Category Archives: User Behavior

The Segmentation of My Slime Trail

First published June 2, 2011 in Mediapost’s Search Insider

My connected life is starting to drop into distinct buckets. Now that I have my choice of connecting through my smartphone (an iPhone), my tablet (an iPad), my work computer (a MacBook) and my home computer (a Windows box), not to mention the new Smart TVs we bought (Samsungs), I’m starting to see my digital footprints (or my digital slime trail, to use Esther Dyson’s term) diverge. And the nature of the divergence is interesting.

Take Netflix, for example. It’s finally come to Canada, although with a depressingly small number of movies to choose from. My Netflix account stretches across all my devices, but the things I watch on my iPad are quite a bit different than my choices on an iPhone. And there is yet another profile for the things I choose on my MacBook (mainly when I travel). On the iPad, it’s typically an episode of “Arrested Development,” “Fawlty Towers” or, if I have a little more time, “Mad Men,” (and yes, I realize those three choices create an interesting psychological profile of myself) that offers some respite when the women of my household commandeer all available TV sets. On the new Samsung, it’s usually a movie intended for viewing by myself and at least one other member of my family.

Kindle offers a similar divergence of reading patterns — again, one application that’s spread across multiple devices. And, like my movie watching, my reading habits vary significantly depending on what I’m doing the reading on. I almost never read on my laptop, but it’s my preferred platform for research and annotation. My favorite reading device is my iPad, but it’s primarily used at home. I only take it on the road for extended trips. My fall-back is the iPhone, which gets called into duty when I have time to kill when traveling or in between my kid’s volleyball games.

Jacquelyn Krones, from Microsoft, did a fascinating research project where she looked at search habits across multiple devices. She found that our searches could be grouped into three different categories: missions, excavations and explorations.

Mission is the typical task-based single interaction where we need to get something done. The nature of the mission can be significantly different on a mobile device, where the mission is usually related to our physical location. In this case, geo-location and alternative methods of input (i.e. taking a picture, recording a sound or scanning a bar code) can make completing the mission easier, because the outputs are more useful and relevant in the user’s current context. This is why app-based search is rapidly becoming the norm on mobile devices. Missions on the desktop tend to be more about seeking specific information when then allows us to complete a task beyond the scope of our search interaction.

Excavations are research projects that can extend over several sessions and are typically tied to an event of high interest to the user. Health issues, weddings, major travel, home purchases and choosing a college are a few examples. The desktop is the hands-down winner for this type of search engagement. It provides an environment where information can be consolidated and digested through the help of other applications. Krones calls this “making knowledge,” implying a longer and deeper commitment on the part of the user.

Finally, we have exploration. Explorations are more serendipitous in nature,  with  users setting some fairly broad and flexible boundaries for their online interactions. While excavation can become a part of exploration, the behaviors are usually distinct. Exploration tends to be a little more fluid and open to suggestion, with the user being open to persuasion, while excavation is more about assembling information to support an intent that is already decided upon. Tablets seem to be emerging as a strong contender in the exploration category. The relaxed nature of typical interaction with an iPad, for example, supports the open agenda of exploration.

What this means, of course, is that the trail I leave behind on my mobile device starts to look significantly different than the trail on my laptop or tablet. Each fits a different use case, as they start to become tools with distinct capabilities, over and above the fact that they’re all connected to the Internet.

Risk, Reward and the Buying Matrix

First published December 23, 2010 in Mediapost’s Search Insider

Last week, I explored how two parts of our brain, the nucleus accumbens and the anterior insula, are key in driving our buying behaviors. I compared them to the gas pedal and brake of our buying “engine.” The balance between the two is key to understanding how we are driven towards our ultimate decisions. The nucleus accumbens drives our anticipation of an emotional reward, and the anterior insula creates anxiety around areas of risk.

As it turns out, you can plot the two as the axes of a matrix on which, theoretically, you could plot any purchase. The four quadrants would be, starting in the lower left and going clockwise: low risk/low reward,  low risk/high reward, high risk/high reward and, finally, high risk/low reward. Let’s take a deeper dive in each quadrant to see what kind of purchases fall into each.

