Aligo's approach allows target recommendation to happen in real-time without having to rely on historic purchase data. This makes this approach less susceptible to the "Cold Start" problem.
The Cold Start Problem
In system analytics, the cold start problem refers to an issue common to automated recommendation systems where the machine cannot make any inferences about an item due to the lack of available information. Since such systems typically build upon an existing database of content filtering or user interaction, recommendation becomes difficult in the case of new communities, new items, or new users which have yet to build interactions.
In the context of the modern digital marketplace, it becomes all the more important to be able to successfully tackle this problem as the constant influx of new offers makes garnering attention at launch crucial.
Aligo takes the issue of customer privacy seriously, and all variables are anonymized in order to ensure that no identifiable and personal characteristics can be derived.