The Right Analytics for the Auto Services Industry

William Cao  |  Chief Analytics Officer

January 23, 2016

Analytics can give you a huge competitive advantage if implemented properly. But before you invest in them, it’s important to know which type works best for the automotive services industry.

Although there are many different analytics applications, they basically fall into three groups:

  • Descriptive
  • Predictive
  • Prescriptive

What you invest in should depend on the objective you are trying to achieve. Let’s take a look.

Descriptive analytics

Descriptive analytics summarize the transaction data to help you understand what happened in the past. Depending on how you collect data, “the past” could mean a couple of years ago … or even one minute ago.

Your sales report is a typical example of descriptive analytics. It helps you understand:

  • What happened?
  • How did your results compare to your plan?
  • How many sales were made, and where?

Predictive analytics

Predictive analytics take you one step further than descriptive analytics. Using your historical data and predictive analytics, you can begin to predict what might happen in the future. If a customer were to come into your store for an oil change today, wouldn’t you want to know when his vehicle would be due for the next oil change, and the likelihood that he’d come back to your store? These are the types of questions predictive analytics can address. They can also tell you:

  • Who are your best customers and what is the best way to target them?
  • Which customer is more likely to respond to a coupon promotion?
  • Which promotional offer is going to be most effective?
  • Which service is the customer likely to need next?

Prescriptive analytics

Once you understand what happened in the past and what might happen in the future, you’ll want to know what you should do next.

Consider prescriptive analytics like you are looking in the rearview mirror while driving your car. Predictive analytics are like a GPS tool that gives you directions, real-time traffic and weather information, and rerouting options if you run into traffic problems.

For example, if you offer brake, transmission, and other services to your customers, in addition to oil changes, you’ll want to recommend one particular service to each mail target to improve response. Which one should you recommend? This is the type of question prescriptive analytics can help you address. Building on the foundation of predictive analytics, they can help you optimize and identify the best scenario for every customer interaction.

So, depending on your goals and objectives, you might need just one type of analytics or a combination of all three. If you would like help determining which one will be best for you, drop me a line at I’d be happy to discuss your specifics and help you develop a plan.

William Cao
William has earned an MBA from The University of Chicago Booth School of Business, an MS in statistics from Kansas State University, and an MS in applied mathematics from Southeast University. William and his team provide data and analytic leadership to Catalyst’s clients.

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