Product recommendations
Recommendations in commerce search are a crucial search and discovery feature to help shoppers discover products more efficiently in your catalog and enhance their shopping experience.
Recommendations are relevant product suggestions; they aren’t related to the query but to products. They're helpful in multiple situations, even when no search results are returned. Whether a shopper lands on your commerce store and hasn’t written any query yet or if a search doesn’t bring back any product results, product recommendations amaze shoppers with product discovery inspirations.
Recommendations are generated based on numerous factors, such as collective shopping behavior, popular product preferences, and even semantically related search products based on respectful AI-powered search mechanisms. For example, you can predict your shoppers' intentions by displaying a list of the latest trending products in your store, recommend shoppers a brand’s new line of products when they first enter into your commerce search, or even provide a myriad of related products that meet your shoppers’ search intentions when your product catalog doesn’t match the exact search terms used.
Shaping your commerce search with product recommendations
Based on your business strategy, you can add product recommendations in your commerce search in different forms and locations at every search and discovery stage:
- Pre-search: product carousels previewing top-clicked or brand-related products can inspire shoppers, even before shoppers start to search.
- During search: the most popular products in your store can be displayed in the predictive search layer while shoppers are formulating their search.
- Post-search: carousels with products other shoppers have been interested in, related products commonly searched together, or similar products in your catalog help shoppers discover products directly on the search engine results page (SERP) they don't even know are available in your catalog.
You can use the corresponding Empathy Platform X components to display product recommendations wherever you want in your commerce search, for example, the search experience landing page, the predictive layer, the SERP, or even the product’s description page.
Recommendations catalog
Empathy Platform offers a complete catalog of product recommendations to amaze shoppers with a discovery experience according to their needs and your business strategy:
Spot the difference
Even though recommendations and suggestions are features that contribute to a more user-friendly and efficient commerce search and discovery experience, catering to different stages of the shoppers’ journey on your commerce search, both features serve different purposes for shoppers and commerce search owners. Empathy Platform recommendations focus on product results to enhance the overall discoverability experience, while suggestions help shoppers write accurate search queries to find relevant products quickly. In short, recommendations directly relate to products, while suggestions apply to search queries.
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Explore the Empathy Platform catalog of features on product recommendations and search suggestions on Learn search and discovery features in Empathy Platform.
Try Recommendations to...
- Make it easier for shoppers to discover relevant products and streamline the search and discovery experience.
- Help shoppers find relevant products quickly, reducing bounce rates and abandonment.
- Support shoppers in discovering more of your product catalog based on what others are already interested in.
- Inspire shoppers with brand products they trust while helping brands have customized storefronts in your commerce.
- When shoppers have found what they want, offer them products that complement their current selection and complete their shopping list.
Privacy-first product recommendations
Product recommendations in Empathy Platform are developed with privacy by design. Privacy-first product recommendations are essential in your commerce search to ensure a positive shopping experience while respecting shoppers’ privacy and data protection.
From privacy-first event data collection to semantic models trained with domain-based anonymous datasets, product recommendations allow you to create product discovery experiences without storing personal data and respecting your shoppers' privacy with consent-integral processes. So, Empathy Platform implements product recommendations for contextualized experiences leveraging artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) techniques respectfully.
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Learn how Empathy Platform services ensure the privacy and integrity of data retrieved from shoppers' behavior, on Understand data privacy and Protecting privacy and integrity in semantic models pages.