We’ve predicted the likelihood of motor purchase preferences of Australian households for specific types of new and used vehicles (e.g Small SUV), specific makes (e.g Hyundai) and a combination of both (e.g Hyundai Small SUV).
We’ve built a series of audience segments that achieve on average 12x improved targeting effectiveness at the top centile of our models. So how do we do it?
smrtr’s propensity models identify households with an increased likelihood to purchase over 240 specific types of new and used vehicles (e.g small SUV), specific makes (eg. Hyundai) and a combination of both (eg. Hyundai Small SUV).
The models are scientifically validated against actual purchase data we receive as an ongoing supply. In the Mercedes Benz example, the actual and predicted lift over random (baseline) is highly correlated. So the models do what they are supposed to!
The possibilities are endless, but the most common applications for this data asset include:
Car manufacturers: can target buyers using predictive analytics down to an individual make and model.
Finance & Insurance companies: can target car finance and insurance prospects using a combination of demographics, income, and vehicle preference.
Media: can extend their targeting capability and offer much richer insight to their audience.
We have all the answers! Well, maybe not all but we’ll do our best to help.