(Credit image/Pixabay)Algolia, an API Platform for Dynamic Experiences has launched Algolia Recommend. An Artificial Intelligence (AI)-optimised API that accelerates the creation and implementation of product or content recommendations across digital touchpoints.

Algolia Recommend surfaces in milliseconds the most relevant recommendations, offers, or suggestions for an online shopper. The App uses Machine Learning models that collect data from two sources: shopper behaviour. (The shoppers’ actions across a website or app, including previous purchases.) In addition to product data (all product attributes contained in the product catalogue, including product, description, availability, and price).

The company says what makes Algolia Recommend unique is the fact that it is simple to integrate. Anglia says it requires as little as six lines of code — and easy to use because it is developed with an API-first approach. Conversely, building a recommendation engine from scratch can be complex. Relying on off-the-shelf, packaged solutions makes it almost impossible to develop a differentiated customer experience or gain a competitive advantage.

Orange România use case

An example use case, Orange România uses Algolia Recommend technology to retain and convert shoppers landing on out-of-stock products. According to Florin Spataru, digital marketing manager at Orange România, “By recommending different, but relevant products, we were able unlock eight percent more revenue on our online store.”

Algolia Recommend is expected to have an impact on increasing the average order value through shopping cart expansion. In addition to customer satisfaction in online stores. The app enables retailers to earn greater trust and loyalty by demonstrating a richer understanding of customers. This is done by surfacing highly relevant recommendations in the moment.

API-first approach to search and navigation

According to Jordan Jewell, research manager, digital commerce at IDC, “Due to COVID-19, retailers saw record growth in 2020. It raised the stakes for practically every organisation to have a digital commerce strategy. In this hyper-competitive market, merchants must provide customers with unique, personalised, and frictionless commerce experiences to succeed. An API-first tech stack is the foundation of these differentiated experiences.”

Algolia’s API-first approach to search and navigation is well suited to enable the future of commerce. With Algolia Recommend, merchants and developers can add a new API to their toolkit. To build more comprehensive digital commerce experiences and grow online sales.

Delivering tailored recommendations

Algolia Recommend initially includes two of the more popular machine learning models that automatically deliver tailored recommendations.

  • Related Products: This recommendation model enables retailers to increase conversions and orders by analysing items a shopper interacts. (e.g. clicks, adds to a cart, and/or purchases) and suggesting similar products during the same session.
  • Frequently Bought Together: This recommendation model increases Average Order Value by upselling complementary items on the product page or shopping cart page. This was based on how other shoppers have interacted with that same item during a single shopping session.

Personalised content

(Image credit/LinkedIn/Julien Lemoine)
Julien Lemoine, co-founder and chief technology officer of Algolia

Algolia recently unveiled its new company direction and vision. It helps customers go beyond the search box with digital commerce strategies,” said Julien Lemoine, co-founder and chief technology officer of Algolia. “The release of Algolia Recommend provides the next building block for retailers to optimise their online experience and increase revenue. These retailers have already unlocked $1 billion+ additional annual revenue. This is on the back of up to 1.7 trillion searches across Algolia’s API platform.”

In a recent survey published by Statista Research, 42% of respondents said that it was “very important” or “somewhat important” to see personalised content. (This included recommendations, offers, or experiences). When studying the impact of product recommendations in the US, 38% of respondents stated they would shop “much more frequently” or “more frequently” at online retailers if they received such recommendations.

Enterprise Times: What this means for business?

Relevant and pertinent content is the lynchpin of the new digital world. Savvy customers expect deeper, relevant experiences and personalised engagement. To deliver on this, Brands need to deliver relevant content, in the context of the consumer. Brands have to deliver personalised product recommendations that enhance the shopping experience. Treat customers as individuals with hyper-personalised product recommendations, as opposed to bombarding them with digital adverts. Algolia says implementing its new functionality requires just six lines of code. Integrating product recommendations tools is not particularly challenging. The set-up of many product recommendations are normally straightforward. The key task is normally the ‘listening mode.’ The period of time before production recommendations APP goes live on the site. At this stage, the App is accumulating relevant site traffic data to facilitate the recommendation configuration. If brands are serious about personalisation then adding a product recommendation tool is essential.


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