customer data correct is to integrate your CRM application with other reliable data sources. This allows you to automatically enrich, revise and keep customer data up-to-date.
Some examples of reliable data sources to integrate with (depending on your specific business purpose):
Data quality is a never-ending task for a data manager and every employee with the necessary rights.
Tasks that the data manager must do regularly:
What if an employee discovers a problem with data quality, but does not have the necessary rights to solve the problem? Optionally, you can give regular users the option to indicate records in your CRM application to be checked by the data manager. Of course, the list of these indicated records must be followed up regularly.
The data quality in your CRM application is very important! So get started right away with the tips in this blog article to keep your data in CRM reliable and usable.
Do you want to improve the data quality in your CRM application in Microsoft Dynamics 365? Let Net IT guide you in determining the most appropriate approach.
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