Algolia Launches Additional AI Models in its Recommend Spring Release 2022 to Supercharge Businesses’ Ability to Engage with Users

New AI-based Recommendation Models Overcome ‘Cold Start’ Challenge

Algolia, the leading API-First Search & Discovery platform, unveiled additional AI (artificial intelligence) models and capabilities in its Recommend Spring Release 2022. Algolia Recommend and Algolia Search, which power more than 30 billion search requests a week, enable any modern business with an online presence to enrich their end-user’s discovery journey by connecting them with the most relevant, actionable recommendations instantly.

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“We’re focused on having the best quality recommendations and making it easy for our customers to implement across their web properties. Algolia Recommend Spring Release 2022 helps organizations anticipate their users’ wants and needs, and recommends the right content to reach them within milliseconds.”

With this new release, Algolia Recommend introduces advanced AI models that are powered by behavioral insights, while being privacy-aware. When coupled with Algolia’s blazing fast indexing capabilities, customers are able to immediately put their most relevant and up to date content into motion for end-users. Algolia Recommend can be implemented and pushed to production in as little as four days with its no-code/low-code tools. Developers can also go under the hood if they wish to further tweak their implementation.

From a single dashboard, merchandisers, digital content managers, or digital business leaders can choose the model that is right for them, deploy it, and then track the results. The Algolia Recommend Spring Release 2022 includes the following new capabilities:

• Popular Trends – An innovative new set of AI models that detects emerging trends based on users’ behavioral data as they interact with various brands, categories of products and content, and topics of interest, all of which provide merchandisers and digital content leaders with the ability to engage instantly with visitors. This increases click through rates, reduces bounce rates, and helps visitors overcome a sense of ‘FOMO’ (fear of missing out) by surfacing what items are in vogue or topics that are trending.
• Business Rules – Low-code/no-code functionality for controlling AI and activating unique business strategies – without the need for developer intervention. This provides greater flexibility for category merchandisers, online retail strategists, and content specialists to generate powerful new recommendations while gaining significant operational efficiency and flexibility.
• Hybrid Recommend Engine – This is a combination of collaborative filtering algorithms and content-based filtering algorithms that together increase the relevancy and accuracy of recommendations. This approach overcomes the ‘cold start’ problem since recommendations can be presented immediately to users once the content-based data is indexed. Availability of behavioral information either at this initial stage or later can further help fine-tune and enrich the quality of recommendations. This new capability will enable all online vendors to increase user engagement more quickly and improve order rates.

In addition to the new capabilities above, Algolia Recommend supports the following popular capabilities:

• Related Products – This recommendation model enables retailers to increase conversions and orders by analyzing items shoppers interact with (e.g. clicks, adds to a cart, and/or purchases) during their sessions and suggesting similar products from this analysis.
• Frequently Bought Together – This recommendation model increases average order value (AOV) by upselling complementary items on the product page or shopping cart page based on what other shoppers have purchased with that same item during a single shopping session.

“As shoppers we have an expectation that there will be recommendations on category pages, PDPs (product detail pages), and checkout pages. It speeds up our discovery of the most relevant products, and for the brands themselves, it increases average order value, conversion rates, and repeat visitors,” said Bernadette Nixon, chief executive officer, Algolia. “We’re focused on having the best quality recommendations and making it easy for our customers to implement across their web properties. Algolia Recommend Spring Release 2022 helps organizations anticipate their users’ wants and needs, and recommends the right content to reach them within milliseconds.”

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According to a recent Total Economic Impact study conducted by Forrester Consulting, Algolia’s ranking algorithm improved the relevance of search results with measured increases of 40% to 50%, especially by mobile customers.

Several early users gained clear benefits. According to Claire Armstrong, director of digital products, at Fender Musical Instruments Corporation, “with Algolia Recommend, we are able to further promote a wide variety of our content, curriculum, and learning activities within ‘Fender Play’, the complete learning app for guitar, bass and ukulele, all of which are supporting the next generation of players on their musical journey.” Additionally, Flaconi increased their AOV by 10% and Gymshark boosted their order rate by 150%.

Nixon added: “Throughout the year, we will continue to innovate and add new functionality to the Algolia Search and Discovery platform. For example, later this summer, we will be releasing a new Merchandiser Dashboard, which consolidates all the functionality a merchandiser will need into a single, intuitive dashboard. This will enable merchandisers to very quickly surface the right content to their users, and comprises a broad array of merchandising capabilities, including category-level merchandising and powerful, AI-based business rules to manage re-ranking for any given category or query, plus much more. We built this dashboard specifically with the business user/merchandiser in mind, ensuring that they will be able to implement, test strategies, and experiment in a no-code environment. This is just one example for e-commerce use cases, however we will have many more announcements throughout the year.”

“IDC expects the intelligent knowledge discovery software market to grow to $11.3 billion in revenue in 2025 with a CAGR of 26.4% over the next four years,” said Hayley Sutherland, senior research analyst, Conversational AI and Intelligent Knowledge Discovery at IDC. “In this space, Algolia’s Search and Discovery Platform, and particularly its Algolia Recommend Spring Release 2022, has the potential to play a significant role in unlocking previously ‘hidden’ data and making content available for organizational decision making.”

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