Low Risk/Low Reward

This is the stuff of everyday life. If you’re a “to-do” list kind of person, these types of purchases would probably be on that list. Think of household supplies like toilet paper and laundry detergent, or the milk, dry goods, etc. that make up a large percentage of your grocery list. This is the world of consumer packaged goods. The only real exceptions are those products that represent personal indulgences, like a steak or your favorite premium ice cream.

There is a huge piece of the B2B market that falls into this category as well: office  and industrial supplies, parts and other often-purchased items.

There is no gas pedal and no brake on these purchases. While the low prices remove any real risk, these are also not the types of shopping trips you look forward to all day. You simply have to get them done. This means the personal engagement with the actual act of purchasing will be minimal. Here, we are creatures of habit. We go to the same places to buy the same things because we really don’t want to invest any more time than is necessary to get the job done. If you compete in this space, you have one strategy and one strategy only: provide the fastest and easiest path to purchase.

Low Risk/High Reward

Here, we have our little indulgences; the day-to-day treats that make life worth living. The entire premium consumer product industry lives squarely in this quadrant: premium desserts, pre-made meals, beauty care products, wines, craft beers and, moving into slightly greater degrees of risk, clothes, accessories, shoes, costume jewelry and electronic gadgets.  This is also where you’d find CDs, DVDs and books. It’s in this quadrant where Amazon rules.

These purchases are all gas and little brake.  If you ever make a purchase on impulse, it’s almost guaranteed to fall into this part of the behavioral matrix.  When women plan shopping trips, it’s to indulge their reward center with these types of purchases. But men are also vulnerable to the siren call of the indulgent purchase: gadgets, tools, sporting goods, electronic games — and, for the metro-men amongst us, clothes and accessories. By the way, manicures, pedicures and spa visits all qualify, along with movies, concerts and dining out.

This quadrant is particularly timely this time of year, because when you buy a gift for someone, you hope you’ve hit this quadrant. The tough part is knowing your recipients well enough to figure out what will kick their nucleus accumbens into high gear.

While the degree of risk doesn’t merit a lot of intensive research, here the buying can be as much fun as the owning, which generally means a higher degree of engagement on the part of the buyer. Shopping environments that enhance the reward part of the equation will be attractive. Buyers are susceptible to suggestion, especially if it comes through our social connections. And brand affinities are powerful here.

In my next column, I’ll provide some examples of the other two quadrants to see what kind of purchases fall into each. Then, we’ll see how each of these buying scenarios might map on the online consumer landscape.

Is the Internet Making Us Stupid – or a New Kind of Smart?

First published September 9, 2010 inn Mediapost’s Search Insider

As I mentioned a few weeks back, I’m reading Nicholas Carr’s book “The Shallows.” His basic premise is that our current environment, with its deluge of available information typically broken into bite-sized pieces served up online, is “dumbing down” our brains.  We no longer read, we scan. We forego the intellectual heavy lifting of prolonged reading for the more immediate gratification of information foraging. We’re becoming a society of attention-deficit dolts.

It’s a grim picture, and Carr does a good job of backing up his premise. I’ve written about many of these issues in the past. And I don’t dispute the trends that Carr chronicles (at length). But is Carr correct is saying that online is dulling our intellectual capabilities, or is it just creating a different type of intelligence?

While I’m at it, I suspect this new type of intelligence is much more aligned with our native abilities than the “book smarts” that have ruled the day for the last five centuries. I’m an avid reader (ironically, I’ve been reading Carr’s book on an iPad) and I’m the first to say that I would be devastated if reading goes the way of the dodo.  But are we projecting our view of what’s “right” on a future where the environment (and rules) have changed?

