- Provides order combination insights and business intelligence on possible combinations of products and gadgets.
- Helps to sell more products to the same user.
- Prioritisation of most and recent combo-sales.
- Multi-level meta-tag integration to improve combination suggestions.
Shopping has been one of the necessary factors of every human being, and most the products which we buy will be the ones liked by us or the products brought by our friends. In the modern era, most of the online platform uses one or the other recommendation engine in order to provide a better option to their users and thereby increasing their revenue. Recommendation engines basically are data filtering tools that make use of algorithms and data to recommend the most relevant items to a particular user. Or in simple terms, they are nothing but an automated form of a “shop counter guy”.
Recommendation app will recommend many products from different categories based on what you are browsing and pull those products in front of you which you are likely to buy. Like the ‘frequently bought together’ option that comes at the bottom of the product page to lure you into buying the combo. This recommendation has one main goal: increase average order value i.e., to up-sell and cross-sell customers by providing product suggestions based on the items in their shopping cart or below products they’re currently looking at on-site.
Recommendation app will notify the users will the similar products that have been purchased buy the users from all the websites in which the app is installed. The data will be stored and pulled out to the users so that the users can purchase the combo products there by increasing the sales of the vendor. The combination will only be displayed if the vendor has similar products of as per the combination of the other vendors and also the best counted combination will be provided to the users.