The e-commerce sector is growing fast and the product recommendation engine has become a popular tool for most of the leading e-commerce stores. When you search a specific product on Amazon, similar products keep popping up for you. That’s what a recommendation engine does, it recommends the most relevant products to each of your users without them doing anything. Survey says that over 40% of shoppers end up buying the products they didn’t plan to buy. And product recommendation acts as a catalyst to it.
Let’s have a look at some of the product recommendation tips for your e-commerce store-
- Incorporate in-depth User Behavioral Data
The secret to the precise product recommendation can often be found in the type of data a recommendation engine relies on. It is important that a recommendation system collects and analyzes all the data related to user browsing history, search, preferred style, brand, color, and others. For instance, if a user prefers red color more, then recommending the user black color dress may not be that effective. So, make sure your recommendation engine is capable of doing this job. Also, have some basic idea about what kind of filtering your recommendation engine is using.
- Recommend Lucrative Offers on the Home Page
Remember, your users don’t have a lot of time to browse through your pages and find out the available offers and discounts. Displaying the most attractive offers in the home page can quickly draw the user attention. For instance, You will find most of the recent discounts and offers on the homepage of the Indian e-commerce giant Myntra, such as- Up to 50% off on T-shirts, Beauty Deals, etc.
- Reviews and Ratings
The reviews and ratings of other customers can influence your users’ buying patterns significantly. It is obvious that a user will pick up a product with 20 ratings over a product with no rating at all. You can display the products with more ratings and reviews on your e-commerce store based on the user preference. For instance, the e-commerce store ebay has rating and review options for each of its products to let the users make better buying decisions.
- Recommend Badged Products
Research says that the products with noticeable badges such as ‘best seller’, ‘our choice’, and others make an instant impression for users. This in turn increases the chance of impulsive buying. The ‘Amazon’s Choice’, ‘Best seller’ etc. are some examples of such badges.
- Follow the Trends
The preferences and demand of the users are highly influenced by the recent trends. For instance, if smart watches are trending in the market, you can recommend the watches of the same category more frequently on your e-commerce store than other types of watches.
Muvi Recommendation Engine - Alie is AI-powered and easily integrable to your website or app. Alie uses advanced algorithms to understand your users and offer real-time recommendations. The scalability, adaptability across domains, and tailored recommendations are the additional benefits of Alie. Want to try it out? Take a 14-day free trial.
