Tagged: Human Biases RSS

  • Ben 11:09 on Sunday, August 29, 2010 Permalink | Reply
    Tags: , , Human Biases,   

    Old School Data Visualisation (Part 2) 

    A quick follow-up to the previous post on the power of data reduction and presentation… here is another example showing how rounding, ordering and thoughtful presentation can turn an incomprehensible grid of numbers into something most people can grok.

    It is from the same article (Ehrenberg, Feb 1992, The Problem of Numeracy, AdMap), but this time relates to television programme viewership.  The first table presents detailed correlations for responses to the question ‘I really like to watch programme x‘ across a range of programmes and two channels (ITV and BBC).

    Apart from an obvious diagonal line of 1.000 in the table (of course each programmes’ rating correlates perfectly with itself), there isn’t much else you can take out from it.  The next table renders the data a little more readable by introducing rounding to one decimal place, discarding the redundant leading zeros and disposing of the meaningless 1.000 diagonal.

    And with a little more thought to row order, spacing and the key data for presentation (i.e., do we really need channel?), we get to the following:

    Those familiar with television in the UK will now see that people who like to watch one sport programme also like to watch other sports programmes, particularly if they are ’round up’ type shows.  They don’t, however, like news or current events programmes so much.  A similar pattern occurs for current event watchers, but the programmes within that cluster have slightly lower correlations, meaning viewership is less likely to be homogeneous amongst that group.  If you are an advertiser or producer, this is useful stuff to know because it will give you an idea of the reach of, and competition around, a certain programme.  And you are more likely to understand this if the data is presented in a clear and concise way.

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  • Ben 16:30 on Sunday, August 15, 2010 Permalink | Reply
    Tags: , , , Human Biases   

    Old School Data Visualisation (Part 1) 

    I was talking to a friend last night about data presentation.  We were looking at an iPad ap that allows users to thumb through and drill-down into their sales data for different geographic regions.  Among other things, the ap displayed charts with smoothed trend-lines to help users get a feel for what the future might hold. Yet, in the relatively brief time I spent looking at the data it was hard to get any real sense of what the key take-outs might be.

    This will have been partly due to my lack of familiarity with the dataset; the person responsible for sales for the organisation would have  brought a wealth of historic knowledge to the data that may have enabled them to quickly see discrepancies or commonalities in the charts.  However, there was also an element of ‘too much’ information.  There is only so much we humans can hold in our short term memory before we become overwhelmed and our ability to do mental calculations or comparisons is compromised.  This is why it is critical for anyone presenting data to consider not only the level of detail required, but also how the information should be delivered for quick and clear consumption.

    Marketing scientist Andrew Ehrenberg spent a fair amount of time on these issues and was a strong advocate of data reduction (which relates to the idea that much success in research relies on the discovery of patterns in data, and that this process is aided by its presentation in simple tables).  In fact, Ehrenberg wrote a book on the subject that is freely downloadable from the EmpGens Journal.

    Here is an example of Ehrenberg’s approach.  I’ve reproduced the tables from a four page article of his in Admap from 1992 titled ‘The Problem of Numeracy‘.  First up is a table not optimised for human consumption.  Try to pick out some noteworthy patterns.

    Now try again, using a modified presentation of the same data:

    The rounding, averages and different row ordering (population size, rather than alphabet) all make it easier to quickly understand the data.  We can now see, for instance, that most regions saw a dip in Q3, that Leeds and Edinburgh have seen strong growth in Q4, and that Leeds is consistently punching above its weight in per capita sales.  We can also easily answer comparative questions like ‘how much larger was Edinburgh than Swansea over the year‘ (about 2.5x), which were much harder to do from the first table.

    People don’t often think of treating tables like other design elements in a user interface.  Yet as the example shows, they can fairly easily be tweaked to great effect.  And, when presented clearly, a table can convey more information in a short space of time than a series of charts.

     

  • Ben 19:32 on Sunday, July 11, 2010 Permalink | Reply
    Tags: Human Biases, Micropayments   

    Flattr: An Interesting Take on Micropayments 

    The flat-rate idea is what makes this new (in beta) micropayment service interesting – it enables people to give to content creators without having to worry about how much they are giving.

    The service needs to overcome the chicken-and-egg problem of not having the large user-base required for the service to be of most benefit.  It will also be competing with other nascent options like Facebook credits, which I imagine will soon expand beyond the confines of the Facebook platform, and Amazon’s Flexible Payments Service.

