Personalisation is not overrated

I came across this very old article about personalisation of websites from 1998:

The article discusses the fad of website personalisation that was sweeping the web back in the late 90’s. Back then, many websites were making the first efforts to personalise the web by giving complex personalisation options to users, through which the website could decide which content to prioritise and so on. He goes on to say that personalisation in this form is pretty much overrated, as the majority of users consider filling out large questionnaire type option screens far too unwieldy and confusing. He does give two situations where personalisation can work, that are characterized by being:

  1. very simple to describe in machine-understandable ways, and
  2. relatively unchanging

To this list, I would add a third characteristic: silent.

Flash forward to 2010: personalisation is alive and well all over the web. The difference today is that there are no more long-winded options screens to tell the website who you are and what you like and don’t like. All that information and more is available on the web, for free. Your Facebook account holds more personal information about you than anywhere else, and it’s almost certainly more than you think. Add to that your web usage habits, what you click on, who your friends are, and what other people who are similar to you did, and there is more information than ever to offer you a fully personalised experience. From the ads that you see on Facebook to the books Amazon tells you to buy; nearly everything you see on the web is specifically targeted at YOU. But it’s silent… you don’t even realise it’s happening – and that’s the beautiful (and scary) part of it.

So what does this mean for experience designers? Well firstly, we should realise that this extends beyond the realm of advertising. We have access to so much of this information, and we can design user experiences that are unique, personal and delightful. (And we can do it without compromising user’s privacy).

I think there are five levels of data that we can look at about our user when designing their experience:

  1. Who you are.
  2. Things you do.
  3. Things your friends do.
  4. Things the crowd does.
  5. External factors.

Let’s look at some examples:

Who you are:

  • where you live
  • where you went to school/university
  • your interests/likes/dislikes
  • relationship status

Most of this is available publicly through your Facebook profile. If your product has it’s own profile service, then it can be aggregated with the information available from Facebook to create a very healthy set of data about who your user is.

What you do:
This is relevant to the specifics of your service. Let’s assume we’re looking at an online mapping application.

  • What you search for (search queries – places, categories) – collect all categories and rank the most searched for categories/regions
  • What you click on
  • Where you check in (category, region)
  • What features of the service do you use 
  • What you ‘like’, rate or review

What your friends do:

  • Again, relevant to the specifics of your service. 
  • Places your friends have been to (category, region)
  • Places your friends ‘like’, rate or review
  • Combine with your friend’s ‘personal’ data amalgamation (see above)

Things the crowd does:

You can learn a lot by watching the behaviour of the crowd. We’re talking generalisations, yes, but these can be refined based on your user’s profile to form quite valuable predictions of user’s future behaviour.

  • People in this area also tended to go to these other places… or of the people who checked into Subway, 40% also checked in to Starbucks, etc
  • People who looked at this place, also looked at these other places (Amazon style recommendations)

External factors:

  • Where you are (this is the most obvious and necessary one)
  • Time of day (prioritise lunch places midday, bars in the evening, etc)
  • Time of year Weather (if it’s raining, snowing, sunny, warm, cold, etc)

By watching carefully what individual users do as well as what the crowd does, and combining this information with your user’s profile information, you have a powerful platform for creating a personalised experience. How to turn this data into something meaningful would be the topic of another post… 

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