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How does a product recommender work?

A product recommender seamlessly adapts the shopping experience for each customer and provides user-relevant product suggestions.

All product recommendations are based on supervised machine learning models that learn from your product data and past user interactions (clicks, previous searches, search trends, etc.)

The product recommendation system ensures your e-commerce search engine always meets changing users' demands and tastes.

Customer is choosing products

Personalized product recommendations

77% of online shoppers tend to choose, recommend, and pay more for the brands that personalize their shopping experience.

The cutting-edge AI technology gets into the core of users’ search terms, adapts the search results based on unique user contexts, and delivers a highly accurate search experience that boosts sales.

Expect a higher conversion rate, an increase in average order value, and more satisfied customers frequently returning to your e-shop.

Product discovery

AI-driven product recommender shows recommendations to your users based on their recent searches and preferences and encourages them to discover hyper-relevant products.

Show top trending products, upsell similar products to the ones the user has recently searched for, or manually pick a few items every shopper will love.

A proactive product recommender encourages spontaneous user decisions and promotes a higher number of last-minute purchases.

AI driven search displays results

Customize recommendations

Tailor a unique shopping experience so it is relevant to your customers and meets your e-commerce strategy goals.

After every customer order, the search engine collects the product conversion Events. You can use these events in a product recommender based on multiple sources:

  • product similarities (based on categories and other attributes)
  • session data (product click, add to cart)
  • user data (product click, add to cart) - it is similar to the session but more persistent
  • cart/order item combinations (furniture, decor, lighting, interior details)

Mix and match different source combinations in your recommender to create an unforgettable search experience.

Similar productsTrending productsFrequently bought togetherCustomers also viewed
Pick recommendations based on product similaritiesShow what’s currently trending among all shoppersUpsell product combinations and increase AOVBlend personal relevance with current search trends

You are never on your own

As difficult as it may sound, the LupaSearch team is here to assist you in creating a highly converting product recommender experience for your shoppers.

The LupaSearch team offers continuous support and shares some tried and tested strategies on how to get the most out of an AI-driven product recommendation system.

You will soon acquire all the know-how you need to manage the product recommendations ideally suited to your business needs.

Want to learn more?

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Ready to see LupaSearch in action?

Request your e-shop search audit - it’s free! The LupaSearch team will analyze your website search and provide guidelines to skyrocket your brand’s sales.

Already convinced? Contact us to get a demo.

Dashboard with personalization preferences