V12 Debuts Active Vehicle Shopper Model

In the US, marketing analytics provider V12 Data has released an in-market automotive model, to identify consumers actively shopping for vehicles.

Acquired by Datamentors in 2016, V12 uses proprietary technology to give business clients access to billions of consumer, business and automotive records. Last year, the firm launched automotive purchase-intender audiences, a service allowing brands to target consumers who are actively shopping for vehicles. Its new model is built on the firm's Vehicle Identification Number (VIN) database, V12 AutoID, which contains information on over 215 million consumers and 186 million VINs. The in-market model uses real-time shopping behavior data and machine learning, identifying consumers who it says are 4.5 times more likely than the average US population to purchase a vehicle within a 90-day timeframe.

The model was built using V12 Data's proprietary intender solution, V12 Signals, which uses mobile location device data to identify in-market shoppers who have visited a dealer's lot or automotive aftermarket location within the previous 24 to 48 hours. Using machine-learning processes, the model is continually ingesting this feed of in-market behavioral data to deliver predictions and recalibrate, and as part of the development process, V12 Signals data is validated against verified auto purchase data.

CEO Andy Frawley (pictured) comments: 'Our new model is highly predictive, using in-market behavior indicators versus historical data. Using current purchase-intent data, we are able to more effectively predict who is in the market now. Today's business climate is constantly changing and evolving, and these real-time factors combined with our machine-learning platform have allowed us to build a truly competitive model that adapts to market changes'.

Web site: www.v12data.com .

All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.