A Timeline of Intellect

If you expand your perspective of human intellectualism to the entire history of man, you find that the past 500 years have been an anomaly. Prior to the invention of the printing press (and the subsequent blossoming of intellectualism) our brains were there for one purpose: to keep us alive. The brain accomplished this critical objective through one of three ways:

Responding to Danger in Our Environments

Reading is an artificial human activity. We have to train our brains to do it. But scanning our surroundings to notice things that don’t fit is as natural to us as sleeping and eating. We have sophisticated, multi-layered mechanisms to help us recognize anomalies in our environment (which often signal potential danger).  I believe we have “exapted” these same mechanisms and use them every day to digest information presented online.

This idea goes back to something I have said repeatedly: Technology doesn’t change behavior, it enables behavior to change. Change comes from us pursuing the most efficient route for our brains. When technology opens up an option that wasn’t previously available, and the brain finds this a more natural path to take, it will take it. It may seem that the brain is changing, but in actuality it’s returning to its evolutionary “baseline.”

If the brain has the option of scanning, using highly efficient inherent mechanisms that have been created through evolution over thousands of generations, or reading, using jury-rigged, inefficient neural pathways that we’ve been forced to build from scratch through our lives, the brain will take the easiest path. The fact was, we couldn’t scan a book. But we can scan a Web site.

Making The Right Choices

Another highly honed ability of the brain is to make advantageous choices. We can consider alternatives using a combination of gut instincts (more than you know) and rational deliberation (less than you think) and more often than not, make the right choice. This ability goes in lock step with the previous one, scanning our environment.

Reading a book offers no choices. It’s a linear experience, forced to go in one direction. It’s an experience dictated by the writer, not the reader. But browsing a Web site is an experience littered with choices.  Every link is a new choice, made by the visitor. This is why we (at my company) have continually found that a linear presentation of information (for example, a Flash movie) is a far less successful user experience than a Web site where the user can choose from logical and intuitive navigation options.

Carr is right when he says this is distracting, taking away from the focused intellectual effort that typifies reading. But I counter with the view that scanning and making choices is more naturally human than focused reading.

Establishing Beneficial Social Networks

Finally, humans are herders. We naturally create intricate social networks and hierarchies, because it’s the best way of ensuring that our DNA gets passed along from generation to generation. When it comes to gene propagation, there is definitely safety in numbers.

Reading is a solitary pursuit. Frankly, that’s one of the things avid readers treasure most about a good book, the “me” time that it brings with it. That’s all well and good, but bonding and communication are key drivers of human behavior. Unlike a book, online experiences offer you the option of solitary entertainment or engaged social connection. Again, it’s a closer fit with our human nature.

From a personal perspective, I tend to agree with most of Carr’s arguments. They are a closer fit with what I value in terms of intellectual “worth.” But I wonder if we fall into a trap of narrowed perspective when we pass judgment on what’s right and what’s not based on what we’ve known, rather than on what’s likely to be.

At the end of the day, humans will always be human.

Wired for Information: A Brain Built to Google

First published August 26, 2010 in Mediapost’s Search Insider

In my last Search Insider, I took you on a neurological tour that gave us a glimpse into how our brains are built to read. Today, let’s dig deeper into how our brains guide us through an online hunt for information.

Brain Scans and Searching

First, a recap. In Nicholas Carr’s Book, “The Shallows: What the Internet is doing to Our Brains,” I focused on one passage — and one concept — in particular. It’s likely that our brains have built a short cut for reading. The normal translation from a printed word to a concept usually requires multiple mental steps. But because we read so much, and run across some words frequently, it’s probable that our brains have built short cuts to help us recognize those words simply by their shape in mere milliseconds, instantly connecting us with the relevant concept. So, let’s hold that thought for a moment

The Semel Institute at UCLA recently did a neuroscanning study that monitored what parts of the brain lit up during the act of using a search engine online. What the institute found was that when we become comfortable with the act of searching, our brains become more active. Specifically, the prefrontal cortex, the language centers and the visual cortex all “light up” during the act of searching, as well as some sub-cortical areas.

It’s the latter of these that indicates the brain may be using “pre-wired” short cuts to directly connect words and concepts. It’s these sub-cortical areas, including the basal ganglia and the hippocampus, where we keep our neural “short cuts.”  They form the auto-pilot of the brain.

