The economic shocks of this year’s global pandemic are likely to be felt for years. The much publicized impending recession will see incomes across the globe continue to be squeezed, and more and more households will find it harder to afford their utility bills. There’s never been a more pressing need for utility companies to be able to identify and engage with their low-income customers. We take a look at the crisis facing these vulnerable households, the advantages of being able to identify them, and how data science can provide utility companies with the perfect solution.


The UK’s energy crisis

According to data published this year by, poorer households across the UK pay on average £60 more per year for their energy than higher income households1. That’s because they’re likely to be on a prepayment plan or on a supplier’s standard variable tariff – both of which make the cost of energy more expensive. The price comparison website found that the average annual energy bill for Britain’s most deprived households is £1,123, while those living in the most affluent areas pay £1,063.


The problem is compounded by the fact that the homes of lower income customers aren’t likely to be energy efficient, which means they have to spend more to keep their homes warm. And of course, recent lockdown and self-isolation measures means everyone is spending more time than usual at home, driving up their energy and water consumption and costs. 


The USA’s water crisis

In the United States, customers are facing similar challenges, but the main crisis lies with water. The country is facing an extreme water poverty crisis thanks to its aging infrastructure, environmental clean-ups, changing demographics and price hikes. 


A recent investigation by the Guardianrevealed that in 12 US cities, the combined price of water and sewage increased by an incredible 80% between 2010 and 2018. The Guardian’s report states that more than two-fifths of residents of some cities are living with unaffordable bills and creeping debt. Federal programs are in place to help low income households afford energy and telecoms bills, but nothing has been put in place for water.


Why reach out to low-income customers?

The need for utility companies to be able to identify and engage with their low income customers has never been more urgent and is driven by a number of factors.

  • Customer support – Reach out to  low income customers to help them reduce their consumption and costs, whether that’s by providing them with tips to help them lower consumption, offering different tariffs, discounts, payment schemes and payment breaks, or by introducing them to support schemes and grants. 
  • Brand – Don’t be the company that waits for its vulnerable customers to contact you when they’re struggling. And don’t be the company that only contacts its customers to send reminder and final notices when they’re in arrears. Build your company brand and reputation as the company that is proactive and supportive.
  • Business – Of course it also makes commercial sense to keep communication channels open with customers who may be struggling. For energy companies you’re less likely to lose the customer to another provider, and for water companies, you can support the customer before they get into arrears and more drastic action needs to be taken.


Can you identify your low income customers?

Before the Coronavirus pandemic, utility companies were already investigating ways to support their priority service customers. As we’ve discussed, the need to identify low income households is now more pressing than ever, but the process of identification is not a simple one. Financial circumstances change and financial information does not lend itself readily to disclosure.


That’s why utility companies are turning to data science solutions. Data science, AI and analytics aren’t new to the energy sector. They’ve been driving automation, delivering insights and reshaping the space for a number of years now. But with a new R&D project, Advizzo is now putting data science through its paces, to help utility companies identify their low-income customers. 


The trial project takes a utility company’s data relating to calls, consumption and billing, and runs it through our platform using Machine Learning to deliver a dataset that gives the probability of a customer being low income (based on parameters set by the utility company and/or regulators). With that data, utility companies can confidently reach out to their low income customers to engage with them and support them. 


If you’d like to learn more about our R&D project or our customer engagement services and solutions, then please don’t hesitate to get in touch.







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