Personalized targeting using look-alike modeling to increase revenues

LatentView Analytics helped a leading online payments company improve its digital targeting efficiency using look-alike modeling to identify the right customers for campaigns thus generating more revenues.

Business challenge
The client was using demographic information of their customer to create lists for campaigns without taking into account their past buying behaviour. As a result, the effectiveness of their sales campaigns was limited. The business goals were to streamline target marketing campaigns and identify a set of customers to match-and-mail.

Solution
The client regularly ran marketing campaigns for its existing customer base, in partnership with large merchants, to promote usage of its payment gateway. LatentView Analytics worked closely with the client’s team and enabled them to run marketing campaigns focused on target lists generated through predictive models with multinational merchants.

Results
LatentView Analytics tested the effectiveness of the model-based solution against the client’s in-house approach. In all campaigns, the LatentView model significantly out-performed the in-house solution in terms of incremental transactors as well as sales volume (measured relative to a control group).

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