5-Step UX Guide to Personal Experiences
Want to use personalization but don’t know where to start? Start here. This 5-step guide should give you some inspiration on how to get going.
1) What do you want to personalize?
Identify the content that you can personalize (and the ways you can personalize them).
2) How will you collect the data?
Make sure you don’t force your users into giving you private data.
3) How do you User Test?
It’s actually really difficult and time-consuming to user test personalization.
4) How do you (as a UX’er) Design the Algorithm?
Don’t leave it to the developers, you can easily join the conversation when you know how.
5) How do you measure if its a success?
Depends what you want. But use these guidelines as a bare minimum.
1) What do you Want to Personalize?
You can make this as generic or interesting as you want. If for example, you are building a streaming platform you could personalize the “recommendations” part of the site (generic, but none the less a must). You could also do something more experimental though, like personalizing the interface.
There are lots of ways to do this, remember though, personalization ≠ customization. It is not allowing your user to pick the color of the menu (a.k.a. user-driven). It is about translating whatever data you have about them into meaningful optimizations (a.k.a. system-driven). If you were to design a streaming platform for teenagers, it would look and perform significantly different from a platform designed for elderly users. Today all sites look pretty much the same to all of its users, and there are still lots of space to innovate in this area so if you have the budget (bots come to mind), try to come up wth unique ways to use personalization in your business.
It is important that your own data, the metadata on whatever you want to personalize is streamlined, and includes all the relevant parameters. If you own a video-streaming service, you want to access as much data as possible on each video. Actors, genres, themes, locations, moods, anything really, that can be tied to a user’s preferences.
If your own metadata isn’t “deep” enough and you only have access to a limited amount of parameters, you may never uncover the patterns of why users like and interact with the content that they do, and thus their experience will be sub-optimal.
2) How Will you Collect the Data?
This all sounds really interesting you say, but how can I know all this about a newly created user? You can’t. Plain and simple. This is what’s known as a cold start. You can fix this in two ways. Either you have them log in with an account from another site that contains an extensive amount of data on them, that they are willing to let you use, or you will have to use an introductory flow where your users fill in a form about themselves. None of those are optimal, as both of them can feel rather intrusive. Furthermore, users don’t trust you from day one. They won’t give you access to their private data before you have proven that you can give them something valuable in return. Your best option is to adjust their experience over time, as you learn more about their habits and behavior.
I would recommend that you provide users with the option to link with their other accounts in the settings (as an opt-in, not as a requirement!). This will give you access to a ton of data, that the user has then actively agreed to give you. Be careful though, mixing different sources of data can be tricky. You are not the same user on Google, as you are on Facebook or Youtube. What you watch on Youtube usually differ from who you follow on Facebook, and that usually differs from what you search for on Google. Needless to say, you will most of the time not need more than one or two sources to start building your own profile on the user, so think wisely about what integrations that can give you the data you need to improve your users’ experience.
3) How Do you User Test? (This part can be a pain!)
Imagine you would like to examine how precise your users prefer their recommendations to be.
You would have to know their actual preferences beforehand and optimize the wireframes and mockups to each individual user test (very time consuming).
Mock data (Not Recommended)
If you just use mock-data, it would not make any sense, because you have no way of knowing which elements that feel more precise to the users (if you make two versions. One with generic content, and one with personalized content, how would you distinguish the content in those, when you don’t know what each user prefers?).
Personas (Not Recommended)
You could also give them personas: “You are now Bob, who has these interests, and loves to do this and this”. Then you would present them with a few screens, with one obviously catering more to Bob’s interests than the others. The user will point to the screen that is most in line with Bob’s preferences. So far, so good, but what value would that give you? Of course, they will choose the one that is catered the most to Bob, because they can’t know what level of precision Bob wants. And even if you told them that, you would still just confirm your own bias. Personas are unfortunately a dead-end when working with personalization.
The Time Consuming Way
Long story short, there are no shortcuts. I would recommend finding a few users that you learn about and continuously test on. Send out a survey beforehand to learn about the users (ask about anything that will be relevant for the personal experience). Then make the content in the wireframes and mockups match each individual user’s actual interests and preferences. This is, unfortunately, the most reliable way to research personalization without having an actual algorithm to test on. If you are fortunate enough to actually have a working algorithm that you can experiment with, then by all means, save yourself the trouble and use that one for the user tests.
4) How can you Design Algorithms as a non-Coder?
Personalization algorithms can be very unwelcoming to visual designers, but it is important that we have a way for designers to alter the functionality, as this is a huge part of the user experience. A way to make it more down to earth is to introduce a point system.
In the example of Netflix, it could be that hitting the like translates to +3 points in the algorithm. Every episode viewed is +1 point. This is the difference between explicit data (a user hit the like button) and implicit data (we can track that the user watches this show a lot). It makes a lot of sense to discuss how you value different inputs. What if I watch only half of the episode, does that still award 1 point or only a half? What if I just watch a few minutes, does that mean I didn’t like it, and therefore it should have a negative value in the algorithm? And how many points do we award the different metadata? The series itself, 3 points, the genre, 2 points, the actor 1 point? What if a user likes everything he watches, should that devaluate the points given? and if another user only hits like on one single show, does that mean it’s the user’s absolute favorite and should be awarded 20 points? You can keep tweaking these numbers and carry out user studies till you reach an experience that resonates with the users.
Note: Remember to Pin Holes in the Filter Bubbles
There are a lot of pitfalls that you have to be aware of when working with personalization. The most common one is trapping the user in a filter bubble. Remember, users are people, and no one is the same throughout life, we change constantly. What your users preferred a year ago, might not be the same that they prefer now. This goes for both content, interface, and any other type of personalization you can think of. This is where you have a responsibility as a designer. Make sure that you allow your users to change over time, and to challenge their status quo. Make sure to peak your users’ interest from time to time, with something that is different from what they are used to. This way your site or product will stay fresh and interesting over time. When your user feels that the site or product grows together with them, that’s when you have succeeded.
5) Can you Measure if the Experience is a Success?
Personalization is a service, which means that it is an intangible, complex, non-visible part of your product, hence, it can be rather difficult to measure. It really depends on what you want to achieve, as personalization can be a very flexible tool.
Netflix for example, have a 60-second rule. If the user can’t find something that they want to watch within 60 seconds, their personalization has failed. This wouldn’t make sense to apply on Youtube though, as 60 seconds on the Youtube front page is an eternity, and something along the lines of 10 seconds would probably be a better success criteria. My point is, you will have to devise your own criteria, instead of basing it on what other sites use. That being said, there are three overall criteria that your personalization in most cases should improve upon:
Efficiency: Can the user find relevant content faster than without?
This could be a matter of measuring the seconds a user spends before finding a product to buy, an artist to listen to, an article to read or whatever your service offers.
Precision: Are the recommendations actually relevant to the user?
Measure the CTR of the recommendations compared to how the users interact with the generic content.
Satisfaction: Are the users happier with the personal experience than before?Surveys, interviews, and other traditional methods of getting feedback will make sense to measure this. If you want to quantify it, you should use a survey with scales (1–10 or similar).
Personalization is the future of most services, but there is no such thing as just adding “personalization”. It is extremely adaptable, and you should spend some time to tweak your service’s personalization to make it uniquely fit your business and your users if you want to stand out from the rest.
Having designers work in collaboration with develops on tweaking the experience can result in outstanding performance and user satisfaction, in the long run, so make sure you come up with a thorough strategy before you implement it and take your time to know not just why you want to use it, but also how. Rome wasn’t built in a day, nor should your personalization effort be.