EV sales have declined. Who will buy them next? - BlueLabs Analytics

EV sales have declined. Who will buy them next?

In the past few months, electric vehicle (EV) sales in the U.S. have stagnated. This downturn has occurred even as a wider variety of EVs have reached the market with lower sticker prices and a federal tax credit became available at point-of-sale. The path to widespread EV adoption may be bumping up against the reality of any new technology’s adoption curve: the challenge of moving past early adopters to the American majority.

How can EV manufacturers break through this impasse? BlueLabs has built an EV consumer model that identifies the American consumers most likely to purchase or lease an electric vehicle (EV), as well as those who might be convinced to. By applying this model to our national consumer file of nearly 200M American adults, we harness the power of data to help EV manufacturers find the next generation of EV buyers.

The consumers who earned the top scores on BlueLabs’ EV model tend to live in urban environments, be younger, and earn higher incomes. These individuals have been amongst the earliest adopters of EVs.

BlueLabs assigned scores to nearly 200M Americans on the likelihood that they intend to purchase or lease an EV. An average score labeled “1.3x” indicates the average score among that demographic group is approximately 30% higher than the average score across all American adults.

Our analysis revealed that urbanicity1, or whether an individual lives in an urban, suburban, or rural environment, is a strong predictor of interest in purchasing an EV. Individuals living in urban centers tended to score more highly as potential EV consumers than people living in suburban or rural areas.

Outside of city centers, people who live in the suburbs were among the next most likely individuals to purchase or lease an EV

To scale the positive impacts of EVs over gas cars, we need to expand the adoption of EVs outside of urban centers, to the populations who use more gas to drive farther distances.  Americans living in rural areas tend to drive more miles each year than Americans who live in urban areas2. Meanwhile, the U.S. Department of Transportation reports that the rate of adoption of electric vehicles in rural areas lags behind that of urban areas by about 40%. The suburbs could be the frontier that helps expand adoption of EVs outward from city centers. 

BlueLabs’ analysis found a clear signal indicating that the more urban a person’s residence is, the more likely they are to be an EV consumer. An average score labeled “1.3x” indicates the average score among that demographic group is approximately 30% higher than the average score across all American adults.

Automakers and charging companies involved in the EV transition will need to continue to invest in addressing the barriers to EV adoption, including charging and cost. Charging infrastructure has largely been concentrated in urban environments and along major travel corridors. Companies and organizations involved in installing EV chargers can benefit from BlueLabs’ EV model to pinpoint the right suburban and rural areas to prioritize for expansion and messaging campaigns. 

As automakers and retailers expand charging networks, bring down EV sticker prices, and expand their offerings from luxury to economy vehicles, a more diverse set of consumers may start to see the value of switching to electric. Suburban and rural Americans, who on average drive farther and thus may need to budget for more gas in a given year, could see larger cost savings associated with switching from gas to electric – a benefit that would simultaneously lessen carbon emissions. 

EV makers can assuage fears related to range anxiety or pricing with targeted charging infrastructure and educational campaigns that share relevant information with the exact individuals who are most likely to consider switching to an EV. To communicate the benefits of going electric to the next generation of EV buyers, get in touch with us about our EV Model and audiences by clicking the link below. 

Methodology

Predictive models identify trends within a smaller group of consumers that we know a lot about. We then extrapolate these trends to the general population of Americans ages 18+. To build this model, we:

  • Delivered a multi-modal omnibus poll to the general US adult population in early February (n=1,783) and late August 2023 (n=2,422) to collect data on their likelihood to buy or lease an electric vehicle.
  • Identified significant data predictors from within our national data file to build a model that assigned scores to individuals based on their likelihood to be interested in acquiring an EV.
  • Applied model to full national data file of nearly 200M American adults to rank-order and identify the people most likely to purchase or lease an EV.
  1.  Urbanicity classification assigned scores to U.S. Census block groups. Scores were calculated using several different variables, including population density, household density, traffic, U.S. Census estimates of urban vs. rural classifications, and employee counts. ↩︎
  2.  Source: Federal Highway Administration, 2022 National Household Travel Survey (NHTS). ↩︎