Sleek, Fast, And Sporty: The Propensity Model
Net Conversion ties offline and online data signals to improve audience targeting and propensity to buy.
Situation
To better understand the quality of the online leads coming from our media and to learn more about the Karma Revero purchaser’s customer journey from ad exposure to website visit to purchase.
Objective
- Develop a more accurate profile on Karma’s target consumer by tying together data systems with third party data appends
Implementation
Tying our Google Analytics, DoubleClick ad server and Karma’s CRM platform, we could connect the dots between web behavior, marketing channels, and offline data, including information on whether a consumer test drove or purchased a car. The online to offline integration allowed us to gain a better understanding of the full customer lifecycle from when they were first exposed to media, visited the site and ultimately purchased a vehicle.
Results
After integrating the offline and online data signals, we layered customer segmentation provided by a third-party data broker to create a more complete picture of a purchaser. We were able to successfully apply psychographic and demographic data to improve paid media targeting and reach more qualified consumers with a propensity to purchase.
As we collect more data, this will give Karma the ability to rank their leads by assigning a propensity score to each based on their likelihood to purchase a car.
