BMW was losing market share and struggled to effectively analyze available data across their media - allowing for only a partial view of the consumer. We wanted to implement a smarter data management process that would provide a holistic understanding of each consumer and help get them to the dealership.
With contemporary consumers taking a purchase path both on and offline, data is often fragmented, flawed and volatile; analysis requires careful management and reconciliation. The luxury auto category had seen declining sales of nearly 8% YoY. Budgets had been slashed, and luxury auto manufacturer BMW was losing market share. As our competitors garnered improved sales numbers, we needed to find a solution for BMW to regain Share-of-Voice.
As we processed partial data from numerous partners, we realized that each partner was wholly focused on the part of our consumer that they had access to. This, compounded with the insight that less than 10% of automotive consumers submit their contact information online in the research process, made it clear that none of our disparate data streams would ever truly be able to provide us with a full, proper and clear understanding of BMW's target audience.
This partial view of the consumer path to sale could and would lead us to massive missed opportunities. In such, we needed to merge all of the fragmented views of our consumers into a comprehensive ecosystem for measurement and strategic audience development.
We also identified location data as a key element of offline data that was missing and would be integral in understanding our user experience.
We set out to find ways to cohesively match this data, not only with the BMW user, but with the specific advertising - down to the creative size and inventory source - that each visitor was exposed to during the campaign lifecycle.
Enter: "The Ultimate Data Machine" - a unified ecosystem and data warehouse that helped create a unified view of BMW prospects to target more precisely across all media channels. Due to data fragmentation that existed in the marketplace we built a machine that:
- Allowed for flawless CRM & custom High-Value Audience ingestion
- Allowed for development and extension of our first-party audiences
- Had API conversion integrations to measure actual dealer visits for multiple data points and media activations
In most campaigns, digital marketers try to gather as much information as they can about their tactical performance and connect their strategies to measurable results. However, while the automotive industry standard proxy has traditionally been online leads, consumer behavior has changed. Less and less people are willing to divulge information and opt in to be contacted by a dealer.
In order to achieve success, we needed to improve the overall quality and richness of our data. To truly identify and understand current and potential consumers, we started with online paid and owned data, moved to second- and third-party data, offline foot traffic, and finally vehicle-level CRM data. Within our effort to create a more robust picture within these disparate sources, we shaped our high-value audiences - a new baseline for BMW. These consisted of users who had shown interest in the brand or model, are in-market, and are actively engaging with BMW through their social networks.
Campaign activation successes from this initiative were also driven in part by the insights made possible through our footfall data integration. We set out to answer the question: Of the people we exposed to our digital creative, who actually went to a BMW dealership? We focused "The Ultimate Data Machine" on the consumer experience and bridged audience, device and location into one cohesive targeting and measurement approach.
We initiated a process to carefully translate and consolidate all digital data into one universal ID through creative usage of various digital user lookup references and sources. Our BMW "Ultimate Data Machine" worked to continually improve our digital media buys through learning, analyzing and then optimizing.
With access to footfall data mapped to BMW's 343 dealership lots in the form of Device IDs, we ingested it into our Data Management Platform - proving to be a crucial step. This allowed us to determine whether or not we had previously served these visitors with BMW digital messaging. By being able to measure in-person visits stemming from media, we could measure program effectiveness in an offline context. Therefore, we could determine the ideal budgetary distribution needed in the marketplace to drive dealer visits.
Our measurement strategy was a two-pronged approach of fast-moving KPIs and slow-moving KPIs. The "Fast KPI" was an instantaneous measurement, such as incremental dealer visits through our footfall conversion API, or an increase in site actions, serving as a proxy for how media was doing in the moment. The "Slow KPI" included car sales, and the analysis of our audience's behaviors and personal attributes. We joined our fast and slow moving KPIs for a data-first planning approach, again contributing to the ultimate goal of increasing dealer visits, and reducing media overlap and fragmentation.
By implementing these new processes, we improved the quality and richness of our data, created stronger insight into that data, and drove positive business outcomes for BMW.