Reflect sales trends in real-time in your creative by driving product decisioning with a recommendation engine. Adacus recommendation engines create a real-time data flow from your site or offline sales system to your creative, leveraging often unpredictable spikes in product sales without the need for manual decisioning rules.
Drive in-ad product decisioning based on overall sales trends or trends specific to a user's profile by leveraging Adacus' user profile data for in-ad product recommendation.
Algorithmic Creative Decisioning
Adacus goes beyond multivariate creative optimization by incorporating it's extensive user data to algorithmically assemble and serve the optimal ad for each user. Simply select variations in 2-3 components of a creative - image, tagline, etc - and Algorithmic Creative Decisioning learns within weeks what creative variations maximizes each user's propensity to convert. This is the most advanced creative optimization technology available.
Algorithmic Decision Tree Generation
When you run an A/B or multivariate creative test, Adacus automatically drills down into segment-level test results to identify the optimal personalization strategy for your brand. While Algorithmic Creative Decisioning is a "black box" machine learning method, Algorithmic Decision Trees are a "white box" alternative that displays in our dashboard the Creative Decision Tree that maximizes whatever conversion metric you choose.
Machine Learning with Cookieless User Profiles
Only Adacus can apply machine learning to creative optimization, because of our investment in cookieless user profiles and offline conversion tracking. Cookieless user profiles - the 1000+ demographic and interest segments that Adacus applies to near 100% of users - are critical to train a machine learning model about what types of users respond to which creative elements. Offline conversion tracking is critical to do creative optimization at all for the majority of brands that lack access to order data that can be onboarded to devices.