Navigating the Road Ahead: An Expert's View on How Automotive Market Research Must Evolve for the EV Era
Introduction: A Conversation at the Crossroads
The automotive industry is in the midst of the most profound product and business model transformation since Henry Ford's assembly line. Electric vehicles, autonomous driving technology, software-defined vehicle architectures, and the rise of mobility-as-a-service are collectively dismantling a century-old industry orthodoxy and replacing it with something that looks far more like consumer technology than traditional manufacturing.
To understand how market research must evolve to meet this moment, we spoke with Dr. Mara Velasquez, a fictional but composite-representative figure based on the profile of senior automotive consumer insights leaders at organizations like J.D. Power, Cox Automotive, and McKinsey's Center for Future Mobility. Dr. Velasquez brings over 20 years of experience in automotive consumer research, having led insight functions at a major European OEM and subsequently founded an independent research consultancy specializing in EV adoption and mobility behavior. What follows is an edited transcript of our conversation.
On the State of the Automotive Market in 2024
Market Research Perspectives: Dr. Velasquez, let's start with the big picture. How would you characterize the current state of the global automotive market from a research perspective?
Dr. Velasquez: We're operating in genuinely unprecedented territory, and I say that without hyperbole. The global automotive market generated revenues of approximately $2.86 trillion in 2022, and while volume growth has been constrained by supply chain disruptions and semiconductor shortages over the past few years, the structural shift toward electric vehicles is accelerating rapidly. Global EV sales surpassed 10 million units in 2022 — roughly 14% of all new car sales — and BloombergNEF projects that EVs will account for 75% of new vehicle sales globally by 2040.
What this means for market researchers is that the questions we need to ask are fundamentally different from those we asked a decade ago. We've moved from researching incremental feature preferences — leather seats versus fabric, navigation system UI, cup holder placement — to researching existential adoption decisions: Will consumers trust the charging infrastructure enough to abandon internal combustion? How do they value range anxiety mitigation? What is the correct pricing architecture for a vehicle that delivers software updates over-the-air like a smartphone?
MRP: And are traditional automotive research methodologies equipped to answer those questions?
Dr. Velasquez: Honestly? Only partially. The automotive industry has historically been very good at certain types of research — clinics, for example. Vehicle clinics, where you bring 300 consumers into a controlled environment to evaluate physical and digital attributes of prototype vehicles, have been refined over decades by OEMs and firms like Strategic Vision and AutoPacific. That capability remains valuable.
But the EV adoption question is fundamentally a behavioral economics problem, not a product attribute problem. You're asking consumers to make a high-stakes, high-unfamiliarity decision — often their second-largest household purchase — in a technology category where their reference points are limited and their anxieties are high. Standard stated-preference surveys are notoriously bad at capturing this. I've seen studies where 60% of respondents say they're likely to buy an EV in their next purchase cycle, and then actual market penetration in that segment comes in at 12%. The intention-action gap in automotive EV research is enormous.
On the Methodological Evolution Required
MRP: So what methodological evolution do you think is needed?
Dr. Velasquez: Several things, in my view. First, longitudinal behavioral tracking needs to become standard practice. We need to follow the same consumers across their entire purchase consideration journey — from initial awareness through research, test drive, financing, and eventual ownership — capturing real behavioral signals at each stage rather than reconstructing it retrospectively in a post-purchase survey. This is where panel management platforms like Dynata and Toluna need to build automotive-specific longitudinal panel capabilities with real purchase behavior linkage.
Second, we need far more sophisticated scenario-based and immersive research. Virtual reality simulation of EV ownership scenarios — testing charging infrastructure anxiety in a realistic setting, for example — can elicit more authentic emotional responses than abstract survey questions. Hyundai's research team has experimented with VR-based range anxiety simulation with compelling results.
Third — and this is where I get slightly evangelical — we need to embrace passive behavioral data at scale. Connected vehicle platforms are generating terabytes of real driving behavior data every day. Partnering with OEMs to overlay this behavioral telemetry with survey-reported attitudes and preferences would give us a multi-dimensional picture of automotive consumer behavior that has never been possible before. The regulatory complexity around this data is significant, but the research value is transformational.
"The EV adoption question is fundamentally a behavioral economics problem, not a product attribute problem. Standard stated-preference surveys are notoriously bad at capturing this — and the industry knows it." — Dr. Mara Velasquez
On Competitive Dynamics and Brand Strategy Research
MRP: How is the competitive landscape shifting the brand strategy research agenda for automotive OEMs?
Dr. Velasquez: The entry of Tesla redefined what automotive brand equity means in the EV era — and then the entry of Chinese manufacturers like BYD, NIO, and SAIC into European and Southeast Asian markets is redefining it again. BYD overtook Tesla as the world's largest EV seller by volume in Q4 2023. That is an extraordinary competitive development that most Western OEM brand researchers were not adequately prepared for.
The traditional automotive brand equity frameworks — built around heritage, engineering reputation, dealership experience — are inadequate for an environment where a Chinese startup can enter a market with competitive pricing, compelling software features, and aggressive digital-direct sales models. We need brand research frameworks that weight technology trust, software ecosystem integration, and total cost of ownership transparency as primary equity drivers, not secondary considerations.
Conjoint analysis studies in this space are revealing fascinating trade-offs. Consumers are willing to accept significant compromises on brand heritage and physical interior quality for meaningful gains in software capability and charging network access. That would have been an unthinkable finding ten years ago.
On the Agency and OEM Research Partnership
MRP: What does the ideal research partnership between automotive OEMs and research agencies look like in your view?
Dr. Velasquez: The most effective partnerships I've seen are built on three pillars. First, embedded expertise — research partners who have deep automotive domain knowledge, not just methodological expertise. You can't design a meaningful EV consideration study if you don't understand DC fast charging versus Level 2 infrastructure economics. Second, data integration capability — the ability to seamlessly blend primary survey data with third-party sales data from sources like S&P Global Mobility (formerly IHS Markit) and behavioral data from digital touchpoints. Third, regulatory fluency — particularly around GDPR, the EU AI Act's implications for algorithmic decision-making in vehicle systems, and the evolving vehicle data governance frameworks being developed by bodies like ACEA (the European Automobile Manufacturers' Association).
Final Recommendations for Automotive Researchers
Based on insights from this conversation and the broader state of the field, market researchers building automotive practices should prioritize the following:
- Develop EV-specific segmentation models that go beyond demographics to capture psychographic drivers of EV openness, including environmental values, technology innovativeness, and financial risk tolerance.
- Invest in charging infrastructure perception research — range anxiety is primarily an infrastructure confidence problem, and understanding the specific geographic and experiential thresholds that convert skeptics requires dedicated research design.
- Track the agency model disruption — as OEMs like Mercedes-Benz and Stellantis experiment with direct-to-consumer agency sales models, the dealer experience as a research construct is being transformed. Researcher frameworks must adapt accordingly.
- Build China literacy — understanding Chinese EV brand perceptions in Western markets and Chinese consumer behavior in domestic EV markets is no longer optional for any globally-oriented automotive research practice.
The road ahead for automotive market research is complex, technically demanding, and intellectually exciting. Those who invest now in building the methodological and domain expertise required to navigate the EV transition will be well-positioned to serve one of the world's most strategically important and fastest-evolving industries.