I visited their website, picked the phone and contract I wanted, and clicked ‘Add to basket’.

The next view showed me my basket.

But look: a little line saying ‘Mobile phone ... Read more]]> I’ve just encountered a stinky example of the Sneak into Basket dark pattern, courtesy of buymobilephones.net.

I visited their website, picked the phone and contract I wanted, and clicked ‘Add to basket’.

The next view showed me my basket.

But look: a little line saying ‘Mobile phone insurance with 1st month free’ has been automagically added to my order.

I didn’t spot that the insurance had been added. Why not?

First, my eye was drawn to the same picture of the HTC One S that I’d seen on the original page. Next to it appeared a summary of the contract details as a big blue link.

The insurance details appeared in the same plain black text as the supplementary information about my contract – I didn’t bother to read that far.

I scanned the amounts in the right-hand column; they included £0.00 for my contract plus delivery costs. Nothing about insurance.

The big green ‘£0.00′ final total, too, suggested that I hadn’t accidentally added anything else to my basket.

My eye skipped over the light grey paragraph below the green total; it looked like standard, dull terms and conditions info.

The final thing that caught my eye was the big, fat ‘Continue’ button, which I happily clicked.

The next screen was for payment and delivery details.

There was no further mention of insurance until I’d confirmed the order, by which time there was no option to cancel.

So: a combination of leading my eye to the pieces of information that I expected to see, and exploiting my preconception that light grey text is unimportant, led me to inadvertently buy insurance I didn’t want.

I should have read everything more carefully before confirming my order. But even so – sneaky!

At UX Brighton last night, Judy Rees introduced a very simple little technique for getting richer findings from user interviews. If you don’t already use it, it’s a potentially useful addition to the user research toolkit.

Judy calls the technique “parrot phrasing”, and it works like this.

Say you’re interviewing a user about ... Read more]]>

At UX Brighton last night, Judy Rees introduced a very simple little technique for getting richer findings from user interviews. If you don’t already use it, it’s a potentially useful addition to the user research toolkit.

Judy calls the technique “parrot phrasing”, and it works like this.

Say you’re interviewing a user about their opinions on a particular topic. When they mention something you’d like to explore further, repeat back the last few words they said exactly as they said them, without paraphrasing. It might be appropriate to use a curious, inquiring tone of voice, depending on the context.

That’s it. The effect is that the interviewee is unobtrusively prompted to elaborate on things they’ve said.

"...it should just work like Amazon?"

For example:

Interviewee: “…it’s quite difficult to keep up with everything, and I tend to find that I only shop for food once a week, what with all the usual evening stuff going on…”

Interviewer: “The usual evening stuff?”

Interviewee: “Yeah, giving the kids their dinner, cleaning up…it’s easier on Fridays because we’re both home from work early.”

Judy split us into pairs and we spent five minutes trying out the technique on each other. The consequences were interesting. As an interviewee, having my own words echoed back to me felt like part of a natural conversation, far more so than had the researcher used their own phrasing for questions.

It meant I was less conscious of being in an interview situation; I felt more in control, leading me to talk more freely and perhaps be less likely to say things that I thought the interviewer might be looking for.

Having my own words echoed back also gave me a subtle sense that the researcher was paying attention and respecting what I was saying. Again, this made me more likely to speak freely.

If you’re not convinced, go and try it out on someone now.

Parrot image by DigitalART2

But a physical on-screen button tap has a distinct advantage ... Read more]]> A new Wired article looks at Nokia research into expanding the uses of accelerometers in phones. You could make an ‘F’ gesture in the air with your phone, for example, to launch its FM radio. You might use another gesture to lock your phone.

But a physical on-screen button tap has a distinct advantage over a mid-air gesture: perceived reliability.

When I physically tap an on-screen control, the outcome is 100% predictable. I push the button, I get the intended result. But with a gesture, it feels like there’s a greater risk of my phone misinterpreting what I want.

So when I’m choosing my interaction method, there’s a cost-benefit tradeoff. Why should I risk wasting valuable seconds while my phone misinterprets my gesture, when I know I can push a button that will work every time?

Obviously, the more reliable the gestural interface, the more confidence I’ll have in it. But it can never trump a 100% reliable button. What’s more, to make the appropriate gesture for what I want to do, I need to recall it from memory first.

That’s not to suggest that gestural interfaces aren’t a good thing; just that the context of use is important. You could allow gestural commands in your design – but in what circumstances will they save users sufficient time and/or effort that they’d choose making a gesture over pushing a button?

Designing voice control interfaces raises the same questions.

(Just to be clear: I think gestural interfaces are very cool. Can’t wait to have a go on Kinect…)

I had butterflies in ... Read more]]> I’ve finished all my MSc coursework for the first two terms, with a running average of 74%, so I’m on course for a Distinction so far. The future remains littered with bananaskins, though: my final project will count for around a third of my overall grade. Plenty still to do.

