The Shopimate™ recommendation engine actively gathers and analyzes data based on a user’s purchasing history. The shopper doesn’t even have to log in for this to take place. The data is then accumulated into a transaction history, which is analyzed to find patterns. They can include favorite products, regular purchases, product categories which are browsed before purchasing and so on. These recommendations can also be fully customized based on locations, product availability, attributes and more.
Based on these, the customer is then presented with products he is most likely to buy alongside his already ordered or searched for items. Regular customers can get instant access to their regular shopping list without having to find every product again, making them more loyal.
What sets the Shopimate™ recommendation engine apart from the competition is real time. Each new pattern is added automatically and used instantly. Even the slightest change in habits from a regular customer is noticed, catalogued and his recommendations adjust accordingly.
Even without specific recommendations, sales can be increased by focusing on bestsellers. Shopimate™ can create and update such a list automatically. This directs additional traffic to products which are in stock and generate the most profit, increasing their popularity even more.