You’ve probably heard a lot lately about auto makers and dealerships becoming more “customer centric”—which essentially means doing a lot more personalized marketing and customer experiences. Perhaps you’ve also been hearing a lot of marketing automation pitches, too. These topics might seem to be at odds with one another; after all, if you’re personalizing service, sales, and marketing for each customer, how can you possibly turn all that over to an automated system? How do you have a one-on-one conversation with each of your prospects and customers as if they are the only person in the world, when your aim is to have thousands, if not millions of customers? That was the challenge that Maruti Suzuki India Ltd.—the leading car company in India—has long faced. “We need to manage the customer conversation with consistency across our businesses and omnichannel journey—purchase, loyalty, insurance, accessories, finance—all of it,” says Noritaka Waduda, advisor and leader for digital transformation at Maruti Suzuki. This need to personalize and maintain customer conversations across large geographical and cultural distances, from initial website customer research to in-person dealership interactions, is part of what led Wakuda and his team to seek out tools that can achieve “customer-centricity at scale.” That’s basically a fancy way of saying “personalized customer experiences, assisted and tracked by marketing automation, which makes such experiences profitable.” That’s a great strategic aim, yet often difficult in practice. As in many automotive companies, data was coming from dozens of marketing platforms and other sources, but data integration and data stitching was a challenge--and took far too much time. Another problem was the lack of data completeness or detail in the data coming from different, often siloed sources. From one touchpoint to another, there were large gaps, and many potential customers who hit the website never made it to the dealership. To reap the rewards of digital transformation, Maruti Suzuki needed a full end-to-end view of engagement and a leading edge automotive marketing approach with customer analytics to match. As it turns out, Wakuda found the perfect marketing automation technology—and much more. Customer data platforms (CDPs) are tailor-made for the task of providing personalized customer experiences that span from keyboard to dealership and beyond. But with their ability to develop detailed user profiles and use these single customer views (SCVs) to tailor customer journeys, they’re also key to powering many other strategic goals common to auto marketers everywhere, such as the shift to data-driven marketing and digital transformation. The choice of Treasure Data CDP has transformed marketing at Maruti Suzuki, and has resulted in a much more data-driven way of doing business throughout the company. “Treasure Data [Enterprise CDP] is the backbone for our customer centricity. It also helps us drive performance. It is changing the culture here,” Wakuda says. At every step of the car-buying process—shop, buy, and own—CDPs are helping auto marketers understand and personalize key touchpoints for each customer journey. Let’s look at each of the five key customer journey stages and see how CDP marketing automation and machine learning can help personalize each step, maximizing not just the chances of a sale at the dealership, but add-on sales as well. Let’s look at how automakers are using Customer Data Platforms—martech that takes data from many sources, such as CRM, ad platforms, web browser histories, and social media—to improve results in all three phases of car buying. 1. Awareness and intent—In these early stages, customers are often open to considering a wide range of vehicles. They’re probably visiting websites, asking around on social media, reading reviews on Car & Driver and Consumer Reports, and looking at ads. One of the best applications of mass personalization at scale is to customize the website landing page that the prospective buyer sees. Here Treasure Data CDP can help by analyzing the characteristics of different people who actually bought a vehicle, and analyzing the current prospect’s behavior and demographics to determine which content is likely to persuade the prospect. A CDP can also determine which action is most likely to result in moving the prospect along the purchase path, based on results with similar people who have made purchases before. Determining the “next best location”—which dealership to send people to, so the sale can be completed there, is also critical in this phase.This feature can really improve results, especially when paired with the best practice of automatically distributing a “hot leads list” that is shared weekly with dealerships for follow-up. The CDP handles stitching the data together, running lead scoring algorithms, calculates propensity to buy, and determines the best dealership based on location and other factors. Maruti Suzuki used these features to manage the handoff from its website to dealerships, and dramatically increased the percentage of customers who went to a local dealership to complete a sale. 2. Purchase—One of the most difficult things for dealers is to figure out which buyers want to buy immediately, and which potential customers are still early in their customer journeys, just researching vehicles for possible purchase months or years out. For example, Subaru used Treasure Data Enterprise CDP to uncover the fact that there were different behavioral profiles for immediate buyers that made them stand out from the rest. Understanding these differences—and customizing customer journeys to appeal to different needs—helped Subaru to gauge each customer’s propensity to buy, increasing conversions by 13 percent and closing rate by 14 percent, while reducing cost per new customer acquisition by 38 percent. 3. Ownership—In this part of the customer journey, the objective is to figure out how to engage the customer to return to dealerships for add-ons, service, and ultimately, future car purchases. Consider, for example, a wife who has had a positive experience with a vehicle brand and suggests the brand when her spouse starts to think about vehicle replacement. In addition, CDPs can help customize and target communications with owners, to drive service. The next-best-action feature, for example, can automate the most likely sequence of touches to get a customer to bring a car in for servicing. And with the rise of connected cars producing a wide range of driving data, it’s easy to see how CDPs could use that data to suggest servicing after, say, a certain number of miles, or an event such as hydroplaning tires or a near-collision due to worn brake linings. So at all phases in the customer’s journey, data makes a difference. Specifically, having a unified, single customer view of each prospect makes a huge difference. And using a CDP to create that profile and automate and orchestrate personalization at the scale at which auto companies and dealerships must operate, is game-changing. That’s how data-driven car companies answer the question of creating customer centricity at scale, and making each and every one of millions of customers feel like they’re the only customer that matters. To learn more about how Treasure Data helps industry leaders reinvent the car-buying experience, visit our automotive solutions page.