Is it possible to tell which customer is most likely to be interested in a demand response, electric vehicle rebate, or prepay billing options? Entergy, one of the largest utilities in the southeastern United States, believes they can. As part of their effort to become more customer-centric, they wanted to know what their customer wanted and how that would impact their business model. Their hope was that by understanding what individual customers want they would be better able to serve, communicate, and engage with customers.

The objective of delivering better products and services was clear, but the pathway was not. Entergy recognized that to properly segment their customers based on propensity to adopt a program and what communication channel was most likely to trigger that successful customer journey they needed significantly more data, which was something they lacked.

With limited information on a broad portfolio of products and services, Entergy conducted a survey to explore the participation potential of new offerings. Creating an analytics-ready data set required a holistic approach. Entergy simultaneously conducted multiple customer surveys and integrated it with a third-party data set rich with lifestyle, behavioral, financial, structural and demographic attributes for both residential and commercial customers. Collecting the data was only step one.  Entergy turned to artificial intelligence (AI) and machine learning, to create a propensity model for product and service adoption rates down to the household and business level. Customers were segmented for each of 30 products and services in Entergy’s portfolio.

Source: Entergy

Entergy’s efforts to understand their customers came in the large context of a grid modernization study which included the objective of more responsively planning for anticipated DERs at a feeder level. By understanding the propensities of businesses and residential customers to adopt particular programs, Entergy can aggregate that potential load forecast up to each feeder.

The grid modernization team was able to include forecasts based on advanced analytics that could account for how the grid would be impacted by rooftop solar penetration, demand response, energy efficiency, and electric vehicles. Once Entergy identified customers as a likely adopter of a specific program they were able to map this adoption’s potential impact down to the Zip code level (Figure 2). This level of detail is very helpful for distribution and transmission planning.

Source: Entergy

As Entergy refines their services portfolio, asset maintenance, CAPEX, and OPEX planning this information can be critical to the grid modernization team to better understand how customer activities may shape the need and pace for future capabilities. By adopting a data-driven customer-centric strategy Entergy is not only able to deliver better quality products and services to their customers they are also able to design their grid to be more responsive and reliable.

Entergy will be discussing their approach their approach to using data science, software, and analytics to better understand their customers on a webinar with Zpryme. This webinar will explore how utilities are using software and data to create appropriate customer journeys. Furthermore, the webinar will explore a customer-driven IT system can help utilities thrive in a digital environment. Zpryme will be speaking with Raiford Smith, Entergy’s Vice President of Energy Technology and Innovation and Software AG’s Saul Zambrano. You can register for free using the link below.