Optimising a customer database

Puck, 28 September 2022

We’ve talked about the importance of data in previous blogs. In the blog series on data localisation, you can read about why it’s smart to keep customer data local. You know the importance of data, but do you also know that optimizing your customer base has a lot of benefits for your business? As they say, the numbers tell the tale.

In this blog, we take you into the world of customer databases. We’ll tell you why it’s important to keep this data clean and give you tips you can start using right away.

You have a customer database, now what?

The data

Before we can talk about optimizing your customer database, let’s start with the basics. What information can you store in a customer database and what can you do with it? This database includes all of your customers’ information such as: name, address, etc. When this information is collected, entered and maintained in a structural way, you create insights that help you understand the customer better. Think about buying behavior.

Through analysis you can find out whether there are target groups within your customer base. Based on this information, you can approach your audience more purposefully and provide personalized offers. The scale of your approach is up to you. For example, do you want to address one target group with a promotion or an individual? An example of a targeted action: You sell sportswear and have noticed a trend where women between 25 and 30 often often buy yoga pants of a certain brand. You can now capitalize on this by creating a promotion aimed at this target group. An example for an individual promotion: People celebrating their birthday get an x percentage discount.

Various programs exist to help you analyze your customer database. This makes it easier to discover patterns, for example. Choose the program appropriate to your systems, goals and methods carefully. Once a system is integrated into your organization, switching to another system is not an easy process. It is also important to first optimize the data in your customer base before you start setting marketing goals. More on this later.

Saving the data

For small businesses, it is not crazy to record customer data in an Excel file. This may be an appropriate choice for a small business, but in general, most businesses use a CRM system. They do this because a CRM system makes storing, adding to and maintaining customer data and related appointments easier. Also, these systems are often suitable for much more than just these “basic” tasks. In many cases, a CRM system can also be linked to other systems such as an e-mail marketing platform and an accounting system. This will make it easier for your company to get more personal contact with your customer and to automate this process.


As a business, you can’t just store and remember all of your customers’ data; there are rules for that. These rules may limit how you can handle your customer data. Pay attention to the following:

  • Privacy: The customer data is for your company only. If you want to give this information to third parties, for example, the customer must give permission first.
  • Security: We have discussed this topic in detail in previous blogs. As a company, you have a responsibility to keep both your company’s and your customers’ data secure. Both physical and digital security. Think camera surveillance in data centers or online firewalls.
  • Transparency: The last point is transparency. Companies are increasingly being held accountable for being transparent in what data they store from customers. Not being transparent about this can come across as untrustworthy.

For more information regarding the security of your data and privacy laws, take a look at the site of “Autoriteit Persoonsgegevens“.

Qualitative data

Optimizing the customer base starts with increasing data quality. What does data quality mean? This is the degree to which the data you collect is suitable for the purposes you want to use it for. We just talked about the goals you can achieve with a properly set up and maintained customer database, for which data quality is very important. If the data is incorrect, incomplete or outdated, it can mean that you are not achieving your goals or drawing the wrong conclusions from the data you now have.

Data quality is and will always be an ongoing process. Companies sometimes see this as a burden. Our tip is to see it as an opportunity for improvement. By continuously checking, supplementing and updating your data, you also stay well informed about what is happening within your customer base.

Check your data

Data quality is important, but how do you measure it? You can do this by checking the data in your customer database with the following points:

  • Timeliness: Is the data current? Are they updated automatically? If so: does this happen regularly enough?
  • Completeness: What data do you expect and want to see in the database, and are all these data actually available? If not, you can look at the way you ask your customers for data, and adjust this approach where necessary.
  • Accuracy: Is all the data correct? For example, are there spelling errors and are the addresses, names and phone numbers still correct?
  • Consistency: Are all data listed the same in each file and system? For example, are they in the correct and equal formats. Think of a format for listing: phone numbers (+31 or 0031), dates (day-month-year) but also bank account numbers and name listing. Also check that the data are the same for each system. For example, does one system have a different phone number for a customer than another system? If so, this could mean that the systems are not properly linked.
  • Duplicate data: Is there duplicate data in the systems? It often happens that customers are duplicated in the system and again the data differs between them. You can prevent cloudy data by properly linking the systems from the beginning. For example, if a customer is registered for multiple services, this can cause problems at a later stage.
  • Clarity: Is the data clearly interpretable and understandable? It should be clear to every authorized employee what can be found where and what the data means. This is to avoid confusion and wrong conclusions.

Using these points, you can measure whether the quality of your data is good enough and you can start optimizing your customer database. Do you see that some data is incorrect, incomplete or not properly linked and therefore the data quality is low? Then this presents a great opportunity for improvement. Therefore, before you start analyzing for marketing purposes, make sure the data quality is high first.

Some final tips:

  • We will keep saying it: make sure the systems are well interconnected. This prevents data quality from deteriorating. This way you can better prevent data duplication, inconsistency and inaccuracy. It also prevents a lot of work for the future. Why? If you automate and interconnect systems, there may be no or less need to adjust and add data from system to system.
  • If you see that the data quality of your customer database is low, tackle this project by project. Set clear goals and formulate a roadmap.
  • If your company has a lot of data stored in databases, make sure IT is aware of the importance of data retention. For example, they can ensure that the systems remain technically sound and can keep up with changes on a larger scale.

Hopefully, after reading this blog, you have a better idea of the importance of optimizing your customer base by keeping data quality high.

Want to read more about data security? Then read our blog “How safe is your website’s data?

Are you looking for tips to improve the user experience on your webshop? Then read our blog “Improve the user experience of your Magento webshop“.

Puck Lamée

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