Machine learning: Personalized product recommendations and in store experiences

machine learning is rapidly gaining public adoption and at aiq we have some of the best specialized models in the business aiq models are trained with the fullest picture of a customer across in store and online engagements don't limit yourself by only trusting models that are trained using a single source of data pos systems, online menus, messaging platforms, website analytics, and programmatic are not sufficient on their own to give you a global picture of what a customer is likely to buy next aiq trains its systems to learn what a customer will buy next based on thousands of interactions happening every second of the day across 1300+ of the worlds largest specialty retailers, delivery, and online selling mediums on the planet ecomm page interactions loyalty member engagements native app engagement events web app engagement events website cookie/ fingerprint derived events (pixels & utm) in store pos the staff member checking them out (avg rating by customers, most sold product/ brand, etc) how long they were in a queue what products and messages they were shown before being in queue (opened, converted after, spam filtered, etc) their favorite store and it's geographical positioning to borders or other stores selling similar products the list goes on and on across over 50+ integration partners you have at your disposal within the aiq eco system in an effort to boost the power of the retail and marketing eco system and offer unreal experiences to consumers globally, aiq has released endpoints giving you the ability to modify the content shown on in store screens based on who is in the waiting room and currently checking out (4 out of 5 people buy 99% edibles, show edibles content and deals on screens as they walk in) enhance the retail sales process by giving sales personas live highly specific recommendations for each customer that they take care of, increasing avg ticket size and eliminating customer frustrations our endpoints also allow you to limit recommendations to products that are in stock know what to buy from wholesale manufacturers (all recommendations can be bundled with audiences limitless options such as "what should we purchase for our top 20% spenders that have visited the store only 3 times and have also purchased wana edibles in the last 8 days) showcase the exact products a customer is likely to buy within your e commerce store product listings just like amazon to convert traffic like a monster! how to get recommendations via api get personalized recommendations for a contact id