Websites of all types should consider these before discounting the use of a recommender engine.
The future of the web is helping people shop and experience sites in a uniquely personal way for them; whether the website is e-commerce, media, social network, or search engine, this is a win-win situation for both the users and the site owners (or store owners, in the case of e-commerce).
One way to do this? Utilising a recommender engine. A recommendation engine, also known as a recommender system, is software that analyses available data (user behaviours, product properties, etc) to make suggestions for something that a website user might be interested in, such as a book, a video or a job, among other possibilities.
Amazon was one of the first sites to use a recommendation system.
Recommended product from Amazon website.
Maybe change Search is hard for users, discovery/exploration is easy to Search limits the users to what they already know while discovery/exploration offers more and is easier and more convenient for users to make choices.
Increased sales
Using personalised recommendations are proven to increase sales. Amazon, for example, reports that 20-30 per cent of sales come from personalised recommendations. Same as with these other examples:
- Netflix: 2/3 of the movies watched are recommended.
- Google News: recommendations generate 38% more clickthrough.
- Amazon: 35% sales from recommendations.
- Choicestream: 28% of the people would buy more music if they found what they liked.
Better user experience.
Show users personalised and more relevant products while their on the site and off (via email). Also give users tools/games to discover more of what they like. Search is hard for users, discovery/exploration is easy.
Increased traffic/page views.
Increased traffic/page views.
By giving users more discovery tools you will receive more traffic and higher product discovery potentials.
Improve customer retention.
Also means higher lifetime customer value. The more users like your site, the more the buy, the higher they are likely to return. Also use targetted and personalised email campaigns to bring them back and keep making them happy.
Recommendation engines are increasingly becoming popular and for good reasons, too. Have you used a recommendation engine? What other benefits have you experienced?
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