How Subaru Quickly Connected Its Data to Understand the Customer Journey
Subaru needed an analytics environment where data could be consolidated from multiple sources. This included daily feeds from campaign orchestration, web analytics, data management platform (DMP), and internal CRM systems that needed to be regularly keyed, loaded and linked in order for Subaru’s data scientists to begin the ultimate process of analysis, summary, and reporting. Subaru wanted the platform to have an automated data feed configured in less than 15 weeks. Both IT and marketing were eager for an early glimpse of possible data gaps, trends, and cross channel attribution.
Merkle partnered with Subaru to build an inventory of the most valuable data feeds to be onboarded. We quickly stood up our Rapid Audience Layer (RAL) platform and began ingesting Subaru’s data: CRM data (profile, purchase activity, etc. ), email and direct mail communications and responses, analytics clickstream data, and DMP digital log data.
At the same time, we worked to provision a cloud-based, big data environment capable of loading, storing, and exposing all the data elements needed for analysis. Such provisioning follows a standard playbook for standing up as well as enabling proper security for the platforms users. Proper data feed analysis allowed for the configuration of automated daily loads once the feed inventory was established. Our expert technical staff engaged directly with Subaru’s stakeholders for a very smooth deployment phase.
Digital and CRM data sources integrated in 12 weeks
Improved site and media activity metrics prior to a vehicle purchase
Better tagging across multiple data sources
Keys to success
- Clean Data: Ensured the timeline stayed on track as data quality issues can derail a project
- Technical Experience: Onboarding data quickly and the ability to foresee possible issues before they become true problems
- Strong Client Partnership: Direct access to key stakeholders and technical staff to help identify and expose data feeds
- Solid Understanding of Solution Goals: Helped the deployment team design a system that accounts for future use cases and realize overall value faster