TL;DR
A large electric utility used Brillion’s personalized bill explanation videos to proactively reduce confusion around high bills and prevent unnecessary call center volume. A randomized controlled impact study found a 1.5% energy reduction after just three communications. Highly engaged, low-consumption customers achieved even greater benefits, including fewer high-bill events and up to 5% reduction in annual usage.
Before
- Customers didn’t have insight into bill changes
- Limited targeted engagement
After
- Personalized videos explain changes
- Segmentation drives stronger outcomes
The Challenge
A large electric service provider in the Southwest faced persistent challenges in customer segmentation, targeting, and overall customer satisfaction.
The utility’s top priority was reducing the utilization of the call center for managing billing issues and concerns. Historically, billing issues make up more than 25% of all calls received in utility call centers, and most of these calls uncover legitimate reasons for bill changes, such as fluctuations in weather. Without proactive outreach, customers were often surprised by higher-than-expected bills, leading to frustration and strain on the call center.
Managers also need to show that improvements are cost effective. Finding tangible evidence that customer interactions were driving changes in overall usage was another challenge. While utilities have a wealth of data on customer interactions and the associated costs, determining cost effectiveness often requires data engineering and statistical analysis, making it difficult to quantify the results that matter.
The Solution
The utility partnered with Brillion to help customers better understand changes to their bills. Using customer account and billing information, Brillion generated personalized bill explanation videos for customers that experienced a large bill change. The videos were emailed to customers at the same time as their monthly bill and explained the factors that contributed to specific changes in usage, such as weather or billing cycle length. The videos also included customer satisfaction surveys and call-to-actions for related programs.
Brillion’s Data Science team completed an impact study to analyze the effect of these video communications. Consumption information was used to analyze whether the communications ultimately helped customers change their consumption patterns after receiving and interacting with the videos. The analysis compared the consumption patterns of customers that did receive communications to a control group that received nothing, adjusting for other variables that might have influenced usage (i.e. Randomized Controlled Trial). The study also analyzed different customer segments to determine whether all customers responded to messages in the same way.
The Results
Measurable Energy Savings
When compared to the control group, customers who received high bill communications showed a reduction in energy use of 1.5% after as few as three communications.
This result is comparable to typical results for behavioral savings programs that run for an entire year. And, these communications saw similar outcomes without using social comparison tactics such as social normalization or neighbor comparisons. Instead, the videos provided highly personalized, relevant information and analysis that helped customers understand their unique energy usage.
Ultimately, these results indicate the potential power of targeted, personalized communications.
Segmentation and the Importance of Impact Studies
The impact study highlighted how communications drive different energy usage responses across different customer segments. Brillion was able to find these correlations using customer communication characteristics such as annual energy use and the number of interactions people had with our communications.
This segmentation showed that customers in the bottom 25% of annual consumption responded most strongly to messages about bill changes. As opposed to other customers, these “low-consuming customers” showed a higher propensity to reduce energy consumption and tended to have fewer high bill swings overtime.
Segmentation by ‘number of interactions’ helped determine a communication ‘sweet spot’ where customers that interacted with at least 5 videos performed better than the rest of the cohort. Customers that achieved this level of interaction were also likely to have fewer high bills in the future.
Information like this is critical to optimizing future communications and helps marketing managers make decisions about the cadence and frequency of messages that customers should be receiving.
