Customers on the lookout for a new vehicle are demanding more from their vehicle purchasing experience. With more ways to buy and higher customer expectations, dealerships need to do more to compete for their business. For instance, new and used vehicle customers are spending less time browsing, fewer days on the market, and are making quicker decisions. Therefore, dealership visits are on the decline, with 41% of new vehicle customers going to just one dealership – up from 30% two years ago. Furthermore, it is estimated that 60% of vehicle buyers aged 45 or under are likely to purchase their next vehicle online with favour given towards contactless sales and services.

In other sectors, most online customers want real-time customer support and will switch companies if they do not achieve excellent customer service. Therefore, there is little reason to suggest this will not happen in the vehicle purchasing market; hence the need for dealerships to be aware of and cater for the changing scenarios regarding new vehicle purchases. Only organisations that can continuously create unique, personalised customer experiences and understand and anticipate customer demands will be able to acquire and maintain loyal customer revenue streams. Consequently, predictive analytics and marketing must be used to identify and anticipate customer wants and needs since it is one of the best methods to ensure relevance with today’s vehicle purchasing market.

What is Predictive Marketing and what can it do for Dealerships?

The use of historical data to estimate future trends is known as predictive analytics or marketing. Data mining, machine learning, and predictive modelling are some of the statistical approaches used to do this. Predictive analytics at vehicle dealership level are commonly used to forecast customer behaviour, analyse preferences, and anticipate next steps. Through use of statistics and predictive modelling, dealerships can develop individualistic marketing campaigns to target customers. Furthermore, these analytical services make it easier to predict demands, recognise preferences, enhance message timing, boost relevancy, and, most significantly, increase sales by distilling statistics into easy-to-understand scores linked with each customer.

Predictive analytics can help dealerships of all sizes cut costs by automating time-consuming and laborious procedures such as screening through leads, identifying the top prospects, and sending targeted messages at scale. In addition, there is no generic approach to selling a vehicle, just as there are several methods to connect with clients. Several advanced marketing solutions assist dealers in simplifying procedures and operations such as acquisition and inventory plans, minimising their dependency on paid lead resources.

Finally, regardless of the time or location, there are links between each department within vehicle dealerships that must be aligned and operate with equivalent datasets; this is the foundation of every successful dealership. By aligning all departments, customer insights can be shared across the dealership to link the customer to the most relevant department. Predictive analytics in this respect helps dealerships maximise efficiency and minimise costings.

How can Dealerships use Predictive Marketing?

The main aims of predictive marketing are to respond to the customer’s needs regarding: the purchase of a service or vehicle within a given timeframe, responding to an offer, mitigate the possibility of defecting to another brand, advocating the benefits of the chosen brand, recommending a particular vehicle class, model or feature, and helping shape the customer’s spending habits at the dealership.

Mercedes-Benz use a combination of Artificial Intelligence (AI) and predictive analytics to effectively anticipate when its current customers are ready for a new vehicle. They began their data modelling in Berlin, Germany, with a heat map to estimate where and when the most likely A-Class driver would purchase a vehicle. Their database consisted of 100,000 client records and after a preliminary investigation, the number of potential Mercedes-Benz A-Class purchasers was reduced to 5,000. This was completed in only six weeks through efficient use of predictive analytics. Furthermore, they also extended their analysis to identify customers who owned at least two S-Class vehicles who were considering purchasing a third.

As of 2017, automotiveMastermind, the premier behaviour prediction technology for the automotive industry, has been working with over 100 Cadillac dealerships to improve sales and profitability. The Mastermind system rapidly and accurately identifies customers who are ready to purchase and their incentives, allowing dealers to rapidly assess sales prospects. This is accomplished by combing significant quantities of statistics from a Dealer Management System (DMS) with social media profiles, financial records, product and customer lifecycle information, socio-demographics, and Big Data analytics. The data is then reduced to a single number, simple ranking system, known as the Behaviour Prediction Score (BPS) which indicates to the dealer which customers are likely to buy right away. Furthermore, Mastermind provides salespeople with customer-specific motivational talking points and highly tailored marketing campaigns that have been shown to boost the likelihood of a buyer visiting a dealer.

Ford is transforming Customer Experience (CX) based on data across numerous brands, business sectors, and geographic units to improve predictive marketing. In 2018, the corporation launched the predictive analytics initiative, which included the reform of technology, processes, and personnel models for personalised consumer interactions. Though the project aims to improve customer experience at apparent touchpoints like dealership showrooms and brand websites, the scope is generally much broader. Many vehicle manufacturers focus on improving CX for bigger client groups and neglect to consider how to improve one-on-one encounters. However, understanding individuals and satisfying their distinct requirements as they travel through their unique customer life cycles has been at the heart of this shift from the outset.

In early 2022, FIDCAR, a start-up within the MotorK group and the EMEA region’s leader in SaaS1 automotive distribution solutions, and Stellantis & You, Sales and Services, have announced the signing of a commercial agreement in the domain of predictive marketing after-sales, putting AI at the heart of tailored customer relationships. This after-sales predictive marketing is a technique for providing customers with uniquely packaged offers at the proper moment based on the status of their car and their real maintenance requirements. The FIDCAR Predict solution is an AI platform that allows forecasting and promotion of after-sales offers that are perfectly adapted to the needs of customers in real time. Furthermore, the mobile application, FIDCAR Check, co-developed with Stellantis & You, Sales and Services makes it possible to greatly enrich the database that serves the FIDCAR Predict platform. This consequently improves marketing relevance and quality.

As of late 2019, almost 300 Jaguar Land Rover retailers were using Market EyeQ’s predictive analytics product to receive data-driven insights of their entire market. Market EyeQ provides a dealership access to all potential customers. On a single sales platform, the dealership has segment-specific access and utilises this real-time proprietary data and algorithms to discover, engage with, and capture more customers in a dealer’s market. The retailer’s own data in its DMS is enriched because of the rise in proprietary data, giving dealers a holistic perspective of their local market. This includes gaining a better understanding of opportunities they were not aware of.

The Future of Predictive Marketing

The ultimate objective for dealerships should be successful consumer interaction — customers who engage with dealership communications are four times more likely to buy from them. To achieve this properly, dealerships (and vehicle manufacturers in general) should collect significant quantities of online and offline customer data, evaluate it with predictive analytics, and forecast future actions. After qualitative and quantitively analysis, timely, relevant communications via direct mail, mobile or social media should be sent.

Looking further ahead, dealerships will be able to target customers through custom ads, mainly via social media. Dealerships should also ensure that their sales teams have the finest tools available to understand each consumer and close a larger transaction by integrating behavioural data and creating tailored marketing campaigns. In this rapidly changing industry, the key to success is to do everything smarter: think smarter, sell smarter, and anticipate smarter.