Data management. Everyone finds it important, yet it often goes wrong. Both in large and small organisations. A missed opportunity! Because ensuring good data quality requires little effort and quickly pays for itself. In this blog, we describe the main causes of data pollution, including practical tips to ensure data quality.
Advantages of optimal data quality.
Current address details, the right names of contacts, the size of a company: all important information for good marketing and sales. After all: the higher the quality of this data, the better you can target your target audience and the higher the conversion will be. The benefits of good data quality far outweigh the costs. You also save on your operational expenses: mail, e-mails and phone calls that end up with the wrong persons or companies do not yield anything. Worse yet: they only cost money.
So why is there so much data pollution?
The reason why the quality of customer data tends to lag behind is often laziness. Filling out the customer system is not a priority to the sales department – and is sometimes even an irritating factor. The consequences are obvious: incomplete or sloppily entered customer data. This results in errors: Mr Janssen is approached as Ms. Jansen, or you address Mr De Jong even though you wanted Mr De Vries. And that could mean missing great opportunities with these prospects! Mutations are also an important cause of data pollution. Companies and people are always in motion, causing the data of your customers or prospects to change continuously.
Practical tips for good data management
- Choose a web service to ensure the data quality. This is a link between your CRM and an external database. This link ensures that the data in your system is automatically supplemented or corrected, even with mutations. Read more about this here.
- Ensure a number of required fields in your CRM that need to be filled out in order to continue. This creates a good foundation.
- Do not make the number of required fields too great; it is better to have a couple good, fully complete instances of data than a lot of half ones. There are companies who maintain dozens of fields, from birthdays to the number of children and whether or not someone is interested in golf. This level of detail only generated more annoyance for the sales department and does not contribute to the data quality.
And lastly, our favourite: link an incentive to correctly entering customer data. This way, you not only reward your sales people for sales, but also for accuracy. This certainly improves the data quality. It works for us!