Our Brain’s “Waldo” Search Party

Now, let’s look at another study that may give us another piece of the puzzle in helping us understand how our brain orchestrates the act of searching online.

Dr. Robert Desimone at the McGovern Institute for Brain Research at MIT found that when we look for something specific, we “picture” it in our mind’s eye. This internal visualization in effect “wakes up” our brain and creates a synchronized alarm circuit: a group of neurons that hold the image so that we can instantly recognize it, even in complex surroundings. Think of a “Where’s Waldo” puzzle. Our brain creates a mental image of Waldo, activating a “search party” of Waldo neurons that synchronize their activities, sharpening our ability to pick out Waldo in the picture. The synchronization of neural activity allows these neurons to zero in on one aspect of the picture, in effect making it stand out from the surrounding detail

Pirolli’s Information Foraging

One last academic reference, and then we’ll bring the pieces together. Peter Pirolli, from Xerox’s PARC, believes we “forage” for information, using the same inherent mechanisms we would use to search for food. So, we hunt for the “scent” of our quarry, but in this case, rather than the smell of food, it’s more likely that we lodge the concept of our objective in our heads. And depending on what that concept is, our brains recruit the relevant neurons to help us pick out the right “scent” quickly from its surroundings.  If our quarry is something visual, like a person or thing, we probably picture it. But if our brain believes we’ll be hunting in a text-heavy environment, we would probably picture the word instead. This is the way the brain primes us for information foraging.

The Googling Brain

This starts to paint a fascinating and complex picture of what our brain might be doing as we use a search engine. First, our brain determines our quarry and starts sending “top down” directives so we can very quickly identify it.  Our visual cortex helps us by literally painting a picture of what we might be looking for. If it’s a word, our brain becomes sensitized to the shape of the word, helping us recognize it instantly without the heavy lifting of lingual interpretation.

Thus primed, we start to scan the search results. This is not reading, this is scanning our environment in mere milliseconds, looking for scent that may lead the way to our prey. If you’ve ever looked at a real-time eye-tracking session with a search engine, this is exactly the behavior you’d be seeing.

When we bring all the pieces together, we realize how instantaneous, primal and intuitive this online foraging is. The slow and rational brain only enters the picture as an afterthought.

Googling is done by instinct. Our eyes and brain are connected by a short cut in which decisions are made subconsciously and within milliseconds. This is the forum in which online success is made or missed.

How Our Brains are Wired to Read

First published August 19, 2010 in Mediapost’s Search Insider

How do we read? How do we take the arbitrary, human-made code that is the written word and translate it into thoughts and images that mean something to our brain, an organ that had its basic wiring designed thousands of generations before the appearance of the first written word? What is going on in your skull right now as your eyes scan the black squiggly lines that make up this column?

The Reading Short Cut

I’m currently reading Nicholas Carr’s “The Shallows: What the Internet is Doing to Our Brains,” a follow-up to Carr’s article in The Atlantic, “Is Google Making Us Stupid?” The concept Carr explores is fascinating to me: the impact of constant online usage on how the neural circuits of our brain are wired.

But there was one quote in particular, from Maryanne Wolf’s book, “Proust and the Squid: The Story and Science of the Reading Brain,” that literally leapt off the page for me: ‘The accomplished reader, Maryanne Wolf explains, develops specialized brain regions geared to the rapid deciphering of text. The areas are wired ‘to represent the important visual, phonological and semantic information and to retrieve this information at lightning speed.’ The visual cortex, for example, develops ‘a veritable collage’ of neuron assemblies dedicated to recognizing, in a matter of milliseconds, ‘visual images of letters, letter patterns and words.'”

For everyone reading this column today, that is one of the most relevant passages you may ever scan your eyes across. It’s vitally important to digital marketers and designers of online experiences. Humans that read a lot develop the ability to recognize word patterns instantly, without going through the tedious neural heavy lifting of translating the pattern through the language centers of the brain. A quick neurological tour is in order here.

