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BENEFITS OF A PRODUCT RECOMMENDATION ENGINE

techalicehunt profile image techalicehunt ・2 min read

You do not need market research to find out whether a customer is willing to purchase at a shop where they’re getting maximum help in scouting the right product. They’re also much more likely to return to such a shop in the future. To get an idea about the business value of recommender systems: A few months ago, Netflix estimated, that its recommendation engine is worth a yearly $1billion.

There are 2 major benefits of using a product recommendation engine - revenue and customer satisfaction. Here we know more about those 2 and some more:

Revenue – With years of research, experiments and execution primarily driven by Amazon, not only is there less of a learning curve for online customers today. Many different algorithms have also been explored, executed, and proven to drive high conversion rate vs. non-personalized product recommendations.

Customer Satisfaction – Many a time customers tend to look at their product recommendation from their last browsing. Mainly because they think they will find better opportunities for good products. When they leave the site and come back later; it would help if their browsing data from the previous session was available. This could further help and guide their e-Commerce activities, similar to experienced assistants at Brick and Mortar stores. This type of customer satisfaction leads to customer retention.

Personalization – We often take recommendations from friends and family because we trust their opinion. They know what we like better than anyone else. This is the sole reason they are good at recommending things and is what recommendation systems try to model. You can use the data accumulated indirectly to improve your website’s overall services and ensure that they are suitable according to a user’s preferences. In return, the user will be placed in a better mood to purchase your products or services.

Discovery – For example, the “Genius Recommendations” feature of iTunes, “Frequently Bought Together” of Amazon.com makes surprising recommendations which are similar to what we already like. People generally like to be suggested things which they would like, and when they use a site which can relate to his/her choices extremely perfectly then he/she is bound to visit that site again.

Provide Reports – Is an integral part of a personalization system. Giving the client accurate and up to the minute reporting allows him to make solid decisions about his site and the direction of a campaign. Based on these reports clients can generate offers for slow moving products in order to create a drive in sales.

Read full article here Recommendation Engine Benefits

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