The Energy and Utilities (E&U) market has opened up and the number of players continues to rise. The competition is no longer over small price margins, but on the ability to involve and retain customers through retention, and strategies designed to improve brand loyalty.
It’s a real revolution that has impacted the brand identities of all the companies in the sector, from industry giants with decades of history behind them to the youngest and most innovative players. And it places customers at the very center of the companies’ focus. Today’s customer is no longer one among many – they an informed set with unique characteristics and needs, who can easily switch from one operator to another in the matter of a few clicks.
The competitive nature of the market – that has made switching simple and immediate for customers – has created a major challenge for E&U companies. Winning new customers is expensive and complex: it means putting complex marketing strategies in place (where results aren’t always guaranteed), investing time and resources, and working hard on all possible leads in the sales funnel.
WNS can help prevent churn by leveraging predictive analytics to analyze historical data of the customers to check their preferences. Machine learning can make things easy for data analysts to quickly and accurately uncover the real reasons why customers leave or why some are loyal to the brand.
By mapping the customer journey, WNS can help E&U companies understand the end-to-end experience from the customers’ lens. Different customers will have different experiences and we will be able to visualize each one of them. Using customer journey analytics, customers can be grouped into segments defined by profitability, readiness to leave and the likely response to offers to stay – this can help reduce customer churn by better predicting it.
Almost all E&U companies, typically, suffer large non-technical losses due to electricity theft, non-payment by customers, and errors in accounting and record keeping.
One such scenario is when a customer opens a new account at the same premises under the name of another family member or themselves to avoid paying large overdue on the previous account. Due to regulatory restrictions, it isn’t possible to say ‘no’ to any new connection request. Moreover, due to limitations in the record-keeping relation of all the customers with each other it becomes difficult to transfer the old dues to a new account. This leads to large revenue losses for the company, while the customer continues to use electricity without payment of old dues.
WNS can help mitigate this risk by creating an early warning system, using advanced algorithmic text mining. This can help E&U companies to identify the potential of such identity-based fraud happening, at the time of onboarding, thus enabling them to transfer the outstanding dues to the new applicant.
A leading U.S.-based utility was able to stop the leakage of nearly USD 1.4 Million dollar annually by leveraging this solution.