Leverage our ecosystem user profiles data and our machine learning-based recommendation engine to generate precise and complete look-alike seeds for social media targeting.
We leverage online browsing and shopping profiles, offline consumption habits, experimental data-driven behavioural traits (e.g. brand loyalty, social influence, individual price sensitivity) to train our neural-net based recommendation engine to generate user seeds for look-alike marketing in social media
Multifaceted data sources allows building seeds with exceedingly superior performance compared to simple "best-shopper" seeds not to mention the crude demographics-based targeting
Our approach allows uncovering many more hidden pockets of value that are typically obscured by the subjective definition of "target consumer"
Targeting model is designed to continuously improve precision, i.e. your advertising ROI will be continuously improving taking in the feedback of the advertising campaign. Many of our clients leverage this feature to only launch mass scale campaigns when optimal targeting precision has been reached.