Personalization Has Permanently Changed UX
The concepts behind a good user experience haven’t changed. Your software needs to be responsible, usable and easily accessible. What has changed? Just… everything else. Competition in software is increasingly competitive, with startups and other companies continuously fighting to expand. Users live in an era of self-importance; when it comes to evaluating an app, they value their own experiences over anything else.
Enter machine learning, big data and cloud computing. Companies are using vast amounts of data to compete in marketing, UX and product design.
81% of consumers want brands to get to know them, and understand when to approach them.
The Recommendation Engine
Personalization isn’t just helpful for UX, it directly impacts your ability to sell product or services. Showing the right products to the right consumers increases purchase rates by almost 50%. Recommendation engines use large amounts of customer data to make correlations between products. They are further personalized with individual user data.
49% of the consumer sample said they bought an item they weren’t planning on upon receiving a personalized recommendation.
The products themselves aren’t the only things changing. Amazon, Facebook, Instagram, Twitter, LinkedIn, Uber, Lyft, Nordstrom, Sephora. Any of those sound familiar? Each one of them is using predictive analytics to individual run personalized experiences to users. Spotify runs several to several hundred variants of their app at one time.
Curated home pages keep users engaged in a way that traditional home pages cannot. Everything is specifically targeted towards the user. When you have eight seconds to grab someone’s attention, you have to focus your efforts on what matters to them.
People lose concentration after eight seconds.
The Future is Extreme
Extreme personalization is the next natural step in personalization. Extreme personalization is able to leverage massive amounts of data and machine learning to make very uniquely curated experiences.
Netflix curates your movie and show recommendations based on their machine learning algorithms. When you log in, everything you see is based on your interests and previous viewing history. Humans make decisions mainly on visual stimuli, so Netflix has title card images for every recommendation — just like Hulu or Amazon. Initially, they had one title card that they used per suggestion, but recommendations aren’t necessarily always because of one aspect. You might like an actor, the genre or specific characters. Netflix realized this and now uses machine learning not only for recommendations but for title cards.back to blog