Use data from the consumer, the vehicle, the factory and beyond to maximize quality, increase customer satisfaction, improve brand loyalty and innovate.
Why AI Now?
The automotive industry has always been data-driven, but today more than ever, there’s immense pressure for car manufacturers to effectively monetize their data. In-vehicle sensors have turned cars and trucks into connected, smart devices that continuously send telematics and performance data back to the manufacturer — as well as to dealers, insurance providers and municipalities. The rise of autonomous vehicles not only increases the volume of new data produced, but is dramatically shifting consumer preferences. Automotive companies need to reinvent themselves from lean manufacturers to innovators of new, intelligent products and services. RapidMiner has experience helping automotive firms accelerate towards a successful future by using all available data from the consumer, the vehicle, the factory and beyond to maximize quality, increase customer satisfaction, improve brand loyalty, and innovate.
Automotive Industry Use Cases
Highlighted RapidMiner Impact
The dealer services group of a leading manufacturer optimized the pricing of incentives and encouraged more customers to seek post-warranty service with dealers.
A manufacturer’s new vehicles sales organization used historical purchase patterns, demographics and more to accurately predict demand, in order to maximize sales by delivering the right inventory for dealers’ locations.
A European manufacturer innovated new business models and launched AI-driven services, such as one that upsells premium parking spot predictions to drivers in congested urban locations.
A manufacturer’s services department analyzed vehicle repair patterns and took steps to improve underperforming service centers, decreasing the rate of return visits and increasing customer satisfaction.
The quality assurance department of a global manufacturer accurately predicted quality issues for individual plants and prevented costly recalls.
The production unit of a leading manufacturer forecasted factory bottlenecks and re-allocated stations to optimize capacity and improve flow, increasing total plant throughput.
A manufacturer’s marketing team used text analytics of customer touchpoints, including social media, to assess pre- and post-purchase sentiment and drive better brand campaigns and targeted communications.
What Our Customers Say
“Revolutionary Data Science platform built to scale & accessible to citizen data scientists.”
– Senior Analytics Manager in the Manufacturing Industry