Connecting customer data to transactional data provides huge scope for competition and innovation in an open banking world
Combine financial services data on customers' income, benefits and account balance with energy data on credit/debit balance, payment plan, annual usage and seasonal usage, and weather forecasts. This allows energy utilities to forecast when customers might fall into arrears, suggest bespoke payment plans to address the problem and even help them plan budgets to protect access to essential services.
Benefits: Faster onboarding and a clearer view on affordability, reduced bad debt thanks to pre-emptive actions.
Combine financial services data on benefits and employment income, child maintenance, rent, and medical expenses with energy data from the Priority Services Register, HMRC core group Warm Homes Discount, presence data, and Energy Company Obligation-installed insulation measures. This allows identification of different categories of vulnerable customer and the most relevant sources of support.
Benefits: Cuts the cost of meeting obligations to vulnerable customers and improves the service they receive.
Combine financial services data on daily and monthly trends in income and outgoings with energy data on solar PV generation supply, energy usage demand and battery charge levels. This allows the energy utility to create a trading platform for domestic customers that can tell them whether it is more efficient to sell the energy back to the grid, store it or use it.
Benefits: Better, easier management of household energy use and bills, leading to stronger customer retention.
Combine financial services data on benefits and income changes, purchase activity, mail redirection and solicitors' fees with energy data on changing usage and debt information. This allows suppliers to identify customers' life events and respond in the most appropriate way.
Benefits: Ability to offer relevant assistance leading to increased customer satisfaction.
Combine financial services data on propensity to insure, indications of hobbies and lifestyle choices, sources of income and patterns of expenditure with energy data on presence, online billing, appliance algorithms and uptake of other products. This allows much more detailed profiling of customers. It also leads to the ability to apply highly tailored offers for customer acquisition, cross-selling and retention via most relevant channels and with appropriate partners.
Benefits: Ability to work harder for the customer – more relevant offers that carry higher value for that individual.
of adults would opt in to financial services which use their data for personalised offers such as utilities
of adults would opt in to financial services which use their data for loyalty points
of adults would opt in to financial services which use their data for offers from their favourite brands