In the dynamic landscape of energy transition, the challenge of rolling out real-time pricing rates is a resource for managing grid stress during peak periods. ILLUME’s approach addresses communication strategies and ensures the successful adoption of new rate designs across all segments.
Rolling out dynamic pricing (or real-time pricing) rates is a challenge, but new rate designs will be increasingly necessary to address periods of grid stress during peak times. ILLUME supported Pacific Gas & Electric (PG&E) in understanding customer openness to an RTP rate across sectors (Residential, SMB, Ag, and C&I) through qualitative research as part of a mixed-methods project.
As the energy transition progresses, the significance of new pricing mechanisms for managing and shifting load will be increasingly important. It is crucial to identify compelling and comprehensible ways to communicate these changes to customers across all segments, ranging from residential and SMB to Ag and large C&I, to ensure the adoption of these new rates. In this case study, we highlight how ILLUME approached conducting qualitative research about dynamic rates with customers across segments and the results of this research.
PG&E will be piloting a real-time pricing (RTP) rate in early 2024 and before piloting these rates, PG&E sought to assess customer orientation and openness to dynamic pricing electricity rates across multiple sectors, including residential, small, and midsize businesses (SMB), agricultural (Ag), and commercial and industrial (C&I).
In addition, PG&E wanted to understand how their customers would respond to the rate to shape marketing, communication, and enrollment information across all sectors of their customer base.
As an added nuance, in a smart home/building scenario, dynamic pricing mechanisms can integrate with smart technology that will automatically adjust energy usage based on price signals. For instance, although an electric vehicle (EV) might be plugged in at 6 p.m., the smart device could pause charging until 12 a.m. when demand is lower. PG&E was interested in understanding customer appetite for these kinds of smart solutions when paired with dynamic rates.
Our research questions focused on the concept of dynamic and RTP rates, barriers to acceptance, openness to third-party or automated technology solutions to support the rate, as well as segment- and sector-specific concerns and opportunities.
We conducted 10 focus groups across three sectors (residential, SMB, and Ag) and across segments related to rates (e.g., TOU rates; demand response (DR) participants, solar, and solar + storage). These different segments enabled us to see where there were variations based on rate or energy status. In residential groups, customers with solar + storage responded quite differently than those with solar only. We also conducted 24 in-depth interviews (IDIs) with large C&I customers across several segments, including manufacturing, food processing, healthcare, and hospitality.
The focus groups fed into a quantitative survey, including a conjoint experiment, fielded by the prime contractor, Demand Side Analytics. The focus groups informed the language and framing of the quantitative survey as well as certain parameters included in the conjoint.
The IDIs included a tailored version of the quantitative survey based on the customer’s historical data that was piped in to provide projections of the bill impacts a customer might see when they enrolled in the RTP rate.
The focus group guide included visuals reflecting the price curves specific to each customer group based on an average bill. Once we conducted the focus groups and analyzed the findings, we presented them to a broad stakeholder group. We also provided specific recommendations to the team developing the quantitative survey and conjoint experiment about elements to include in the survey and to test in the conjoint experiment.
Across segments, customers wanted specific and tailored information about how this would impact their bills. In focus groups, customers rejected the ‘typical’ impacts we shared, emphasizing that their unique situations were not typical. More specifically, it wasn’t sufficiently clear from the materials presented how they differed from (or were close to) the typical values for them to translate it to their own situation in a meaningful way.
- As a result, in the conjoint, customers were shown projects based on their historical usage bands.
Recognizing this concern would likely be even more significant for C&I customers, the team folded in actual historical data for these customers. However, when shown projections based on their historical usage, commercial and industrial customers said they too would need additional details before committing. Specifically, they were looking for a side-by-side comparison of what they would have been charged had they been on that rate in the previous year.
One of the in-going hypotheses of several stakeholders was that these rates would be viable and easy for people to participate in because of automated technology solutions that would manage energy use for homes/businesses without the customer actively attending to it. However, most customers responded negatively to this idea. This was perhaps even more the case in commercial businesses where managing operations was an individual’s job, and the idea of automating that was not perceived positively.
- Instead, customers generally were skeptical of these automated solutions because they solved a problem that the rate had created. The easier solution, for customers we spoke with—and given that the rate was framed as an option and not default—was not to opt into the rate. This suggests that until the rate becomes default or the benefit of being on the rate (whether in terms of carbon impact or dollar savings or both) becomes something that customers want and will seek out, the automated tech may not be a draw, because it solves a problem that customers can more easily remove by opting out of the rate.
While many customers across segments were concerned about the environment and reliability, framing the rate as supporting PG&E in ensuring reliable service was not well received. Customers suggested that reliability was PG&E’s problem to deal with. That said, messaging that focused on the grid as a holistic system where customers could play a meaningful part in ensuring reliability in their community was much more salient.
Customers who had experienced issues with reliability in the case of planned outages or emergency situations were more aware of reliability as an issue and it was a motivating concern. These customers often indicated more openness to adjusting their behavior to prevent future reliability events. Some customers explained that that they would prefer to make accommodations “on their terms” than experience an outage.
Many customers (commercial and residential) we spoke with were already on a Time of Use or other time-varying rate. As a result, the concept of electricity prices varying was not new to them. Many even shared that they had made changes to their operations or routines to adapt to TOU rates. For instance, some residential customers shared how they had shifted household tasks to early morning hours to avoid peak times. Similarly, several businesses shared that their operations already had shifted significantly to close by 4pm, thus avoiding peak hours from 4pm – 9pm. For these customers, openness to further shifting was limited. This suggests that RTP or other time varying rates will need to be more distinct from—or offer additional value above and beyond—current TOU rates in situations where most customers have shifted to a TOU rate.
In the context of the study, the focus group findings seamlessly informed the design of the quantitative survey and conjoint experiment. As a result, the study’s outcomes are actively influencing the development of marketing, outreach, recruitment, and enrollment materials, all in preparation for the pilot launch scheduled for February 2024.
The transition towards cleaner energy sources necessitates not only a transformation in how and where we generate electricity, but also a fundamental shift in how and when we consume this electricity. This transition includes distributed generation and dynamic energy resources, and in the near-to-middle term, it encompasses the incorporation of dynamic pricing mechanisms aimed at nudging energy consumption away from the peak demand hours, enhancing reliability.
To successfully design accessible and useful rate structures, it is important to understand how customers perceive energy rates, identify their concerns, and why they might, or might not, consider a dynamic rate.
To gain a comprehensive understanding of customer perspectives and insights, a hybrid research approach, blending qualitative and quantitative research methods offers insights beyond a single approach. In this case study, focus groups enabled the team to capture customer perspectives across groups and segments in an informal and conversational fashion. This holistic approach goes beyond the limitations of either method used in isolation, yielding a deeper understanding of customer dynamics in the context of energy rate preferences.
 ILLUME led the qualitative research portion of this project. Demand Side Analytics (DSA) led the quantitative survey and conjoint effort.