The global energy sector is changing rapidly, and the key driver behind this revolution is data. In the UK, regulation and policy – along with better-informed and more demanding consumers – have played their part in phasing out the traditional ‘single provider, single contract, forever’ model.
It is vital for energy service providers to embrace the opportunities provided by analytics and data harvesting in order to increase customer reccomendations and thus retention. A benefit of new technologies that utilise artificial intelligence (AI) is that they analyse customer habits and data, allowing energy service providers to have granular insights into what their customers want and need.
Changing the model
Arguably, the biggest changes are taking place at the provider end – in order to keep consumers happy and maintain their loyalty. Customer service should be a priority for all firms, but a provider that is asking homeowners to commit to a monthly spend cannot afford to be careless regarding its user experience. Moreover, with an increasing number of newly-empowered and savvy customers deserting the old contract model (helped by smart meters and data-driven support for switching), energy companies are adapting their offerings to give domestic and commercial consumers what they want, how they want it.
A recent Ofgem-commissioned study of consumers’ engagement with the energy market reports that UK purchasers are increasingly willing to engage with providers, with the comparison of tariffs and provision (and switching in light of this) becoming increasingly normal behaviour. Interestingly, another Ofgem survey, this time of businesses, suggests that enterprises are now less inclined to switch and that this is frequently due to satisfaction with their current supplier. So it seems that both price and service quality are involved in the choice of provider, and energy suppliers must deliver on both fronts.
One response to this situation is the provision of energy as a service (EaaS), whereby the provider assumes some of the risk traditionally assigned to the purchaser, and provides energy at a fixed price, based on its prediction of the client’s likely use. EaaS is one solution for businesses that need to benefit from the ability to budget for known expenditure. For providers, there is also the security of assured income, but furthermore the chance to increase profits through fluctuating energy prices, and by managing energy stocks efficiently. This efficiency can take many forms, including the use of renewables and on-site and remote energy storage.
Forms of energy provision to homes are also evolving. In April 2018 in London, the first peer-to-peer energy exchange was completed over blockchain. Solar energy generated by panels on a block of flats was allocated to residents on the basis of their usage profile. Via blockchain transaction, excess energy from several panels was sent to a user in a nearby (but different) building.
Many predict that blockchain transactions will become increasingly important to the energy sector. Not only for peer-to-peer energy sharing, but also due to their potential for speeding up transaction switches and as an unbiased and indisputable record of truth in an increasingly fragmented and fast-moving marketplace.
The evolution of AI
All of these changes rely heavily on data; to predict, profile, administer and assess costs. We are living in the age of big data, and this is being fuelled by the increased usage of AI, which can mine, format and deploy information in ways and speeds beyond human capability.
What’s more, AI — as voice assistants and applications such as Google Home and Alexa — is making its way into the homes of consumers, where it can monitor and profile energy use. Some examples are when a light is switched on, or when a kettle is boiled – activities that can link to an in-house smart meter. Amazon’s Echo device series, which uses Alexa, currently has five different models to suit the preference of the customer. These devices already allow Amazon customers to purchase items, play music, make and receive calls, and provide information on news, sport and weather – and could, very soon, go one step further in assisting users. As Alexa already holds the ability to make payments, it could not only understand a homeowner’s profile, energy needs and preferences (i.e. renewable energy), but also provide energy recommendations and manage a supply contract.
Future advances may enable these devices to inform listeners of the best ‘daily energy deal’ that is suited to them, based on ‘her’ understanding of their energy use – enabling smart switching and micro-contracts that ultimately benefit the end user.
The latest research in this field of technology shows that domestic use of AI is destined to grow substantially: PwC reports that while just ten percent of consumers taking part in its research owned an AI device at the time, many more had definite plans to purchase an AI device. With more people planning to purchase AI devices for their homes in the near future, companies should be developing ways to use the data that is gathered to their advantage in order to gain and retain customers.
These insights can then be used to enable suppliers to create offerings to suit the customer, placing them multiple steps ahead of the competition and reduce switching volumes. Customers would in turn benefit from the use of data, receiving offers and deals based on their consumption of energy, and find great value deals tailored to them.
Regardless of the finer details, whether customers turn to Alexa, Google or their smart meter for the information they need, data is a vital force behind the transformation in the energy sector – and presents myriad opportunities that providers could and should be exploring to develop a competitive edge. Energy suppliers who ignore the benefits that increased data mining can give them do so at their own risk, and face the prospect of losing previously loyal customers to their competitors.
Dominic Carlyle, Technology & Innovation Director at Netcompany
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