The impact and potential of data
When you think of data, quickly privacy comes to mind. Within the KPN Data Office, nine data principles are maintained, with which the company ensures, for example, that data is compliant. Stephan: 'But the timeliness and reliability of data are also included. Within KPN, the Privacy Office ensures that the privacy of customers is safeguarded. If we want to implement a new type of data use, we always check it with the Privacy Office to ensure that we comply with both the AVG and the customer's expectations. Usually, we are even a bit stricter than the AVG with that.'
The Adobe Experience Platform is currently being implemented at KPN. It is an open system, suitable for building and managing solutions for various customer experiences. This enables KPN to centralize and standardize its customer data and content from every system. Using data science and machine learning, personalized customer journeys should ultimately be improved.
This sounds wonderful on paper, but in practice KPN has an enormous amount of data and using this data has an impact on millions of people. Setting up the various systems at KPN to get the right offer to the customer is a challenging puzzle, says Anastasia. ‘There are several challenges. The first challenge is the amount of data. There is simply so much data and sometimes we can't process it all. Secondly, a mistake can have huge consequences, so we must triple check everything before we do anything and run lots of experiments to make sure it's right.'
Then there is also the issue of noisy data; meaningless, meaningless data. How do you deal with that? Some data may not be that important or relevant and recognizing them is a matter of experience. By consulting a lot with colleagues, we learn to recognize them better and better, but smart models can also help us with this,' says Anastasia.
At the same time, the question arises: 'What would be the impact if KPN did not take the trouble to make an appropriate offer to its customers? Anastasia is honest about this: 'The impact is still quite small now, because we are not as far yet as we would like to be with personalization’s. We can do much more, use more data, unlock more sources. That has huge potential. If we do not do those experiments now and learn those lessons now, we will be empty-handed in the future. Then customers will probably get an inappropriate and boring offer that does not suit them at all. Data analytics is mostly very new, but the learning effect is huge. If we build on what we have already learned, we will be able to do much more in the future and that will make our customers happy too.'
Stephan adds: 'We are now trying to present several generic options for all customers. We do this based on data, but it results in rough options, while we want to be much more specific. Realizing this in all systems is a huge operation, but one that we have embarked on with great conviction.
One customer data platform
The Adobe Experience Platform could therefore change a lot in the future. Built on RESTful APIs, it opens the system to developers so that business solutions can be easily integrated using existing tools. Partners can also build and integrate their own products and technologies as needed. In addition, it uses Adobe Sensei, artificial intelligence (AI) and machine learning (ML) technology, to automate tasks, personalize customer experiences and predict customer data.
Stephan illustrates the functionalities of Adobe Experience with several examples. If you as a customer have just purchased a new digital TV subscription from KPN, it is not logical that a few hours later you will see a banner or receive an email offering the same service. Logically, that customer would not need to see that offer again. Another application is in the event of (service) disruptions, for example. If a customer has looked up a number of things and filled them in online, in an ideal world you would want the helpdesk - provided the customer has given permission of course - to have access to these details. In this way, the customer does not have to explain the same story a second time during an actual customer contact.