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Predictive Analytics: Sales Driven by Data

The best decisions are those that anticipate adverse situations and predict results, which increases our sales effectiveness.

In sales, we are used to overcoming any obstacle in order to achieve our sales goals. However, the best decisions are those that anticipate adverse situations and predict results, which increases our sales effectiveness.

In this article we will look at two types of indicators that allow the Sales Manager to be proactive with their decisions and analyze available information in order to find ways to sell more:

  • Time-based indicators
  • Event-based indicators

Days before the next service

This time-based indicator is obtained by comparing two pieces of data: the date of purchase of each vehicle and the average date of its service. This difference in days can be used to calculate how far in advance each customer should be called to offer a service.

CustomerDate of purchaseDate of next serviceDays
Dan Wilson2019/03/022019/02/27362
Francis Robinson2019/04/202019/02/10296
Ann Jameson2019/04/222019/03/17330
Mia Thomas2019/05/022019/05/28392
Average days:345

Why is this information useful?

Customers whose next estimated service date is coming up can be invited to book a workshop appointment.

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Days after purchase

This time-based indicator averages the days elapsed between customers’ first and second vehicle purchases. This indicator is similar to the previous one, but is applied to the purchase of vehicles and parts; this indicator is subject to other customer-based variables.

CustomerFirst purchaseSecond purchaseTime
Mike Lopez2019/03/022022/02/273 years
Rich Hart2019/04/202023/02/104 years
Danielle Sullivan2019/04/222024/03/175 years
Julia Marquart2019/05/022023/05/284 years
Years average:4.25

Why is this information useful?

Depending on the type of purchase being analyzed, you can organize contact actions with customers who are close to meeting their next expected purchase date, and offer them products before they look for them at other dealerships.

Average kilometers at time of purchase

Imagine the following situation: a customer buys a new vehicle. A few years later they trade that vehicle in and buy a new one. We can use the trade-in’s odometer reading to calculate the customer’s vehicle usage average.

Why is this information useful?

Your DMS can show you a list of customers whose vehicle mileage is, for example, between 100,000 and 200,000 km. You can then launch a targeted marketing campaign aimed at those customers to offer them a new vehicle.

This same indicator can be used to plan Upselling campaigns. Taking the previous list, you can filter by vehicle model to offer them newer models of the same brand.

Predictive indicators are the key to success for proactive dealers who do not sit and wait for opportunities, but instead seek them out. The opportunities are there as are the tools to take advantage of them, the question is: what are you waiting for to sell more by using your data?