The unexpected or apparently random discovery of a new product, according to recent research, can have a major and positive impact on the customer experience. When customers unexpectedly discover something new that they like, their enjoyment and satisfaction of a particular product or service will be greatly enhanced.
Recent research by the University of Sydney, University of Florida and Rutgers University demonstrated how important the random discovery of new products can to the overall customer experience. When serendipity is introduced into the experience of discovering new products the positive feelings associated with it are greatly magnified.
The research looked at a range of different industries and types of organisations including online subscription services, museums, movies, food consumption and music. It was found that creating serendipity through positive, unexpected, chance encounters increased satisfaction, enjoyment, perception of meaningfulness, willingness to pay, willingness to recommend a service, and interest.
As an example, the research highlights how Netflix introduced a shuffle feature last year to help viewers discover something new and unexpected. The feature appears counter intuitive to the principles of Customer Experience, by eliminating a customer’s ability to search and choose what they want to watch. But too much choice, where a customer spends ages trying to find something they want to watch, can lead to weariness and disengagement.
Consumers of streaming services, such as Netflix, are less impressed by a large selection of movies or songs than they are by a platform that randomly suggests a movie or song that is to their taste. Being pleasantly surprised can play a major role in customer satisfaction,
The concept of serendipity was introduced into behavioural science by American sociologist Robert Merton, referring to the situation of accidentally making a new and unexpected discovery while in search of something else. Discovering something positive that suites our tastes, accidentally, has the potential to be far more satisfying than making a decision or choice on our own.
Steven van Belleghem who was quoted in a recent article in Forbes Magazine, explains, “I think we’re now seeing brands creating what I call ‘artificial serendipity.’ It is driving the success of many subscription boxes, for example, as customers find joy in being introduced to unfamiliar brands. Even Netflix have introduced a shuffle button that eliminates choice and instead plays a randomly selected show to help users discover something unexpected. I believe that brands that understand how to stimulate serendipity have an opportunity to set themselves apart in 2022.”
Recommendation engines have been standard on ecommerce websites for some time now, where customers receive product recommendations based on prior purchasing decisions. Recommendation engines are essentially data collation and filtering tools that use algorithms to analyse historical data. Think of then as automated shop assistants, where, as well as showing the product the customer is enquiring about, they also recommend products that may be relevant to a particular user.
Recommendation engines assist customers to sort through the vast amount of product information that is available online by presenting users with snippets of information and content based on their preferences and tastes. As well as presenting items based on what a customer has previously bought, recommendation engines or algorithms will also present the most popular choices or purchases on a site and the items which have received the highest ratings or reviews.
As well as creating a more engaging customer experience these algorithms can create additional revenue by up selling and cross selling products. However, users can become bored with the suggestions provided. They may already be very familiar with the most popular items and will often lose interest when offered items very similar to the ones they’ve already purchased.
To improve user satisfaction, recommendation engines should look at offering serendipitous suggestions: items not only relevant and novel to the target user, but also significantly different from the items that the user has rated or previously bought. This requires broadening the parameters and the diversity of potential products being recommended.
Offering too much diversity though, can impact accuracy and end up presenting items that are completely irrelevant.
