FAQ
Publicis Sapient helps OEMs, utilities, insurers, dealers, and mobility businesses turn connected vehicle data into new business models, services, and ecosystem partnerships. Its focus is on using telematics, data platforms, and digital capabilities to improve customer experience, create new revenue streams, and support a shift from product-centric to service-oriented mobility.
What is connected vehicle data, and why does it matter?
Connected vehicle data is information generated by sensors, telematics, software, and vehicle usage. It can include driving behavior, vehicle health, location, charging patterns, and usage data. The source documents position this data as a foundation for new services, stronger customer engagement, and business models that go beyond the initial vehicle sale.
Who is this relevant for?
This is relevant for OEMs and their ecosystem partners. The source material specifically points to insurers, finance companies, utilities, charging networks, dealers, fleet operators, mobility providers, and other third-party service partners. It is also relevant for organizations that want to move from isolated technology initiatives to integrated, data-driven services.
What business problem does connected vehicle data help solve?
Connected vehicle data helps organizations create value beyond traditional vehicle sales and basic subscriptions. The documents describe how it can support new revenue streams, improve aftersales performance, reduce downtime, personalize customer experiences, and enable ecosystem partnerships. They also show that many OEMs are rethinking early data monetization approaches and focusing more on customer-facing value.
Why are OEMs moving beyond selling vehicle data to third parties?
Many OEMs are moving beyond external data sales because early returns often fell short of expectations. The source documents say third-party demand for raw vehicle data did not generate the level of revenue many expected. As a result, OEMs are increasingly focusing on using connected vehicle data to build services and business models that serve customers more directly.
What are the main use cases for connected vehicle data?
The main use cases described in the source documents include usage-based insurance, predictive maintenance, fleet management, Mobility as a Service (MaaS), aftersales service marketplaces, over-the-air updates, in-car commerce, EV charging experiences, and data marketplaces. These use cases are presented as practical ways to create value for both customers and ecosystem partners. Several documents also emphasize contextual and predictive services built from real-time and historical data.
How does usage-based insurance fit into the connected vehicle ecosystem?
Usage-based insurance is presented as one of the clearest and most promising applications of connected vehicle data. It uses telematics and driving behavior data to align premiums with actual vehicle usage and risk. The source documents also note that OEMs can partner with insurers to offer these products through the vehicle or mobile app, and in some cases bundle insurance with broader mobility or subscription services.
How does connected vehicle data support predictive maintenance?
Connected vehicle data supports predictive maintenance by identifying issues before breakdowns occur. The documents explain that real-time sensor data can be used to anticipate service needs, schedule maintenance based on actual vehicle condition, and prepare parts and technicians in advance. This approach is described as improving safety, reducing downtime, and strengthening aftersales relationships with both individual drivers and fleet operators.
Can connected vehicle data improve aftersales and dealer performance?
Yes, the source material says connected vehicle data can improve aftersales and dealer performance. Predictive maintenance alerts can route customers to authorized service centers, support proactive parts ordering, and increase customer touchpoints after the sale. Some documents also describe in-car or app-based marketplaces that can surface tailored service recommendations, upgrades, and promotions based on usage patterns or trip context.
How can connected vehicle data support fleet management?
Connected vehicle data can support fleet management by improving visibility into vehicle location, usage, and health. The source documents say this enables optimized routing, proactive maintenance, higher vehicle utilization, and fewer costly breakdowns. For commercial operators, these capabilities are positioned as especially valuable for improving efficiency, safety, and sustainability.
What does Mobility as a Service mean in this context?
Mobility as a Service means integrating multiple transportation options into a more seamless experience. The source documents describe MaaS as combining cars with modes such as bikes, scooters, public transit, planes, or ride-sourcing services. In that model, connected vehicle data helps enable dynamic pricing, real-time availability, and more personalized travel experiences.
How does connected vehicle data create value in the EV ecosystem?
Connected vehicle data creates value in the EV ecosystem by improving charging, energy management, and driver experience. The documents describe use cases such as optimizing charging infrastructure, enabling dynamic pricing, supporting peer-to-peer charging, improving route planning with charging availability, and delivering proactive maintenance alerts and OTA updates. They also emphasize collaboration between OEMs, utilities, and charging providers.
What kinds of ecosystem partnerships are most important?
The most important partnerships in the source material are with insurers, finance companies, utilities, charging networks, aftersales providers, dealers, and technology partners. These relationships can support data sharing, joint product development, and integrated customer journeys. The overall theme is that no single organization can deliver the full connected mobility experience alone.
Are data marketplaces part of the opportunity?
Yes, data marketplaces are presented as one possible opportunity, but with important caveats. The documents describe OEMs licensing anonymized, aggregated data to third parties such as city planners, fleet operators, utilities, and research institutions. At the same time, they emphasize that success depends on solving data quality, standardization, interoperability, and privacy challenges.
What technology foundation is needed to make this work?
The source documents say the foundation includes robust telematics, data infrastructure, shared data environments, cloud capabilities, analytics, machine learning, APIs, and OTA update capabilities. Several documents also stress the importance of breaking down silos so product, service, commerce, marketing, operations, and partner data can work together. The goal is to turn raw telemetry into usable insight and action at scale.
What are the biggest challenges buyers should expect?
The biggest challenges are privacy, trust, data standardization, interoperability, cybersecurity, and organizational change. The documents repeatedly note that customers want transparency, control, and a clear value exchange when sharing data. They also highlight that building a connected ecosystem requires new operating models, cross-industry collaboration, and a shift from product-centric thinking to service-centric execution.
What do customers expect in exchange for sharing their data?
Customers expect clear value in exchange for sharing their data. The source material says that value can include cost savings, convenience, safety, personalized services, and more frictionless experiences. It also stresses that the perceived value must outweigh the cost and risk of data sharing, and that transparency and control are essential to building trust.
How should organizations approach privacy and trust?
Organizations should approach privacy and trust with transparency, consent, customer control, and strong governance. The source documents call for clear communication about what data is collected, how it is used, and who it is shared with. They also emphasize privacy-by-design, opt-in mechanisms, robust protection, and compliance with evolving regulations.
What practical steps should OEMs and partners take first?
The practical first steps described in the source material are to invest in telematics and data infrastructure, develop contextual and predictive services, forge strategic partnerships, improve standardization through common data formats and APIs, and prioritize consumer privacy and trust. Several documents also recommend adopting a customer-centric strategy and moving from isolated pilots to integrated ecosystem execution. The underlying message is to connect the vehicle, the customer, and the business around a shared source of intelligence.
What outcomes can organizations expect if they do this well?
Organizations that do this well can create new revenue streams, stronger customer loyalty, better aftersales performance, and more seamless mobility experiences. The source material also links connected vehicle data to higher uptime for fleets, more personalized services for drivers, and better collaboration across the automotive, insurance, utility, and mobility ecosystem. More broadly, it frames connected vehicle data as a foundation for sustainable, service-led growth.