Herbert Simon came up with some pretty interesting concepts, among them satisficing, bounded rationality and chunking.

Before Simon, we commonly believed that humans came to optimal decisions in a rational manner, based on the information provided. We took all the data that was accessible, weighed pros and cons and used our cortexes to come to the best possible outcome.

Simon, in effect, said that this placed to high a load on us cognitively. In many cases, there was simply too much information available, so we had to make choices based more on heuristics, cutting the available information down to a more manageable level. He called this “satisficing”, a blend of satisfy and suffice. And Simon started saying this a half century ago. Imagine how this translates to the present time.

We have never had more information available. At the click of a mouse, we can access huge amounts of information. There’s simply no way we can process it all and come to rational decisions. And this brings us to another concept, that of bounded rationality. We’re more rational about some decisions than others. It depends on a number of factors, including risk, emotional enjoyment and brand self identification. Think of it as a chart with three axes. One axis is risk. We put more rational thought into decisions that expose us to greater risk. In consumer decisions, risk usually equates with cost, but in B to B decisions, it could also include professional reputation (related to but not always directly tied to cost). We’re going to put a lot more thought into the purchase of a car or house than that of a candy bar. Another axis is emotional enjoyment. This is a risk/reward mechanism to most decisions, and if the reward is one that is particularly appealing to us, we tend to be swayed more by emotion than rational decision. If we’re planning a holiday, we may make some irrational decisions (or at least, they might appear that way to an outsider) based on a sense of rewarding ourselves. We’ll treat ourselves to a few nights in a 5 star resort, when the 3 star resort would offer greater overall value. The final factor, and one that is usually buried somewhere in our subconscious, is how we use brands or products to define who we are. Now, no one usually admits to being defined by a brand, but we all are, to some extent. This touches on the cult-like devotees that some brands develop. Harley Davidson, Rolex, BMW, Apple and Nike all come to mind. Is a Rolex a rational choice? No. But a Rolex defines, to some extent, the person wearing it. It says something about the person.

Bounded rationality says that there are boundaries to the amount of rational thought that we can and we want to put into decisions. The amount we decide is sufficient depends on the three facts discussed.

Now, the use of Search tends to plot somewhere along this 3 dimensional chart. If risk is high and brand identification is low (buying software for the company), there is a high likelihood that search will be used extensively. If risk is low and brand identification is high (i.e. buying a soft drink or a beer) there is almost no likelihood that search will be used. In this case, the two factors usually work inversely to each other. Emotional enjoyment isn’t as directly tied to search activity. We will do as much (or as little) searching for a purchase that will give us great enjoyment as for those that won’t.

It’s interesting to watch how these factors impact search intent and behavior. Satisficing leads to a classic sort of search behavior, what I call I category search, where we use fairly generic, non branded queries that broadly define the category we’re looking at. Let me give you an example. Tomorrow my wife and I are headed to Europe for a week. We’re going to spend a few days in Portugal, then fly up to London for SMX (where I’ll be talking more about these ideas in some of my sessions). We’re flying into Lisbon, then renting a car and driving down to the Algarve region. I have GPS navigation software for my PDA, but only for North America. I wanted to get European software, but because of the limited use of it, I didn’t want to spend too much. The developer of my North American software didn’t make a EU version, so I turned to search to find a suitable candidate. Here there was no brand identification, some degree of risk (if it didn’t work in Europe, I’d be lost, literally) and no emotional enjoyment factor. My first search was what I call a “landmark” search. I wanted to find some sites to plot the landscape. Sites that listed and compared my alternatives would be ideal matches to my intent.

I searched for “pocket pc gps software”, knowing that “gps software” would be too broad. I soon found the sites were pretty much all about North American versions. Few of them offered or reviewed European versions. I spent several minutes on the TomTom site trying to order a European version from Canada but to no avail. Apparently TomTom doesn’t believe people in North America would ever choose to drive in Europe.

In classic “satisficing” behavior, I wanted to cut my research workload by setting some basic eligibility criteria: it had to work on a Pocket PC, it had to be reasonably priced (under $100 preferably) and it had to offer coverage for all of Europe (we’re going back to France and Italy next year and I’d like to use it then as well). My next search was for “pocket pc gps software europe”. This gave me what I needed to begin to create my satisficed list. Ideally, we want 3 or 4 alternatives to compare. I did find the TomTom choice, but I was already frustrated with this, and the price was over my threshold. Destinator also offered an alternative that seemed to be a little better match. It matched all the criteria, appeared to have some decent reviews and was available on eBay for about $75, including shipping. Sold! Was it the optimal choice? Maybe not. If I had spent hours more doing research, I could have probably found a better package or a better value. But it was good enough.

Chunking has to do with cognitive channel capacity, and the amount of information we can store in our heads, accessible for use. Again, we tend to maximize the available slots by creating chunks of information, grouping similar types of information together.

When you look at Simon’s work, even though the majority of it far preceded search engines, it sheds a lot of light on how we use search in a number of cases. If you want to tap into user intent, I would recommend finding out more about bounded rationality and satisficing. Chunking is probably worth a look as well.