Alice sits at her laptop computer to visit her favorite online apparel shop. After a couple of clicks, she is browsing the store’s goods looking for things that may interest her. She specifically want to buy a belt but only if the price is right.
After a while, she has concluded her search and has added a belt to her shopping basket. She browses a bit more and finally she decides that, before concluding the purchase, she should look around in other stores as well. This belt she has found is exactly what she has been looking for but its price is not quite right for her.
She leaves the store and visits other websites with similar content. While doing so, a sound comes from her mobile phone telling her that she has a new email message. She instinctively checks her mailbox to find out that she has a message from her favorite online clothing store who, having seen her unfinished basket, make her an offer with a personal discount coupon of 12%. This, by coincidence, is the price she had in mind for the belt she reluctantly left behind so she goes back, enters the coupon code and finalizes the transaction.
Behind the scenes: Our algorithms have calculated the reservation price that the specific user has in mind for the specific item. All the retailer has to do, is to communicate this price to the customer. In other words, the retailer can avoid across the board price reductions and make targeted offers just where it is really needed to conclude a sale.