    However, if they manage to get beyond beta I’d love to see what the usage stats turn out like.

    • How many times would people give to the same content creators within a given period?
    • Would sites with high user repeat visit rates do better than those with low repeat rates but high traffic?
    • What phrases and presentations of the flattr button would generate the most gifts?

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  • Ben 10:23 on Saturday, April 24, 2010 Permalink | Reply
    Tags: Human Biases,   

    No More Shortcuts for You! 

    A quick follow-up to an earlier post on the attraction of shortcuts…

    I spotted some Wellington City Council contractors erecting a solution the other day:

    I guess putting up a barrier is much cheaper than paving the goat-track!  The day after I took this there was someone churning up the ground with a rotary hoe, so it’ll be back to a grassed area in no time.

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  • Ben 11:04 on Monday, April 5, 2010 Permalink | Reply
    Tags: Human Biases, , Perception, Wine Glasses   

    Does that Wine Glass Really Enhance your Wine? 

    My partner loves fancy wine glasses.  Unfortunately for her we don’t have much room at home, or have people over very often, so it is hard to justify buying different sets for different wines and occasions.  Of course, this doesn’t stop either of us from gazing upon the various options in whatever home store we happen upon.

    Were we to buy some nice glasses, I suspect we’d draw upon a number of excuses to rationalise our decision, the key two being:

    1. They look and feel really nice, and
    2. Experts say the right glasses enhance the flavour of the wine.

    I have no problem at all with the first excuse.  It’s the second one that sets off my bullshit meter, because ‘experts’ are often wrong and I’ve not actually seen any evidence that the assertion is true.

    To test whether wine glasses enhance the taste of a wine, you’d have to do some blind testing.  That is, the wine tasters would have to be blind to which glass they were quaffing or sniffing from when they gave their judgements.  Pretty much all of the tests I managed to find in my trawl of the web were unblinded (see here for a recent NZHerald ‘test’), so the participants may have been influenced by the look of the glass itself rather than any true structural effects of the vessel.

    I did manage to find one reference to research using blind tests, in a section of Wine Science from 2005 by Dr Ron Jackson:

    …shape does affect the intensity of the wine’s fragrance – those possessing a wide base and narrow neck enhance the perception of the wine’s aroma.  However, the differences detected from a variation of shapes on the wide–narrow theme were marginal.  Published evidence does not support the view that particular shapes uniquely enhance the character of specific wines.
    However, the reference also states…
    That particular shapes are not uniquely suited for tasting particular wines does not mean that they do not affect perception or, indeed, aesthetic pleasure.  Science has amply confirmed that visual and psychological influences often have a greater effect on what we perceive than the more subtle sensory data provided by taste and smell.
    That’s right, the effect of the wine glass shape is very real in a sense, but that sense is pretty much all in our heads.  If you take away the visual cues of the glass from the drinker, you also take away the differences in taste experienced. Knowing this is likely to have a couple of implications:
    1. You’ll be better prepared to argue with the next wine glass snob you encounter, and
    2. Different glasses are now likely to have less of an effect on your perception of wine taste.
    I guess another implication is that the glass that most enhances the flavour of a wine will vary from person to person; the more aesthetically pleasing the glass is for you, the more it is likely to enhance your experience of the wine you are drinking.  So don’t let people tell you what glasses you should use.  Use the ones you like best.
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  • Ben 16:28 on Saturday, February 20, 2010 Permalink | Reply
    Tags: Human Biases,   

    The Incredible Gravitational Pull of Shortcuts 

    It was a beautiful day in Wellington on Friday, so I took a stroll along the waterfront at lunchtime.  As I was returning to town I noticed something interesting between Cable St and Jervois Qy…

    I doubt the goat track is much shorter than the paved alternative, yet there must be some perceived directness about it for a good number of people.  Perhaps it was first formed by those running to catch a green pedestrian light, like the guys in the first shot.  Whatever the case the path now seems to have a life of its own.  Enough pedestrians have taken the dirt route just to get to the waiting point that the entire area next to it has been completely stripped of grass.

    Indeed, I must admit I found the dirt path choice quite compelling even though I wasn’t in a rush and could see the other pedestrian light was already orange.  It was probably the social proof of the well-worn track (“others seem to think it would be quicker, so it probably is”) along with the direct line-of-site to the other crossing that provided the appeal. And the fact that the path was already bare meant there would be no guilt in walking on the grass.

    What’s bizzare is that we’ll choose that route even though it doesn’t really save us any material time.  In fact, even if it did save time, in most cases it would mean we just get to a waiting point quicker!

