In this series, we will take an in-depth look at our current analytics projects in the utilities sector. We will primarily allow data scientist Jan Vercammen to speak to clarify the synergy between sector and solution. In the previous series, we already discussed the Customer Journey tooling and the Churn insights Tool. Today, we will tell you more about another innovative project: tariff setting with Smart Meter Data.
Smart Meter Data for the fast-changing utilities sector
The utilities market is in a constant state of flux and there’s an unmistakeable need for innovations. Obviously, utilities want to stay profitable. However, at the same time, they have to continue offering their customers an impeccable service. Quite a challenge, because customers are becoming more and more demanding and seek more control over their consumption and costs.
On top of which, smart grids have to support consumers who are increasingly shifting to become prosumers themselves. In short, the focus of the utilities sector is shifting to green energy and today our energy streams must be ready to handle two-way traffic. To provide an answer to these new issues, AE started in co-creation with a utilities partner a proof of concept to utilize the data of a smart grid. A crucial element of this smart grid are the digital meters.
Personalised tariff plans
Earlier, the regional governments in our country introduced regulations that enabled the use of these new energy meters. These meters reveal a wealth of information about the consumption patterns of families, something the utility sector has been monitoring for years. We are all familiar with the principle of day and night tariffs. Our utilities partner wanted to take things one step further and develop personalised tariff plans.
3 customer profiles in the utilities sector
We wanted to put our utilities partner’s ambitious plan to the test. In collaboration, we created different customer profiles on the basis of data obtained from digital meters. We set up a pilot project and went to work with the data of British restaurants and bars. We analysed the data and processed them using various algorithms. As a result, we arrived at three customer profiles. Jan Vercammen explains our working method:
“With this pilot project, we wanted to come up with algorithms capable of gleaning patterns from Smart Meters. First off, we determined the profile of the classic restaurants that offer both lunch and dinner. In addition, we also discovered the restaurants that provide continuous daytime service, such as cafés with a limited menu. And finally, we put together a profile including brunch spots and bars.”
An innovative future
“Defining the profiles is only a first step,” Jan continues. “We could, for instance, also look at the fluctuations of tariff settings over time. We have taken all challenges into account in this nifty tool. As we can make all insights tangible with the aid of this tool, the data science team can confer with business analysts in bite-sized language. Thanks to the smart meter data, our customers no longer have to take decisions based on gut feeling and are headed towards an innovative future of well-founded decisions.