How the Brain Reads

The brain has a habit of developing multiple paths to the same end goal. Many functions that our brain controls tend to have dual routes: a quick and dirty one that rips through the brain at lightning speed and a slower, more rational one. It’s the neural reality behind Malcolm Gladwell’s “Blink.” This dual speed processing is a tremendously efficient way of coping with our environment. The same mechanism, according to Wolf, has been adapted to our interpretation of the written word.

Humans have an evolved capacity for language. Noam Chomsky, Steven Pinker and others have shown convincingly that we come out of the box with inherent capabilities to communicate with each other. But those abilities, housed in the language centers of the brain (Wernicke’s and Broca’s Areas, if you’re interested) are limited to oral language. Written language hasn’t been around nearly long enough for evolution’s relatively slow timeline to have had much of an impact. That’s why we learn to speak naturally just by hanging around other humans, but only those with a formalized and structured education learn to read and write. We have to take the native machinery of the brain and force it to adapt to the required task by creating new neural paths.

Instantly Recognizable…

So, when we read a page of text, there’s a fairly complex and laborious process going on in our noggins. Our visual cortex scans the abstract code that is written language, feeds it to the language centers for translation, and then sends it to our prefrontal cortex and our long-term memory to be rendered into concepts that mean something to us. The word “horse” doesn’t really mean the large, hairy, four-legged mammal that we’re familiar with until it goes through this mental processing.

But, like anything that humans do often, we tend to create short cuts through repetition. It’s important to note that this isn’t evolution at work, it’s neuroplasticity. The ability to read and write is built in each human from scratch. The brain naturally tries to achieve maximum efficiency by taking things we do repeatedly and building little synaptic short cuts. Humans who read a lot become wired to recognize certain words just by their shape and appearance, without needing to run the full processing cycle. Your name is a good example. How often have you been reading a newspaper or book and run across your last name? Does it seem to “leap off the page?” That was your brain triggering one of its little short cuts.

So, what does this mean for online interactions, particularly with a search engine? In next week’s column, I’ll revisit a fascinating brain scanning study that was done by UCLA and take a peek at what might be happening under the hood when we launch a Web search.

 

The Human-Technology Connection: Enabling Change

First published May 6, 2010 in Mediapost’s Search Insider

Aaron Goldman scooped my column on Apple, Siri and search (although, looking at the column, I think I can claim partial authorship) so I’m going to broaden the lens a little bit. This is a theme I’ve discussed in a number of recent presentations, as well as at least one prior column, and I think it touches on why the news from Apple and Siri is potentially so important.

Humans Will Be Human

I’ve said before that “technology doesn’t cause our behaviors to change, it enables our behaviors to change.” The difference is subtle but profound. Let me give you an example.

I recently moderated a panel discussion on social media in the B2B marketplace. One by one, the panelists marched out their supporting evidence (14 zillion people access Facebook every 12 seconds, that sort of thing) and their own opinions. The consensus was: things have changed. Indeed, they have. But at the top of the session, I said this wasn’t about technology, this was about people. And people are social animals. We follow the herd, and more importantly, we communicate with the herd. One could feel the “Groundswell” (a pun and plug in one!) literally surging through the room.

At the end, we turned to the audience for Q&A. A middle-aged woman, definitely falling on the Digital Immigrant side of the tech-savvy divide, stood up and called the entire panel out: “I don’t buy it. I don’t buy all this technology is making us more connected. I haven’t seen any evidence of it. In fact, I’ve seen the opposite. I’m a professional recruiter and I can’t get a candidate to pick up the phone and talk to me. I need to get to know them and I can’t do that through an email. I need to have a conversation. I think technology is isolating us, not connecting us.”

It’s All About Options

The panelists pointed out the generational differences between her and her candidates, saying that this could be the cause of the change of behavior. But I wanted to probe a little deeper, because I wasn’t so sure technology was the culprit here:  “I suspect that when you’re recruiting, your motivation to connect with a candidate is not always the same as their motivation to contact you,” I said.

