Electricity retailers have experienced a steady rise in new competitors, and an increase in customer churn in the wake of deregulation. And with that comes an increased pressure on prices, according to a recent McKinsey & Company report.
The rate at which customers churn (the number of customers shopping around and moving from one retailer to another) tends to indicate their level of engagement in the market. The greater use of comparator websites is also highlighted by McKinsey as a factor in the rise in churn rates.
While the report says that energy retailers are “feeling pressure” due to increased churn, it also believes that companies now have a new tool in the form of personalisation, which can help to individualise the interests of customers based on their behaviour and help companies to manage, attract and retain customers. It points to four key factors that can help extend personalisation to electricity retailing, which we consider below.
Not only can businesses target their customers through more personalised communications, but McKinsey state that consumers now expect it. Research shows that 74 per cent of customers find mass marketing frustrating, especially as they are increasingly exposed to personalised communication from other retail sectors.
Personalisation stems from retail and customer goods marketing of consumer preferences and attitudes. According to McKinsey’s research, across these sectors, effective personalised online content has delivered a five to eight fold improvement in the cost of marketing with customer acquisition costs falling by almost 50 per cent.
McKinsey state that personalisation could bring many benefits in the energy sector; energy companies struggling with increased customer churn could use some of the lessons shown from other retail sectors to manage, attract and retain their customer base.
One challenge though is that with a more limited set of offerings, the energy sector differs from other sectors, such as fast moving consumer goods. And in the National Electricity Market a further challenge is the re-regulation of prices that has the potential to curb the opportunity or incentive to innovate.
McKinsey’s report says that energy companies often struggle to capture and generate valuable insights from customer data, and despite the advantages of personalisation, many energy companies worry they might upset customers or lack the data they need for more personalised marketing.
McKinsey contends that many energy companies already possess the analytical and technical skills required for more efficient and targeted communications, and need to “take the first step on the personalisation journey” to start tapping into its “enormous potential”.
It says that personalisation can play a pivotal role in the energy sector: location and housing data can be utilised to target customers who have an above average energy consumption, while looking at past customer behaviour, could also help to identify who may be interested in smart home devices. When a contract comes up for renewal, the energy provider could draw on personalised information for a more tailored offer.
Making personalisation successful in the energy sector
McKinsey identifies four factors (identified from other retail sectors) that are key to a successful approach to extending customer personalisation to the energy industry:
1. Getting the right data (and not more):
According to the report, firstly, energy companies should focus on storing, selecting and analysing the internal data that they already have. A view of each customer can be created by linking basic customer information (age, gender, and postcode) with behavioural information (energy consumption, billing information) and interaction data (website browsing and search behaviour, number of telephone inquiries), allowing energy companies to identify customers at risk of churn and develop new bundled products to offer to segments with relevant product preferences.
Secondly, by applying these descriptive methods to data, companies can then go further to develop key insights by incorporating advanced data-mining or machine-learning techniques, which makes it possible to predict customer behaviour more efficiently. Metrics such as customer lifetime value could be also developed.
To personalise offers even further, companies could then further deepen their internal customer view by gathering external information - like a customer’s demographic group and housing characteristics (apartment or house) - relevant factors when deciding who should be sent certain offers.
2. Identifying the right triggers for successful customer contact:
McKinsey state that responding quickly to certain customer behaviours is more important to constructing a perfect response – and identifying ‘triggers’ can help to align a specific event with a specific customer.
Examples of triggers might include visits to web pages about energy products; online searches related to house moves; clicks on FAQs about terminating a contract; or specific search terms. The company can then decide an appropriate response to certain triggers. McKinsey state that trigger marketing is relatively new to the energy sector, but is well established in the telecommunications sector:
“For instance, a customer who uses a comparison site to check out new mobile-phone contracts may get a call from his current provider shortly afterwards with an attractive offer to extend the contract. Typical acceptance rates for offers like these range from 20 to 30 per cent” …
“If a utility tracks a customer browsing through its online FAQs and clicking on questions about home moves, it can send her an automated message promoting its home-moving service and a new tariff to encourage her to continue using its services in her new home."
3. Embedding the right culture for testing and learning in agile teams:
Creating personalised customer campaigns requires a new way of operating, according to the report, calling for a dedicated and agile team – or “pods” - across sales, marketing, analytics channel management and IT to be able to test pilot campaigns and scale-up quickly. McKinsey state that as a pod becomes more effective, it can launch more campaigns (as many as 20 to 30 campaigns per month) than a conventional marketing team (two to five campaigns).
4. Using the right methods and technology to scale-up effectively:
The report states that most energy companies become stuck in pilot mode, unable to roll out successful campaigns to their customer base. To scale-up, McKinsey believe that an energy company needs to update data in real time and automate algorithms, ensure system infrastructure is stable, and create more interfaces for sales channels. McKinsey suggests that an automated interface that can collect and integrate data into algorithms enables companies to constantly update their information on a customer’s likely behaviour.
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