Case Studies: Chapter 10 – Automobile OEM & Lead Scoring

Automobile manufacturer improves lead scoring for potential buyers

Car manufacturers – or OEMs as they refer to themselves – are partnered with a dealership network of independent businesses. The role of the OEM’s website is to drive demand for the brand and generate leads for their network. 

At the top of the sales funnel, there are (hopefully) many more leads coming in to dealerships than they have salespeople available. So which of the leads should their sellers email and call back first? Where should they focus their time and energy? 

That’s the same challenge sales teams face in many industries, e.g., B2B and financial services. It’s the domain of lead management, and it is typically supported by lead scoring.  Namely, the leads are scored based on behavior and other profile information to rank them by their value and their likelihood to transact in the near term. As a result, sales teams can engage with the most “ready” leads for a conversation. It’s a win-win for everyone.

In our case study, lead scoring was already implemented at the US car manufacturer a decade ago. Their system leveraged website behavior as part of its scores, e.g., whether the individual completed car configurations and which ones. When the individual completed a lead form, their lead score was attached to the profile. Dealers were able to rank incoming leads by this score. 

Before enriching with Experience Analytics data

In their evaluation of this program via response attribution, the OEM found that leads that the system scored as “hot” were six times more likely to complete a car purchase. And even leads scored as “medium” were still twice as likely to buy a car as “cold” leads—a massive success.

After enriching with Experience Analytics data

Now, imagine what Experience Analytics data could do to improve this effort? Here you can score: 

  • Where is each lead in their journey, e.g. window-shopping vs. actively in the market?

  • How engaged is the individual with various models or aspects of the cars?

  • What attracts them, e.g., visuals or specifications?  What are the colors or engine details that they are interested in?

Real-life car salespeople do this in the blink of an eye.  Hopefully, they leave us alone to browse the car lot when we’re just orienting ourselves, but somehow they are right there when we seem to be in serious buying mode. Experience Analytics can help make the online car shopping experience a better one.