Recommender Systems

Our Recommender Systems allow brands to recommend products, categories or offers to customers at the N=1 level. The SOLUS Recommendation System has the following features:

SOLUS AI takes in online and offline transactions, online behaviors, preferences, location and product data, and more. These multiple signals help it come up with recommendations that are relevant in all contexts, for each customer.

At the heart of the Recommender system are multiple recommender algorithms, each of which caters to a different strategy. This approach, combined with a “Recommender of Recommenders”, ensures that we solve for different contexts ranging from cold-start to the data rich.

Our recommender outpts are made available as “Stories” – marketing friendly ways to use the outputs from the machine learning systems, without having to get into what the underlying algorithm is. Want to Cross Sell? Want to drive Exploration? Want to push Reorder? There’s a story for every use case with SOLUS.

We’ve made deploying recommendations simple, and super-quick. SOLUS has business layers where a user can include or exclude recommendations, add stock and inventory checks or even bump up promoted products. Finally at the deployment end we have multiple options ranging from our custom short-link + landing page deployment to Recos as a Service.