In the age of Big Data, vehicles have begun reporting information about customer usage, trends, location and much more to the manufacturer to inform product development and go-to-market strategies.

Imagine if dealerships had a similar feedback loop with their customers – to know which vehicles a consumer is interested in and the exact time they are considering making a purchase.

By leveraging behavior prediction analytics, dealers can accurately identify which customers are most likely to buy and the reasons why. All of this helps to nurture customer relationships and leads to increased loyalty, retention and sales.

Behavior prediction is possible because of the vast amount of data available created by customers. As cars become more connected they send upwards of 25GB of data to the cloud an hour, which helps anticipate the time before another purchase.

Customers spend 59% of their shopping time online, asking for recommendations and visiting OEM and dealer websites. These are essential data points, leading dealers to their next sale. The industry is working at a rapid rate to be able to take this data and turn it into a meaningful transaction for both the consumer and the dealer.

A typical dealer management system bundles information about a customer, such as purchase and maintenance history. However, DMS programs are limited to information generated from a customer visit and cannot be used to anticipate future behavior.

DMS tools now can take this one step further and utilize Big Data, combined with proprietary behavior prediction technology, to take thousands of data points and create an accurate picture of a potential customer. To help dealers more precisely target their next customer, a modern DMS should include demographics, vehicle history, social-media information and information from the OEM about deals obtained in real time.

Sales staff should have access to this information delivered directly to their desktop, and include a customized marketing campaign tailored specifically to each customer using predictive analytics. The report should include an evaluation of how ready a customer is to make a purchase, talking points to drive them toward a purchase and micro-targeted mail campaigns targeting their vehicles of interest.

By leveraging behavior analytics in this way, the dealership gets the upper hand and can better influence sales.

A streamlined, data-driven sales process is important to maintain a positive car-buying experience. Some 79% of customers want their in-dealer buying experience to be completed in less than two hours. According to a recent study, the average customer spends more than two and a half hours purchasing a vehicle and satisfaction begins to dip after 90 minutes.

Effectively using predictive analytics helps shorten the sales cycle, ensures the customer remains satisfied and boosts productivity 25%.

By embracing new technologies, Big Data and predictive analytics, dealers can improve the car-buying experience for everyone involved, while driving sales and profits.

The key to success in this evolving market is to not just sell cars smarter, but to do everything smarter: marketing, selling and predicting.

Johannes Gnauck is CEO and co-founder of automotiveMastermind, a provider of predictive analytics and marketing automation technology for the automotive industry.