Is the Web a Perfect Information Market? And what does that means for brands and politicians?
Behavioural economics is the dismal science with people brought back in. I think it tells us that the more perfect a market, the easier it is to see human irrationality at work. The web is a perfect information market, full of glitches of course, but one that REALLY shows human irrationality and its consequences.
The definition of a perfect market would be something along the lines of information being freely and equally available in the same timely manner to all participants. Sounds like the web.
This is one of the reasons why we think the web acts in a bull and bear kind of way that stock markets also do. And why we think marketing has to think less rationally and change its expectations.
My vote for the most irrational market behaviour of people is the Apple iPhone. Apple dominates the market in information about mobile handsets, and specifically that of smart phones.
First a piece of external data from Hitwise: iPhone almost immediately outstripped interest in the iPod just about from the minute it was launched.
Then there was consolidation of that interest until by late 2008 the iPhone was unassailable in the market for smart phone information. We studied the iPhone and Android, the Google-led open source operating system for mobile phones, from December 2008 to March 2009 to compare the two, to understand the web as an information market for handsets.
If you want to get on top of the very latest in the iPhone bull market turning bear take a look at this post of yesterday from Michael Arrington at Techcrunch. Om Malik is also an iPhone sell advocate. Interesting point is both have lived with serious iPhone negatives for two years and chose not to write or mention this. And the sell recommendation is not based in performance negatives. It is based on new contract conditions that Apple and AT+T want to impose.
So let’s turn the clock back. During our study period there was no major iPhone initiative or announcement. There was however the announcement of the first Android handset, the HTC G1.
Under normal circumstances Android, with the infinite reach of Google, and HTC should have dominated the information market for mobile handsets during this period.
What happened? During that time iPhone garnered 12 times more information flow than the G1 and Android combined.
The normal way to look at this is to say the iPhone gets stronger information flow because it is more popular. But we don’t believe the web works that way.
Take Facebook as a parallel. There is little in the way of competition to Facebook. It has define a service that is similar on concept to many other social networks but no-one else tops 200 million users. There is a bull market in Facebook information. Its numerical success bears only an ill defined relationship to its inherent qualities.
In our view there is a tipping point in cases like iPhone and Facebook where the fact of information becomes more critical than their features, price or quality.
The iPhone is a poorly constructed product, with a long lock-in contract, arguably with poor performance characteristics compared to competitors.
If the only answer to its success is the user interface or usability then we’d have to conclude that all products should focus primarily in usability regardless of performance. In the case of the iPhone consumers choose to pay a higher than normal price to ignore poor performance.
Instead we believe iPhone addiction is the phenomenon we are looking at. As with Facebook. And other online bull markets. The kind of factors that are at work are confirmation bias – a tendency to take on only information that works as confirmation of our views; and availability bias – a tendency to use the latest information available rather than the balance of information.
Neither of these explains the peculiar web characteristic that we see with the iPhone, that people are generating information about it, all the time and that this information is crowding out other information about smart phones. To get at that we need to look at the sources of influence in web information markets. We’ll be digging out our Android study to do that in our next post.
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