Same Lessons on Rebate Programs, Eleven Years Apart

TECH Clean California launched a few years ago to help California households adopt heat pumps and other clean energy upgrades, but the roots of appliance rebate lessons go back further. More than a decade earlier, the U.S. Department of Energy ran a different appliance rebate program and wrote down what it learned.

Reading the 2015 DOE report on the State Energy-Efficient Appliance Rebate Program (SEEARP) (originally published via OpenEI) next to TECH Clean California's upcoming best practices report, a pattern jumps out: some of the same lessons show up twice, more than a decade apart - while at least one lesson clearly stuck.

1. Program complexity discourages participation - simplicity drives it

Back in 2015, DOE observed that consistency and simplicity in program design mattered for effective coordination:

"Some manufacturers found working with the 56 different program models during SEEARP extremely challenging. They suggested that having four or five regional models would provide greater consistency and allow for more effective coordination."
SEEARP Volume 1, Section 4.2, p. 35

Fast forward to 2026, and TECH Clean California's draft report identifies the exact same friction as one of its top findings:

"Program simplicity is key to success. In both formal and informal feedback, the most common improvement suggestion from contractors is to simplify TECH Clean California and make it easier to participate, particularly for smaller businesses who don't have time and capacity to navigate the intricacies of program requirements... While the intent behind these requirements is understandable, an accumulation of constraints can create friction and implementation challenges that deter participation and increase administration costs."
TECH Clean California Best Practices Draft Report, Executive Summary, p. 8

2. Application errors and approval friction slow programs down

DOE's 2015 report specifically called out application errors as a drag on rebate processing:

"Frequent errors in applications" and "Application errors take time and effort to identify and resolve" - listed among the disadvantages of mail-in rebate processing.
SEEARP Volume 1, Section 3.4, Table 6, p. 25

TECH Clean California's 2026 draft describes the same problem in its own program, eleven years later:

"The cumulative complexity of these requirements manifests in the form of increased application approval timelines, higher rejection rates for minor errors, and elevates contractor soft costs - this can strain the capacity of firms to participate, particularly small businesses, and discourage contractor and customer engagement."
TECH Clean California Best Practices Draft Report, Executive Summary, p. 8

3. Targeted, higher-value incentives for low-income households - a lesson we kept

Not every echo between these two reports is a case of forgetting. One is a genuine success story: a lesson learned in 2015 that has stuck.

DOE's 2015 report found that targeting deeper rebates at low-income participants increased program impact, pointing to real state examples:

"A targeted rebate program can help struggling residents buy new products and can increase your program's impact." Kansas "limited its program to low-income residents, offering rebates of 100% of the purchase price," while Oregon "targeted low-income homeowners with rebates of 70% of the purchase price."
SEEARP Volume 1, Section 3.2, pp. 17–18

TECH Clean California's draft shows this same approach is still working, more than eleven years later:

"Increased incentives for customers based on income are an important way to serve customers equitably. Since the July 2025 launch of TECH Clean California's dedicated equity bonus incentives, equity customers have received 62 percent of incentives, significantly above TECH Clean California's current goal of 50 percent... appropriately sized equity incentives can help low-income households adopt heat pumps."
– TECH Clean California Best Practices Draft Report, Executive Summary, p. 6

Unlike the first two examples, this isn't a lesson being re-learned - it's one that was learned once and never lost.

Why this matters

Programs like TECH Clean California operate independently and years apart from programs like SEEARP, but the underlying dynamics of consumer rebate and incentive design don't change much: complexity discourages participation, paperwork friction slows everyone down, and targeted incentives can reach the households who need them most.

Two out of three of the parallels above suggest institutional memory is a real risk for public programs - lessons documented in one report don't automatically carry forward into the next one, even within the same state, even in service of a very similar goal. The third shows it doesn't have to be that way.

What are you seeing rebate programs learn and... not learn?

What program lessons do you see being repeatedly relearned? And just as important, what are we better at learning and building on?

Share your take in our LinkedIn conversation [LINK TO BE ADDED – LinkedIn post URL] or join the discussion on Reddit [LINK TO BE ADDED – Reddit thread URL].

Note: As of this blog post's publication date, TECH Clean California's Best Practices Draft Report has not yet been published; it is expected to appear on the TECH Clean California website once finalized.