Published on <a href="http://ift.tt/2pbqGPL">| Prototyping: From UX to Front End &mdash; Medium</a> Sean Hervo 
<h4>The new normal</h4>
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My earliest memory of personalisation in technology is from playing Ocarina of Time on the N64 as a kid. Upon starting a new game I was shocked to read “Wake up Sean”.
My name was being integrated in to the dialogue. While incredibly simple, it made the game feel like my adventure.
Today personalisation is present in pretty much everything online, from ads based on ‘that 90s boy band t-shirt you haphazardly clicked on last weekend’, to recommendations based on previously watched movies.
<h4>This time, it’s personal</h4>
By using data about a person’s online habits, you can offer services that look like they’ve been made exclusively for them.
Essentially, personalisation (controlled by the system) is tailoring content to more effectively meet a user’s needs, and providing experiences that feel more personal.
Spotify is one of the best examples of a service using this to great effect.
Using listening history, they can recommend songs and albums that fit in to the music you like best.
This works by finding users who have played the same songs and then recommending previously played songs that the other hasn’t listened to yet, a process known as collaborative filtering.
The songs themselves are also analysed, to find similar acoustic patterns.
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Their Discover Weekly feature gives you an entire personalised playlist each week — even including your profile image — to create an experience unique to you.
It’s become a massively popular feature. Within a year of launching, Spotify reported it had been tried out by 40 million users with a collective 5 million songs being played.
In fact it seems to have become something of a cult, with users posting on social media about the playlist each week.
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Netflix uses data science in a similar fashion to curate a list of TV shows &amp; movies you might like. Again the focus is on the individual user, a list of shows/films curated just for you.
There’s the ability to create multiple accounts for everyone in the household, so they are each getting their own personal content.
<h4>Forming habit</h4>
When personalisation is used correctly, it is both useful and addictive — users will keep coming back for more.
Again, I’m going to use Spotify Discover Weekly as an example.
It releases every Monday: This builds anticipation as users know exactly when the new playlist will be out, it also forms habit as they will be using it on the same day every week.
The selection of Monday as release day is also strategic. Monday is the day that most people go back to work after having the weekend off, they are eager for something to put them in a good mood.
The nature of music consumption means they can multitask while they listen on the commute or even during work itself.
It is simple: A solid example of KISS principle, users simply subscribe to the playlist once and then it’s a case of merely opening the app and hitting the play button each week.
Most importantly, it’s delivering music that users ❤️: Studies show that levels of dopamine in the brain were found to be up to <a href="http://ift.tt/1EUzpIe">9% higher when volunteers were listening to music they enjoyed</a>. Dopamine is the ‘feel good’ chemical and it is highly addictive.
<h4>Customisation</h4>
Roger Silverstone wrote about how technology can be ‘domesticated’. <a href="http://ift.tt/2cAqCpx">He introduced the idea of taming technology to fufill personal requirements</a>.
In other words, customising (controlled by user) it to be more personal.
Customisation allows the user to feel special and in command of the applications they are using, creating a sense of ownership.
For services like Pinterest and YouTube there is a level of user control on what content will be shown — you follow the topics you find most interesting and sign up to receive push notifications of your favourites, so you never miss new content.
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When logging in, only content the user cares about is shown, thus ensuring a happy, hassle-free experience on each visit. One that feels unique.
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ESPN allows selection of favourite teams or sports, to allow easy and quick access to the content that matters most to their users. Push notifications can be enabled to keep up to date with live games.
Conclusion
Personalisation is particularly prevalent in applications today and will likely continue to be used in new ways that make task fulfillment quicker and easier.
When used correctly, it can have a majorly positive impact on user experience — sometimes bordering on addiction — customers will keep coming back for more.
However, only consider implementing personalisation/customisation in to your design if it’s going to benefit the user.
The user comes first, but you will also have to assess the potential ROI before commiting.
Context is equally important, does it make sense for your existing content/business model? Is it part of a rebranding effort?
You’ll need prototyping/testing to ensure it is the right fit for your business before you invest time and money in to building, but as examples have shown — when you do it right, personalisation can work wonders for your product or service.
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<a href="http://ift.tt/2p8cJkU">Personalisation in Design</a> was originally published in <a href="http://ift.tt/2cAqCpx">Prototyping: From UX to Front End</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.

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