Energy comparison websites: Friend or foe of the energy supplier?
Energy retailers spend significant amounts of money on marketing activities to attract new customers; energy comparison websites, door-to-door, and influencer marketing amongst others. Although these channels might be promising, the value they deliver to energy suppliers is not so great. Instead, data-driven marketing alternatives that can be used to strengthen customer acquisition, retention and service processes within a marketing department are gaining ground in recent years.
How energy comparison websites work
In Belgium and the Netherlands, one of the most competitive deregulated energy retailing industries, energy comparison websites like energyprice.be or energievergelijk.nl have gained extreme popularity in recent years. The commission-based business model is built upon a commission that is paid each time one of the online visitors signs up for a new energy contract. Interestingly enough, in the Netherlands only, it is estimated that although ⅓ of customers are not really interested in exploring new energy deals, the remaining ⅔ is somehow or very interested in that. Given that a lot of customers shop around in these countries, one could assume that customer comparison websites are great tools for customer acquisition. Is this true for the long run though?
On the energy supplier side
In the Netherlands and Belgium, contracts for gas and electricity are purchased together, thereby one customer that switches energy providers usually signs up for two contracts. On the energy supplier side, the customer acquisition cost for each customer with two contracts would be around EUR 75 - 200 while the customer lifetime value is estimated at around EUR 200 - 300, depending on the channel. For example, price comparison websites typically cost around EUR 75 per customer, but customer lifetime value tends to be around EUR 200. This is due to the fact that customers a utility company is acquiring most of the time through those regular channels are very likely to shop around after 1-2 years and thereby churn, a fact which devalues this number even more. As a matter of fact, 20% of the annual energy supplier churn is triggered by price comparison websites. In addition, in most cases, energy comparison websites proactively send notifications to customers after a year asking whether they are content with their choice or if they would like to switch again. Therefore, we see that the total marketing value of these channels is not so great.
3 data-driven alternatives to acquire, retain and service customers
Utilities’ marketing departments can tap on smart meter data to optimize their processes on customer acquisition, retention and service. Here are three examples of how to do that:
1. Smart meter data to predict excessive monthly consumption
A common cause that is driving end customers to churn is experiencing bill shock at the end of the year. What is now possible with smart meter data is for energy retailers to use them in order to predict when their customer’s monthly consumption exceeds their monthly installments. Using smart meter data to calculate the KWh consumed and having this information available in a digestible way on a monthly basis can result in fewer bill shocks and fewer angry calls in customer care centers.
2. Smart meter data for personalisation
Customer acquisition cost decreases as customers remain in the utility base for a long time while at the same time, the customer lifetime value, and thus the profit, increases. It is, therefore, more valuable for utilities to invest in retaining customers and keeping them satisfied rather than investing more in the journey of acquiring new ones. What’s more, most energy retailers try to keep churn numbers lower than the intake of new customers or at least in line. They try to not wake up the sleeping customer base since they keep on paying and at the same time, try to keep the high-value customers (high consumption-driven) and offer specific cash-back retention in cash when they give signals they are leaving. Using smart meter data is now used to create better internal profiling of users to retain and determine better tailor-made plans or tariffs, which are based on their activity. The data can help to understand, target, and predict which customers are valuable, how likely is it to churn (propensity) and use this input for the marketing teams.
3. Predicting who is likely to churn
Lastly, despite the various marketing efforts, some customers will churn at the end of the contract year. Forecasting churn, however, is a significant strength for utilities to calculate and allocate optimally their marketing budget. Predicting churn is now possible with smart meter data, for example taking into account customers whose energy consumption is significantly different from last year due to extreme weather conditions or changes in consumption patterns.
Comments