Understanding Customers’ Vehicle Service Patterns
We gathered service details (type of service, vehicle mileage at the time of service, etc.) and customer information (type and category of vehicle, customer age and address, etc.). This was analyzed to determine customers’ commitment to get their cars serviced on time, the number of times per year they brought their vehicles into the shop, and the dollars spent per service.
AI and ML were used to add geographic and demographic data to develop unique customer profiles. These were studied with the goal of discovering what would motivate customers to a deeper level of brand loyalty – one that extended to the maintenance of their vehicles.
Defining a Loyal Customer
With the additional insight this study offered into vehicle maintenance patterns, our client:
- Created a model which could segment their buyers into ‘high repeat purchase’ and ‘low repeat purchase’
- Could use the information gleaned from this study to create a marketing strategy designed to bump their ‘low repeat purchase’ segment up into the ranks of loyal customers.