Nanigans, the cross-channel SaaS (software as a service) platform for large-scale performance advertisers, has launched incrementality optimization and reporting in the platform, which supports Faceboook, Instagram, Twitter and programmatic retargeting campaigns.
The machine learning-driven solution aims to target consumers deemed likely to be influenced by advertising and limit spending on users who are already likely to convert.
Ric Calvillo, Nanigans co-founder and chief executive officer, said in a phone interview that the new service uses machine learning to predict revenue lift from an impression (a user) and make a bid based on that prediction in real time.
In comparing Nanigans Incrementality to a multitouch attribution (MTA) model, Calvillo said, “Giving partial credit to channels is broken. It’s just de-duping conversions but still using touch-based attribution. That confuses correlation with causality.” That’s because MTA gives credit to the impression or click even when those people would have purchased organically anyway without the extra ad exposure. Nanigans measures revenue lift relative to a holdout sample of people.