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These days, our tech has gotten pretty good at looking at our behavior — along with an increasing array of other factors — and adjusting to fit our lifestyles and preferences, or to keep us engaged.
Thanks to the rapidly evolving possibilities that come with big data, whether we’re talking music and fashion or movies and ads, it’s big business to ensure that what we see on our screens is relevant and ever-evolving.
So how do some of the new and popular apps and services fueled by this evolution work? The answer is often more interesting — and more human — than you might imagine. Below, we take a look at how a number of technical platforms adjust to optimize user experiences.
The personalized music radio service emerged from a dream: The Music Genome Project. Patrick Wells, a writer for Sound Called Music, tells Mashable the story: In 1999, music techies Tim Westergren and Nolan Gasser sought a way to sequence the “genetic material” of songs so that users could tap into a database of characteristics, thus connecting users with personalized music selections that the platform predicted they’d enjoy. As the number of songs, or “genes,” increased, Pandora went to work, looking at music along key vectors — think “acid rock” or “extensive vamping.”
Today, the platform makes selections that match your current sounds. Giving thumbs-up and thumbs-down feedback helps the system narrow its next picks along the lines of what you love the most.
Then there’s the next generation of how your tech will interact with you: With TREEbook, you buy a story from the company’s in-app selection and start reading. While you read, TREEbook’s algorithms consider your actions and your environment — from the time of year you open the book to the length of time you’re reading at each sitting.
Then, story “branches” take readers in different author-intended directions, according to their external and behavioral factors — this means the book in hand offers a unique experience for each user.
At the end, you can look at a map of how your branches unfolded, and you can go back and select a whole new read-through, or cherry-pick the branches you missed. TREEbook calls this an individualized experience, in that you’re not actively personalizing the story — rather it’s changing, behind the scenes, based on your individual circumstances.
One of the cool things about the personal-style service that Stitch Fix offers is that it couples algorithms with human deciders. That is, you actually get one-on-one considerations from a stylist on the company’s side of the equation. With your order — or fix, as the official lingo goes — you get a personalized note about each option. As you accept and decline different styles and pieces, both the stylist and the technology (mathematical algorithms) work together to send you more accurate selections based on your personal preferences and wardrobe needs.
According to a recent report on Mashable, only one-fifth of the service’s users show up with a concrete idea of what they want to watch online. The rest go by the site’s recommendation engine, which, following some seed-data provided by initial survey questions, pulls data based not only on what viewers previously watched, but also on their activity while watching. Its algorithms take into account what time you viewed your content, on what days of the week and so on. All of this data goes into picking just the right suggestions for “what to watch next,” advice heeded by most of the site’s users.
User intent, location and timing have become the connective material between our old ways of finding new things — browsing and shopping — and what is likely to be the future of individualized technologies, which may include recommendations delivered to us by brands.
Advertisers, of course, love this. With ad exchanges and real-time bidding, they can get their hands on anonymous consumer activity and then drop highly timely display ads into those users’ social feeds and other channels. But this isn’t such a bad thing for users — they’re more likely to receive relevant content and personalized advertisements for products and services in which they’re actually interested.
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Source: http://mashable.com/2014/06/02/personalized-tech-brandspeak/?utm_medium=feed&utm_source=rss
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