Recommender Systems

Over 15 ways to make personalized recommendations at the individual customer level

Our Recommender Systems are Machine Learning models that allow brands to recommend products, categories, offers or even content to customers at an individual level.

 

Data Ingestion, simplified

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 personalized recommendations that are relevant in all contexts, for each customer.

Ingest customer and transaction data into Recommender Systems
Machine Learning based Recommender Systems by SOLUS

Learning Algorithms

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.

For instance, Genome Matching is a strategy that looks at “what do people like you buy”, while a fairly distinct strategy is “what are your past preferences”. Both of these (and more) co-exist within SOLUS.

Outputs as Stories

Our recommender output are made available as “stories” – marketing-friendly ways to use the outputs from the machine learning system, without haveing 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.

  • Top N Recos
  • Cross Sell
  • Reorder
  • In Cart Based
  • Wishlist Based
  • Fav. Cat/ Brand
  • Exploration
  • Smartbasket
  • Recos Within A Category
  • People Like You
  • Trending In City/ Season
Marketing friendly Recommender system outputs ranging from Cross sell, Upsell, Exploration, Preference Based, Trending and more
Recommender output deployed in push messages, on landing pages, in App, on Web or provided as a service via a Recommender API

Recommendations Deployment

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.

Our Recommenders At Work

A Few Of Our Clients

Book a Demo to get a deep dive into how SOLUS AI can help

  E-301, 3rd Floor, Lotus Corporate Park, Off Western Express Highway, Jay Coach Area, Laxmi Nagar, Goregaon (E), Mumbai – 400063.

  slath@solus.ai

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