Our customer, a globally operating German car manufacturer, employs nearly 130.000 people and is one of the largest commercial enterprises in Germany. The traditional company, which looks back on more than 100 years of history, is one of the premium brands in its sector.
The after sales business is highly important in the automotive industry. Apart from the sale of new vehicles, the service, parts, and maintenance business constitutes a significant share of the profits. With increasing competition and decreasing customer loyalty it has become ever more important to retain customers and to submit the right offer at the right time.
thaltegos supported an automobile manufacturer in the prediction of service intervals to enable a targeted sales approach. For the prediction of the next service event in after-sales it is crucial to define the relevant customer segments as well as influencing factors on the service intervals. For example, the intervals for an oil filter change can differ considerably depending on the vehicle model and age. To include these factors in the prognosis, service history data have been used as a starting point. Based on this information, the “Interpurchase Time (IPT)” – the time between two consecutive service events – as well as factors influencing the IPT have been extracted. Consequently, it was possible to determine the effect of specific factors and to derive a regression model for the prediction of service intervals.
By means of this model, future service events can be predicted more precisely than before. Compared to the simple sequence continuation, the share of correctly predicted service intervals is 20 % higher with the regression model. Hence, for instance the next oil filter change of a vehicle can be determined more accurately and the customer can be approached in time. The prediction of service intervals enables the automobile manufacturer to carry out targeted marketing actions in after sales. Depending on the service demand and service time it is possible to individually approach the customer with the right offer at the correct moment. Furthermore, segments at risk of customer churn can be identified to launch measures for customer retention. As a result, dealer and workshop capacities can be planned better and customer loyalty and profitability are positively influenced.