“It’s your job and top of mind, but for them, you’re just an interruption in what they were already doing. They may not be ready to have a chat with you,” I continued. “Twenty-five years ago, when we were starting our careers, the phone was the only choice for instantaneous, ‘at-a-distance’ communication. But now, we have many choices, thanks to technology. So, they have options and they’re picking the one that’s appropriate. They’re time-shifting the interruption to a time more convenient, when they’re more motivated to contact you. I suspect that if we had that choice 25 years ago, we would have done the same thing. Technology hasn’t changed us, it’s just given us more options to do the things we really want to do.”

The Human Act of Searching

So why is that important for Siri, Apple and Search? Well, just as we had to adapt to the phone as an instant communication channel, we’ve had to adapt to the interface that search gave us to seek information. Let’s face it; typing words into a box is not the way we evolved to communicate. We talk. We touch. We listen. We see. We’ve had to adapt to a non-organic, structured format — 10 blue links in a list — because we had no choice. It was all the technology would allow at the time.

Also, separating the acts of retrieving information and doing something with the information is not natural for us either. We’re used to a tighter connection between the two. Information is seldom an end point. Doing something with the information is a much more common objective.  But up to now, search could only really act as an information retrieval tool.  It was powerful, and we adapted quickly because we recognized the power, but it wasn’t natural.

But look at what Siri and Apple are trying to do: On this platform, search is asking for something, getting it and immediately doing something with it. Sound familiar? It should. It’s what we’ve done for most of our history as humans. And that’s what technology, at it’s best, should do: give us more ways to be human.

Human Irrationality Online

irrationalLast week, I talked about the work of Daniel Kahneman, Amos Tversky, Herbert Simon and George Akerlof, key figures in helping define the foundations of consumer behavior, both rational and irrational, that dictate the realities of the marketplace. Today, I want to talk about how these emotional and cognitive biases and limitations play out online, but first, a quick recap is in order:

Prospect Theory – The role of psychological framing and emotional biases in determining human behavior in risky economic decisions. For example, how we’re more sensitive about loss than we are about gain.

Bounded Rationality – How we cannot endlessly consider all alternatives for the optimal behavior, but rather rely on “gut instincts” to help sort through the available alternatives.

Information Asymmetry – Why the marketplace has traditionally been unbalanced, with the seller almost always having more information about the product than the buyer.

This is Nothing New…

As I said last week, these are all hardwired human conditions that have been present for hundreds of generations, even though it’s only been recently that we’ve learned enough about human behavior to recognize them. And it’s these inherent tendencies that have changed the marketplace since the introduction of the Internet. The huge volume of information available online allowed us to shift the balance of the marketplace to be more equitably distributed between sellers and buyers. Let’s explore how each of these occurrences drove the behavioral change, which was enabled, not caused, by the introduction of the Net.

We understand that risk is present in almost all consumer transactions. This fact brings Prospect Theory into the picture. We will unconsciously employ our emotional biases to deal with the risk inherent in each purchase: the greater the risk, the greater the degree of bias.

The Risk/Reward Balance

Consumer motivation relies on us mentally balancing risk and reward. The balance between these opposing forces will dictate how we deal with risk mitigation. If there is a high reward — for example, buying our mid-life crisis sports car or taking our dream vacation — our emotional biases will be tilted towards maximizing this reward. Consumer research is really more about wish fulfillment than it is about risk mitigation.

But if there is little or no reward, our research takes a much different path. Think about how we approach the purchase of life insurance, for example. There is no inherent reward here, just risk — or rather, mitigation of risk. And insurance salespeople mercilessly exploit the emotional bias of loss by getting you to picture your family’s future without you in it.

Informed Does Not Always Equal Rational

This risk/reward balance will dictate what our online research will look like. And this is where Akerlof’s Information Asymmetry comes in. One of the ways we mitigate risk is by educating ourselves about our purchase. We look up consumer ratings, read reviews and pore over feature sheets.

