How to improve data quality in your CRM application?

Why is data quality in CRM so important? 💡

Does your CRM application contain incomplete, outdated or duplicate customer data?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:

• in the worst case scenario, your data is considered as not reliable and therefore simply not usable.
• your employees will ignore the CRM tool and they will again manage their own lists.
  eg. the account manager manages his list of customers with associated contacts in his own Excel file.
  eg. the marketing employee does not want errors in email campaigns and starts his own lists of email addresses in a separate digital marketing tool that is not linked to your CRM application.

Result: you lose the 360° view of your customers and that’s harmful for your CRM strategy.

Data quality in your CRM application: a shared responsibility?

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 give these 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.

Start at the source: quality before data input

You can automatically assist employees for data entry by:

• automatically validating entered data through a consistent format of specific data; such as company numbers, telephone numbers, email addresses, etc. You usually use regular expressions.
• where possible, completing data automatically as much as possible; such as automatically filling in the municipality and province as soon as the zip code is entered.
• building consistency rules to make invalid combinations of data impossible; for example, if one specific field contains value X, then the other field must contain value Y.
• where possible, using picklists or add auto-suggestion to free input fields; as for entering a country.
• making necessary data mandatory to avoid incomplete input.

💡 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.

End user training

Make your end users aware of the importance of data quality:

• communicate who in the organization uses the data, for what purpose and what problems can arise due to poor data quality. Set clear expectations regarding contact management so that everyone takes their own responsibility.
• devide responsibility. It’s obvious that an account manager is responsible for the data quality of contacts of his own customers.
• define clear rules. What is poor/good data quality? What do you do with abbreviations? eg. “Pvd Wouwerstr.” or “Pastor of the Wouwerstraat”. Be sure to update these rules if new problems arise.

Re-evaluate who may or may not manage your contact database

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:

• create or edit Contacts, Accounts, Leads.
• perform “Bulk Edits”, “Export for reimport” & “Imports”. There is always a risk that Contacts are stored in your CRM application with incorrect data. Import rights are not for every user anyway.

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 customer data

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:

• when creating and updating a customer record: provide an automatic message to the user that the CRM system has discovered a duplicate.
• With automatic data inflow (e.g. via an online form): ensure an automatic search of possible matching contacts (via exact or via fuzzy search). This way, the existing contact can be linked instead of creating a new duplicate contact.

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.

Integration with third party data sources

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):

• Trends Top
• Verrijkte Kruispuntbank Ondernemingen
• Graydon
• LinkedIn Sales Navigator. For example, there is a standard integration between Dynamics 365 & LinkedIn Sales Navigator.
• …

Create an action plan

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:

• perform “Advanced Find” queries of Contacts, Leads, Accounts with missing or incorrect data, to discover records of poor data quality.
• run duplicate detection.

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.

Conclusion

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.