I had butterflies in my stomach whilst travelling up to the 8th floor to check my grades on the board outside the Prof’s office. Haven’t had that feeling for a while!

A while later I was still tweaking Obsidian curves to create a little tie for one of ... Read more]]> I needed some very simple, cartoony figures to represent different user groups on a diagram I was drawing in Omnigraffle, and couldn’t find anything free and suitable online. So I started using Omnigraffle to make my own.

A while later I was still tweaking Obsidian curves to create a little tie for one of my figures, and realised I could have done the whole job with a pencil and paper in a tenth of the time.

I was quite pleased with them though, even though Bill Buxton would disapprove. Feel free to download and use the Omnigraffle stencil if you like.

Say I’m playing a game where every so often, I can pick up guns from the floor. I always pick up uzis, because I have a particular penchant for cutting zombies in half with ... Read more]]> Do video games learn what a gamer likes as they play, then tailor the rest of the game experience accordingly?

Say I’m playing a game where every so often, I can pick up guns from the floor. I always pick up uzis, because I have a particular penchant for cutting zombies in half with a spray of automatic fire. But I ignore other guns. Are there ways that the game could notice my fetish for particular weaponry and provide a liberal scattering of uzis next time I play?

I don’t know whether this kind of personalisation is standard practice yet; if anyone knows more about it I’d be interested to hear. Anecdotally, a friend that makes driving games told me that some games do use dynamic difficulty balancing. If you’re being useless at Mario Kart, for example, a rocket will shoot up your arse and boost you towards the cars ahead. If you’re doing really well in some games, you might suddenly get more obstacles thrown your way.

This throws up some interesting questions about fairness and satisfaction. If I’m beating someone at Mario Kart because I’ve invested hours mastering it, why should they be given a leg up? As a beginner, do I really want a leg up? It must be difficult for game designers to get right.

Of course, difficulty is just one way of personalising a game experience. Giving the uzi fan more of what they appear to like is another. I’m repeatedly in awe of the complexities involved in game design and would encourage any interaction designer to read about it.

Lots of us are wary of the prospect of companies like Google tracking our every ... Read more]]> Imagine if you had access to a record of everything you’ve done online in the last five years – down to keystroke level, even – and could analyse it to see what it reveals about you as a person.

Lots of us are wary of the prospect of companies like Google tracking our every move online; building up a thorough profile of our behaviours and preferences that can be sold to advertisers. But what if that growing profile could be used to try to help us become more self aware and to make better life decisions?

Potentially helpful recommendations based on our personal preferences and behaviours are now everywhere online (see Amazon, last.fm, Meetup, etc etc). But these services are all relatively closed, or only address a specific dimension of my ‘lifestream’; say, music. They aren’t able to help me interpret comprehensive data about my behaviours and preferences from the entire breadth of my internet use.

Hunch.com asks you an open-ended series of trivial questions about your personal preferences (try it – it’s addictive) then uses the impression it builds of you to provide advice to life questions  you have. But Hunch’s profile of me is limited to conclusions drawn from the self-conscious, considered answers I give to its formal set of questions – fun and extensive as those questions are.

Imagine instead if I were to let a service track everything I did online, tracking my unconscious behaviours as well as my conscious actions (let’s put aside the huge question of privacy and ownership for now). Then I could use that service to interpret the data it had collected to help me to make life decisions. Not just about how to spend my money, or what music to listen to, but what kinds of goals I might want to set for the coming year. What kind of career might suit me best; in what places and with whom I seem to have been happiest; whether I’m ready to have a baby. (Disclaimer – these are just random examples!)

This is just a big fuzzy concept that I’m trying to get my head around. Is my online footprint a reliable basis for making big life decisions? Almost certainly not. But it’d be an interesting way to get some potentially useful insights into myself as a person, my instincts and preferences, based on years of real data about my actions.

The push towards open linked data – making it easier to link, categorise and find online data – will bring these questions to the fore. On the one hand, there will be an explosion of innovation, crunching the new rich variety of data to provide useful insights about individuals, issues and organisations. On the other hand, of course, there will be plenty of tough questions around privacy.

It’s got tons of fascinating insights – drawn from OKCupid’s usage data – about people’s social behaviour, identity and dating preferences. Plus a few predictable findings, naturally.

It blows my mind to think of ... Read more]]> I just discovered the blog of OKCupid, a dating site (via @billwscott if you must know – research purposes only!)

It’s got tons of fascinating insights – drawn from OKCupid’s usage data – about people’s social behaviour, identity and dating preferences. Plus a few predictable findings, naturally.

It blows my mind to think of the implications these kinds of datasets could have for social science research. Imagine what researchers could do with, say, Facebook usage datasets if made publically available.