MET-A data

Challenge

Find a solution to the evergreen problem for the automotive industry: tying online consumer behavior to vehicles sales data.

Automotive brands face a unique set of challenges. A user’s online experience is distinctly separate to what actually happens in a dealership. There has been no way for brands to correlate a user’s online research, with how that directly influenced the sale of a vehicle.

Utilizing Google Marketing Platform (GMP) we could understand what users do onsite, which channel drove them to the site, when they downloaded a brochure, or requested a test drive. However, any analysis was purely restricted to online, where a lead is considered as good as a sale.

Solution

We activated our MET-A data framework. Through the discovery phase, we identified that MINI send their customers a post-purchase email. By appending parameters to links in these emails and some advanced configuration in Google Tag Manager and Google Analytics, we identified consumers who had purchased a vehicle. Once we bring the consumer back on site, ID’s can be linked and we are able to understand the research each anonymized customer undertook prior to entering the dealership, as well as which vehicle was purchased.

Using Google Analytics 360, this rich data streamed into Google Big Query daily, allowing us to discover deeper insights.  This new series of metrics enabled us to visualize the full consumer journey from beginning to end.

Results

This dynamic creative strategy saw a 22% increase in CTR instantaneously.

We found that customers we predicted had a ‘high’ probability to purchase had purchased cars at a rate of 4.3 times that of other audiences. Seeing the results across real data meant we could accurately validate this model.  

MINI is now clearly able to track online to offline conversions for the first time. We can now see the online journeys of over 60% of MINI’s customers, prior to making their purchase decision.

We’ve been able to define new metrics and measures of success for activation and real-time optimization.