    This ‘gravitational pull’ of shortcuts is frequently exploited.  Just look at the ads for 30-day weight-loss programs and get-rich quick schemes.  Even when there is little for us to gain we’ll take the short route so as to not miss out on just the potential for a mental, physical, or financial bargain.  It is unfortunate that the designers of this particular pedestrian crossing didn’t take it into account.  It might have made for a little less mud in winter.

    Still, it gave me something to write about!

    Here’s the area in Google Street View if you want to talk a stroll around it yourself…


    View Larger Map

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    • Scott 9:27 on Monday, March 1, 2010 Permalink

      People will generally do what is right for them at the immediate time. In this case, when crossing in the direction of the two guys in the bottom of your photo. The first crossing is aligned with the exit of the second as you mentioned. As such they continue walking to what they perceive is the correct crossing path for them. It’s not till they get under the cover that they realise that the crossing has been put at a different angle and the timings are not aligned as a single pedestrian crossing. As such, they deviate their path to ensure that the crossing buzzer has been activated. I think you’ll find the deviation is a road safety matter. Not sure it’s the social proof you think it is as it would be quicker had the intersection not been designed to make it not so. Surely it’s a social proof that council walking paths are always the slowest(safest)?

    • Ben 20:20 on Monday, March 1, 2010 Permalink

      Hey Scott.

      I guess we’d have to ask them if they were just looking for a quicker route or whether they actually thought the ped crossing continued over the grass. At least in the beginning (before the grass was destroyed) it should have been clear to people that the ‘official’ route to the next ped crossing was the paved one, and I imagine most people would see that the paved path leads to a ped crossing once they get to the edge of the one they have just finished and look over to the road.

      I’ve also taken to watching people cross from the nearby overbridge every now and then (they don’t let me out much) and people do use the dirt path in both directions. This suggests that at least the folks coming from the cable street side are using what they perceive is a quicker route, since they would take the paved path if they mistakenly thought the ped crossing continued straight ahead (i.e., if they made the same error that you suggest the running guys are making, but in the opposite direction).

      Whatever the case, the original path design has probably led to a less safe environment; the makeshift (‘faster’) grass path is currently attracting people toward the outside edge of the crossing, where they are closer to oncoming/stopped traffic. It’s speculation, but I suspect that if the grass path was properly paved it would direct people to the middle of the crossing more effectively. All the compacting work has even been done already!

  • Ben 16:38 on Saturday, November 7, 2009 Permalink | Reply
    Tags: Cialdini, FOWA, Human Biases,   

    Why You Should Read Some Cialdini 

    Recently, Carsonified posted this video of a Kevin Rose (Digg) speech at the Future of Web Apps conference in London.  The talk, titled “Taking your Site from One to One Million Users”, covers a range of methods for growing web traffic and engaging users.

    Although many of his examples are interesting in themselves, it is worth noting that a number draw upon core psychological principles first put together 25 years ago by Robert Cialdini in a book titled Influence.  Cialdini studied how social norms and ingrained behaviours have a massive influence on our responses to the various stimuli we are presented with on a daily basis.  He grouped them into six general categories:

    • Reciprocity
    • Commitment and Consistency
    • Social Proof
    • Authority
    • Liking
    • Scarcity

    You can read a little more about each of these here, but it really is worth taking the time to read the book (most libraries will have it).  It presents both the underlying motivators along with specific examples of their expression in practice, so it is more useful than hearing only the examples themselves, which don’t necessarily lend themselves to application in a range of different domains.

    Cialdini also recently co-authored a book titled Yes!, which presents summaries for over 50 scientific studies relating more-or-less to the six categories above.  It is a fascinating read.  Here are a couple of the findings:

    • Tips increase by up to 23% when waiters give mints to their customers directly, rather than letting them pick the mints up from a bowl at the counter.  [an example of reciprocity]
    • A hotel increased guest towel reuse rates (an environmentally friendly action) by 33% simply by changing the wording of the call-to-action message on a sign in the bathroom.  The most successful message suggested that others who had stayed in the same room recently had reused their towels. [an example of social proof, and also liking - we are influenced more by those who share attributes with us]
    • Asking people to predict whether or not they will go out and vote actually increases the chance they will go out and vote (by about 25% points in the study cited).  [an example of social desirability bias combined with commitment and consistency]

    There are many other examples in Yes! that translate the six general principles into practice, so you are bound to find some inspiration for mixing it up and applying the principles yourself.

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