Giving customers what they want is an essential factor for success in business, but knowing what they want is not an easy problem to solve. Customers do not always want the same thing; they may not even have a clear idea of what they want. With current business to customer (B2C) mass customization tools and technology, high levels of customization are possible, however, as psychologist Barry Schwartz has pointed out, too much choice can be overwhelming. Schwartz calls this phenomenon the paradox of choice.
Researchers Michal Piasecki and Sean Hanna don't think that providing choice to customers is always a bad thing, but they do believe that the choices provided must be meaningful to the consumer. They redefine the paradox of choice such that the negative effects of choice (dissatisfaction, unhappiness and even paralysis) come from the lack of meaningful choice, not simply the total amount of choice. Instead of limiting the choices presented to a consumer, they believe businesses should provide choices which are relevant to that particular consumer.
Providing relevant choices isn't an easy task, however Piasecki and Hanna believe that tools based on genetic algorithms could be a good solution. Genetic algorithms, a set of artificial intelligence methods inspired by natural evolution, use a browsing customer's actions to learn to generate increasingly better solutions. By learning what is important from the customer, this configuration software can avoid overwhelming the customer with irrelevant details. In tests, Piasecki and Hanna found that the genetic algorithm-based tools were more popular than typical parametric product configurators. By automatically recognizing the options which are meaningful to a buyer, genetic algorithms could make browsing a more pleasant experience for everyone.