A lot of times, people don’t know what they want until you show it to them.
Steve Jobs, founder and long-time CEO of Apple
35% of Amazon.com revenue is generated by its recommendation engine
15% of web shop visitors admit to buying recommended products
11% is the worldwide average e-commerce revenue generated from product recommendations
Will a particular user like a particular product? Who should the product be recommended to?
The answer to the questions is a product recommender system.
Traditionally, a recommender system would look at
- the products that a particular customer has purchased before and recommends the same products again, or
- the products belonging to the same category and recommends them without much consideration
A modern recommender system is powered by artificial intelligence. Instead of generic customer segments, an AI-powered recommender system creates a unique profile for each customer taking into account the customer’s interests, activity history, and other personal and demographic characteristics. Personal profiles are used to generate unique recommendations by matching product profiles with customer profiles.
Often recommender systems, both traditional and AI-powered, do not keep up with the changes in customer interests and over time start to recommend less and less relevant products. Also, out of the box systems are difficult to customize and adjust to specific needs.
The solution is theklen.ai AI-powered recommender system that is
- based on the state-of-the-art AI algorithms
- continuously learning and refining customer profiles without the need to take the system offline
- Increase average order value
- Transfer shoppers to clients
- Boost number of items per order
- Provide relevant material
- Engage customers
- Drive traffic
- Grow User satisfaction
- Provide reports
Personalized recommendations powered by the theklen.ai recommender system can increase revenue up to 20-30%.