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How Porsche Retail Group used machine learning to reach new audiences with intent to buy approved pre-owned cars

Objective

To grow Stock Searches for pre-owned Porsches as cost efficiently as possible.

Challenge

Porsche Retail Group wanted to increase sales of pre-owned Porsches by using a cost-effective way of driving enquiries for pre-owned stock (Stock Searches).

Porsche Retail Group teamed up with iotec to use machine learning that went beyond traditional contextual and demographic targeting, to drive enquiries from an audience with intent to buy a pre-owned car.

Through the use of first party data and machine learning, iotec was able to identify signals of intent among existing Porsche customers and target prospective customers who shared the same behavioural patterns. Prospects then searched the available pre-owned Porsche stock and placed enquiries to their local dealership.

 

Solution

To find high quality consumers demonstrating intent to purchase a pre-owned Porsche, first party data from Porsche Retail Group customers was combined with iotec’s proprietary behavioural data. iotec’s machine learning technology identified the behavioural patterns that distinguished them from other people. Once a seed audience was identified, iotec’s machine learning used the data to optimise towards the CPA goal.

Results

 

 

 

 

 

 

 

 

 

iotec provided a top level of client communication and clarity and honesty on results with regular new insights on our customers’ journeys. We now have a greater understanding of how users search and use our website.
Sean McCorkindale, Group Marketing Executive, Porsche Retail Group

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