We created the agnostic recommendation system that can be used as a service with a simple API (Application Programming Interface) integration and suitable for e-commerces, magazines & mobile apps.

A bookstore is a cool warehouse with a bad recommendation system

That’s an inconvenient truth we all are facing. The old-fashioned bookstores are beautiful places to spend time but they are also very inefficient in terms of conversions. As Client, you are buying a book for two reasons, mainly:

  • You already know what book you want to buy
  • You buy a book to justify the time spent in the bookstore

That’s why we are buying even often books online, because even if we are losing the fancy experience in the real world (bookstore) we get better (online) recommendations.

We live in a Recommended world

Two thirds of the movies watched on Netflix are recommended ones. We suppose to choose, but we are addressed to few options by algorithms. Sounds scary? No, if the algorithm is explainable and clear (https://ec.europa.eu/jrc/en/publication/robustness-and-explainability-artificial-intelligence).

Recommendation System Benefits

Deliver Relevant Content

By analyzing the customers’ current site usage and their browsing history, a recommendation engine can deliver relevant product recommendations as they shops. Data is collected in real-time, thus the software can react and incorporate new trends on a user-by-user basis.

Engage Shoppers

A personalized experience and the recommendation of relevant products increase the shoppers’ engagement. Shoppers can delve much more deeply into the product line, without having to perform search after search.

Convert Shoppers to Customers

Converting shoppers into customers requires a special touch. Personalized interactions provided by a recommendation engine show your customers that they are valued as individuals. In turn, this strengthens their loyalty.

Increase Average Order Value

Average ordervalue typically goes up when a recommendation engine displays personalized options.

Increase the Number of Items per Order

In addition, the usage of a recommendation system, not only causes the average order value to rise, but also an increase of the number of items per order. When the customers can comfortably choose among options that meet their interest, they are more likely to additems to their purchase.

Main Key Performance Indicators

Click-thru rate +90%
90%
Conversion rate +40%
40%
Revenues +50%
50%
Revenue per visit +5%
5%

One API for endless possibilities

  • Simple integration
  • No maintenance
  • Pay per use

Endpoints

  1. Upsell → recommend alternative products, generally more expensive, and of higher quality
  2. Related products → bundle products related to the considered one, and often bought together
  3. Similar products by specs (iPhone → Samsung Galaxy S)
  4. Recommendation:
    • Home page recommendation
    • Checkout recommendation (a history-dependent, bought-together treat. Generally cheap)

Contact us for a demo and additional info

We are more than happy to showcase our solution and to explore the right approach for to increase your business.

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