The Netherlands is constantly changing. If we look at CBS data, we see that on an average day, more than 5,000 Dutch people move, 460 children are born, 462 compatriots die, 205 couples get married, but 272 marriages are also dissolved. Sorrow and joy alternate with all these life events at record speed. In the hour that you enjoy your cheese sandwich or make a video call, there have already been more than 200 moves and 20 children born. That adds up quickly!
How do all those life events affect a database?
Viewed through a customer data lens, every move, wedding, or funeral is a change that affects the quality of the customer data. For example, you work at a large company with 500,000 customers. All important data such as last name, age, home address, and telephone numbers are collected in a nice database. What if we let the ravages of time do their work for one or three years and we don’t look at the data quality. What will the customer data be like after a while?
The calculation example below shows that the quality of the data deteriorates very quickly. After one year, about 15 percent of the database is no longer up-to-date. After three years, that is already 45 percent. And that is based on only three variables and in an optimal situation in which the database is complete and up-to-date. Unfortunately, that is not how it works in practice. Mistakes are regularly made when entering data. Not surprising, because the more people enter customer data, the greater the chance of errors.
What does the GDPR say about this?
It is generally known that data quality says something about the suitability of data for the ultimate purpose. Less well known is that the GDPR even specifies what organizations must do to achieve the quality of customer data:
”Personal data must be correct and, if necessary, updated; all reasonable measures must be taken to erase or rectify („accuracy”) personal data which are incorrect, having regard to the purposes for which they are processed, without delay;”
Users of and those responsible for customer data therefore have a considerable challenge on their plate.
Customer services, communication, marketing, finance and IT
Which company in the Netherlands is not data-driven these days? Data is the fuel on which companies grow, a way to stay ahead of the competition. More and more professionals are realizing this. From the work floor to the boardroom. That is why data quality has been given a prominent place on the list of business-critical processes. And rightly so. All the more so because the dependence on and responsibility for data is cross-departmental. Customer services wants to help and retain customers, the communication department wants to communicate relevantly, marketing and sales go for the optimal reach and return on investment. The finance department wants customers to meet their financial obligations and IT realizes all too well that applications and infrastructure are worthless without data. Despite the fact that everyone knows this, correctly recording customer data and keeping it up-to-date is still a major challenge. The results of our benchmark confirm this.
Benchmark customer data of the BV Netherlands
For our benchmark, we analyzed the data quality of almost a hundred companies. We wondered: how up-to-date is the customer data? And how correctly is customer data recorded? A few striking results:
- The age group is not known for 30% of customers;
- 13% of the customer base has moved;
- A database contains an average of 5% of customer data from people who have since died;
- 70% of existing customers cannot be reached by telephone due to missing information.
It is evident. There is still much to be gained in the field of data quality.
We are happy to help you further
You have probably become convinced of the importance and necessity of data quality. After all, as an organization you want to comply with the GDPR but also be data-driven. But where do you start? Know that customer data must meet the ACCU principle. Customer data must be Up-to-date, Correct, Complete and Unique. These are the prerequisites for optimal data quality. You can read which three steps you need to take for this inthis customer case from online department store Klingel.