Korrelate, co-founded by Aqfer CEO Daniel Jaye in 2010, was a groundbreaking company that revolutionized the intersection of online behavior and offline purchases, particularly in the automotive industry. Jaye, a veteran in the ad tech space and former co-founder of Engage, brought his extensive experience in behavioral targeting to this venture.
During his time at Korrelate, Daniel Jaye and his team made some groundbreaking discoveries that challenged conventional wisdom in the automotive marketing space. Their work provides a fascinating case study in how data-driven insights can revolutionize industry practices.
Korrelate’s primary focus was on online-to-offline attribution, a holy grail for marketers trying to connect digital behavior with real-world purchases. In the automotive sector, this meant linking online activities to actual vehicle registrations.
Korrelate’s Automotive Industry Insights:
The Color Revelation
Perhaps the most surprising discovery was that a user picking and visualizing the color of a car was the strongest predictor of purchase intent. This seemingly simple detail outperformed traditional metrics like submitting lead forms or using car configuration tools. It’s a powerful reminder that emotional connections (like imagining yourself in a car of a specific color) can be more indicative of intent than rational actions.
Lead Form Fallacy
Contrary to popular belief, Korrelate’s data showed that lead form submissions were not the best indicator of purchase intent. In fact, only about 0.5% of car buyers had filled out a lead form. This insight challenged the entire lead-generation model that many auto marketers had been relying on.
Rich Data Insights
By partnering with Polk (now part of IHS Markit), Korrelate gained access to DMV registration data. This allowed them to provide incredibly granular insights, showing not just whether someone bought a car, but exactly what make and model they purchased – even if it wasn’t the brand they were initially researching online.
Competitor Intelligence
The Korrelate data didn’t just show who bought cars; it also revealed when people ended up purchasing from competitors. This type of insight is invaluable for understanding cross-shopping behavior and competitive dynamics in the auto industry.
Media Investment Optimizations
By linking online behavior to actual purchases, Korrelate could provide detailed diagnostics about which types of media investments were most effective. This went beyond simple click-through rates to show which activities truly influenced purchase decisions.
Privacy First Approach
Despite working with sensitive data, Korrelate maintained a strong focus on privacy. They used a “k-anonymous” approach in their data clean room, ensuring that individual consumers couldn’t be identified while still providing valuable aggregate insights.
Challenging the Status Quo
The work at Korrelate demonstrates the power of challenging assumptions with data. It shows how even in a well-established industry like automotive sales, there’s always room for new insights that can dramatically shift marketing strategies.
Moreover, it underscores the importance of looking beyond traditional metrics. While lead forms and configuration tools provide explicit data about user intent, Korrelate’s work showed that implicit signals (like color preference) can sometimes be more powerful predictors of behavior.
For today’s marketers, the Korrelate story serves as a reminder to continually question our assumptions and let data guide our strategies. It also highlights the potential of connecting online behavior to offline actions – a challenge that remains relevant in today’s omnichannel marketing landscape.