AI to derive more value from existing customers
eCommerce is constantly looking for ways to cross-sell and up-sell effectively; this is where an AI-based recommender system can help.
AI can be used to identify products/services that your customer will most likely buy if offered to them.
By placing this, businesses can bundle sales products together, deliver complementary and alternative product recommendations.
To increase sales we need to improve our customer base, but the
Customer acquisition cost (CAC) can be pretty high for eCommerce, especially. The cheapest way to increase our sales numbers would be to get our existing customers to buy more. This is where AI-Recommendation systems come to play.
Online shoppers want variety, convenience and personalization,, and a lot more!
AI’sAI’s recommender system can motivate purchasing and boost up the conversion rate for a website.
The personalized recommendations drive customers to upgrade their purchases by giving high-precision product recommendations
AI’s Recommender systems use different relationships to come up with recommendations.
The “user-product relationship” happens when users have an affinity or preference towards specific products that they need, “Product-product relationships” occur when products are alike, and the “user-user relationships” happen when some customers hold similar tastes concerning a particular product or service.
AI-based recommender engine can analyze the individual purchase behavior and detect patterns that will help provide a particular user with suggestions of products that will most likely match their interests.
Examples of data inputted in the AI system may include star ratings, reviews, feedback, likes, and following. clicks, views, purchases and user-ratings, etc
There are plenty of ways e-commerce can utilize the recommender system to drive sales.
One of the various ways the Recommendation system can be used to cross-sell is by implementing “Related products recommendations” in the website by using AL algorithms like “Also add to the basket” or “You might also like” options in online stores.
Alternative products recommendation is another excellent way to keep your customer engaged even when the product they are looking for may be out of stock.
At times a particular product that the customer is looking for may currently be out of stock, and this shouldn’t become a cause for a customer to leave empty-handed. Providing alternative product recommendations can turn an annoyed customer into a happy one.