Low- and moderate-income (LMI) customers have their own unique challenges that make a homogenous approach to serving them pointless. Historically, utilities lumped LMI customers in with the rest, casting a wide net and hoping the right message or program would stick over time. But that didn’t work then, and it won’t work now. To best serve LMI customers, we need to understand them at a granular level and remember that they’re humans. We need to treat them as an audience of one and develop holistic, equitable solutions that will address the root causes of LMI challenges, not sweep them under a rug while we hope for success.

According to a January 2022 press release from the US Census Bureau, there were 37.2 million people in poverty in 2020, roughly 3.3 million more than in 2019. These customers can be a challenge to properly serve and support. They cost more to serve and have an impact on customer satisfaction scores. Not managing an LMI program effectively also risks driving up rates because regulators often allow utilities to recoup certain bad debt costs through rate hikes. So how can utilities best help those in need? It’s become clear that “the way we’ve always done it” no longer works. We recommend a three-step process that will improve the way you’re connecting with LMI customers and enhance their customer experience.

“One size fits all” isn’t equitable for LMI customers

Data science and machine learning are impressive tools that allow you to conduct analyses that are unlikely to be successful if performed by hand. As we kicked off LMI-focused projects, we wondered how data science could help and if there was a way to amplify our efforts. We started to ask ourselves, What if we used machine learning to look at utility data related to arrears, disconnects, past-due balances, and contact center actions?

Our approach begins by defining LMI customers. Then we use modeling to create a segment of LMI customers and a digital replica of each customer, formed by combining utility and E Source data. Some of the proprietary data we work with include behavioral and lifestyle attributes such as:

  • Income
  • Size of household
  • Age of kids
  • Revolving credit card data
  • Mobile phone use

Additionally, if advanced metering infrastructure data is available, our experts can use that to map energy profiles for each household.

We use customer name and address information to fuse together your customer records with our data. From there, our data scientists can identify customer cohorts based on similarities in the data profiles.

Our analyses revealed some interesting things about each of these cohorts. But we struggled to understand why some struggled with paying their bills when, demographically, they looked the same. Performing ethnographic market research to dive deeper into customers’ wants and needs was key.

Perform an ethnographic market research study for a glimpse into your customers’ worlds

Ethnographic research focuses on the customer as a unique individual, examining their behavior in real time through direct engagement. Traditional forms of data collection, such as surveys and email outreach, are great, but they don’t capture customers’ true sentiments and raw honesty.

Our experts can connect with your customers one-on-one for an intimate interview and bring the voice of the customer into projects. This face-to-face research provides insights into customers’ emotions and needs, delivering the data required to create effective programs that aren’t only attractive to them, but are also the most beneficial to their unique needs.

Develop customer-centric solutions with an E Source design-thinking workshop

It’s not enough to rely on the traditional approach of market research where data is collected through customer surveys and one-on-one video interviews. Utilities must do something with all that data. It can be overwhelming, but we’re here to help.

Design thinking is a radical way to flip the product and service creation process on its head. Our approach brings together a cross-functional group of employees to participate in a three-day workshop to develop products and services. Why a cross-functional group? It’s great for design thinking because it helps prevent groupthink and provides different viewpoints.

During our design-thinking LMI workshops, we help utilities develop customer-centric, early-stage solution concepts based on the results of our ethnographic market research. Our experts can help navigate new ideas and challenges while also identifying opportunities.

This approach puts customers’ needs at the core of the solution development process, relentlessly keeping customers—real human beings—at the forefront to make sure we’re developing solutions that have a high likelihood of resonating with our target audience. This inverts the historical utility product development process, which is typically focused on developing solutions that meet utility needs and then incentivizing customers to participate to help meet those utility needs.

What your utility can start doing today to better serve LMI customers

In the meantime, you might be wondering what you could do to get started today in addition to the strategies described here. It can be daunting, but here are a few tips for improving LMI service.

  • Talk to your LMI customers on a regular basis. Spend time with community partners and have those crucial personal conversations.
  • Don’t assume that existing offerings will fix LMI challenges. Have tough conversations internally about whether a program is effective. If not, why not? How can it be redesigned, or does it need to be scrapped?
  • Develop solutions with your LMI customers. We’re generally too far removed from their challenges to know whether our ideas are good ones. Designing solutions in partnership with LMI individuals or proactively getting their input during the design process will lead to far more successful offerings.
Understanding customer needs through data science and ethnographic research Jeffrey Daigle, Sara Patnaude Community outreach Corporate initiatives Energy equity Customer experience Design thinking Ethnographic research Voice of the customer (VOC)