Driving Electrification with Data and AI throughout the Customer Lifecycle

As both the electrification (and broader sustainability) and AI landscapes evolve rapidly, data is no longer optional: it’s the differentiator. From OEMs and retailers, to travel operators,  and rental companies, data can accelerate the electrification and sustainability journey. Without it, both strategy and execution will be less pointed.

Consider the EV market. Globally, different markets are at different points of maturity, with factors affecting take-up from government policies to charging infrastructure, price sensitivity to range requirements and even the ‘zeitgeist’ in the press. For the likes of OEMs and rentals, judging the right time to enter or ramp up activity in a market is critical. It affects everything from supply chain of the right mix of vehicles to sell or offer for rental to marketing.

Predict EV market readiness to launch in the right markets at the right time

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But with data – and AI – it is possible to predict the optimal time through publicly available data. This data – such as the price gap from ICE to EV models, press sentiment, charging network, etc – has been encapsulated in our EV barometer to allow OEMs and rental providers to consider things like dealer allocation and fleet composition, or how they will focus their advertising and commercial activity in key geographies, to ensure all of their business lines, from new car sales, resale of EVs, usage and aftersales. Which means that EV market brands can invest in each market at the right time on their adoption path, neither over or under-investing and instead riding the adoption wave without guessing.

Balance carbon compliance and profitability

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Of course, all mobility operators have ambitious and challenging sustainability targets to meet, as well as their own commercial targets. Corporate Average Fuel Economy (CAFE), Net Zero and other government directives can sometimes seem at odds with the commercial needs of a business, especially in less mature markets. Balancing the two is both a challenge and necessity.
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This is where data and mathematics comes into play. It’s a classic optimization task that allows you to leverage data to balance all of the constraints to meet seemingly misaligned objectives. Balancing sales, profitability and margin targets, product mix, production and supply chain as well as CO2 penalty thresholds ensures marketing budgets and strategies are set to align with and deliver against those constraints in the best way possible.

Target and nurture the right EV prospects

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Taking things a step further, it’s just as important to be able to catch EV-ready consumers at the right point in their buying cycle to drive EV adoption. By understanding EV adopter attributes and preferences through propensity scoring, you can then directly target those individuals most likely to switch from an ICE model to an EV. This ensures messaging and offers land both efficiently and effectively. For example, in a less mature market, both your pool of EV-ready consumers and your EV stock or allocated production availability may be quite low. But if you can identify the most interested consumers, you can build sophisticated CRM programmes to drive their interest and eventually action to deliver early sales while market readiness catches up.
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If you then overlay other data-derived scores, such as expected vehicle renewal dates, the CRM engine becomes ever more efficient and effective. Based on propensity scores alone, we’ve seen performance increase five-fold for EV campaigns compared with the average CRM programme. And with today’s AI and chatbots, you can deliver these scores in dealership networks to transform lead generation and conversion even further.

Improve customer retention and loyalty

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Once you have converted a consumer to an EV, you then have the potential to derive an incredible amount of behavioural insights from connected car data. Information that you would only ever previously see snapshots of at servicing or maintenance intervals. This offers significant opportunity for in-life personalisation.

Those early days of driving your first EV can be a little nerve-wracking. Finding the right charger in the right location can seem like a minefield, and one that may hold back usage as ‘range anxiety’ sets in. With connected car data, you can detect this behaviour and tailor communications accordingly. Perhaps you can see persistent over-charging and remind an EV driver of the impact on future battery life. Think of all of the safety, sustainability and wear and tear communications you could consider, and their impact on customer experience and loyalty. Not to mention the potential to improve residual values by driving better vehicle care.

Forecast residual values and leasing models with precision to unlock used EV momentum

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Residual values are truly a hot topic for EVs. The lack of accurate forecasting three years ago is now hitting the used EV market, where momentum is slow. Even at point of purchase, an accurate forecast of resale value is essential, such as in car finance.

The challenge here begins in the very early stage of a future EV car development in the engineering teams. All of the income from factors such as price, sales and market share that occurs upstream is derived from the accuracy of the residual value forecast. The more accurate the forecast, the less financial uncertainty in future as you optimise resale values and the better the momentum in the used market. In the world of AI, Generative AI brings augmented expertise to the task and Agentic AI can be used to run market trends detection and alerts. All of which delivers confidence in future income.

Beyond the EV market

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The EV market is just one area of mobility where data can be the differentiator in delivering a more sustainable future.
We’ve built numerous models and tools for brands like Renault, Hyundai, Nissan, and Le Shuttle across a range of applications, from marketing to operational excellence. For example, our work with Le Shuttle to deliver GenAI predictive maintenance decreased unplanned incidents and downtime on aging rolling stock while increasing early detection and operational efficiency to deliver c. €1.5M+ annual savings. For a global rentals provider, embedding unified marketing measurement reduced waste and increased efficiency by over 9% for the same spend. Understanding causality in paid and organic search for a global airline helped them to understand the role and value of search in the path to purchase.
All of which drives both greater efficiency and effectiveness.

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To find out more about how data could be your differentiator, read our success stories in mobility.

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