Today, consumers are much more informed than they were a generation ago. But all that information does not necessarily mean we will make a more logical decision. We humans tend to look at information to support our emotional biases, rather than refute them. So, the balancing of information asymmetry is still done through the lens of our emotional and psychological frames, as shown by Kahneman and Tversky. We have access to information online, but each of us may walk away with different messages, depending on the lens we’re seeing that information through.

All This Information, All These Choices…

And that, finally, brings us to Simon’s concept of Bounded Rationality. We have more information than ever to sift through. As I said a few columns back, we can employ different strategies to make decisions. Some of us embrace bounded rationality, or satisficing, making us more decisive. It’s important to note here that the fact we’re trusting our gut to make these satisficing calls means that we may be trusting emotion rather than logic. Others try to optimize each decision, weighing all the variables. While this is perhaps a more rational approach, it can tax our cognitive limits, leading to frustration and often abandonment of the optimal path, resulting in a decision that ends up being a “gut” call anyway.

Our need to access information to mitigate risk has lead to the behavioral changes in consumer behavior. The Internet enabled this. It wasn’t technology that changed our behavior; it was just that technology opened the door to allow us to pursue our hardwired tendencies.

The Four Horsemen of the Consumer Behavior Apocalypse

First published March 25, 2010 in Mediapost’s Search Insider

Right out of the gate, let’s assume that we all agree consumer behavior is in the throes of its biggest shift in history. And the cause is generally attributed to the Internet.

While I don’t disagree with this assessment, I believe there may be some misattribution when it comes to cause and effect. Did the Internet cause our consumer behavior to change? Or did it enable it to change? The distinction may seem like mere semantics, but there’s a fundamental difference here.

“Cause” implies that an outside force, namely the Internet, pushed us in a new direction that was different from the one we would have pursued had this new force not come along. “Enable” is a different beast, the opening of a previously locked door that allows us to pursue a new path of our own volition. I believe the latter to be true. I believe we weren’t pushed anywhere. We went there of our own free will.

Free Will? Or Hardwired Human Behavior?

But, even in my last statement, language again gets us in a sticky place. “Will” assumes it was a conscious and willful decision. I’m not sure this is the case. I suspect there were subconscious, hardwired behaviors that had a natural affinity for the new opportunities presented by the online marketplace.

For most of our recorded history, we have assumed that rational consideration and conscious will forms the basis of human thought. If we did seem programmed automatically to respond to certain cues, this was as a result of being conditioned by our environment, the classic Skinner black-box approach. But when we were on top of our game, we were carefully considering pros and cons, making consciously deliberated decisions. These were the forces that drove our society and our behaviors. This theory formed the basis of economics (Adam Smith’s Invisible hand), Cartesian logic, and most market research.

But in the last few decades, this view of rationality riding triumphant over human foibles has been brought into question. In particular, there were three concepts put forward by four academics that caused us to question what drove our behaviors. These folks uncovered deeper, subconscious routines and influences that lay buried beneath the strata of rational thought. And it’s these subconscious behaviors that I believe found the new online opportunities so enticing. Let’s spend a little time today looking at these four thinkers and the new paradigms they asked us to consider.

Amos Tversky and Daniel Kahneman – Prospect Theory

Adam Smith’s Invisible hand, driven by the wisdom of the market, has been presumed to be the ultimate economic governing factor. The assumption was that each of us, individually making rational economic decisions, would ultimately decide winners and losers and capitalism would stay alive and well.

But Tversky and Kahneman, in their paper on Prospect Theory, showed that the invisible hand might not always be guided by a decisive and logical mind. We all have significant hardwired cognitive biases that often cause us to make illogical economic choices. For example, if I offered you $1,000, with no questions asked, or a chance to win $2,500 based on a coin toss, you’d probably take the sure bet, even though mathematically, the odds for net gain are better with the coin toss.

Prospect Theory shot some holes in the previous theory of Expected Utility, a model where we carefully weighed the pros and cons of a potential purchase based on a return on investment model. Emotional framing and risk avoidance played a much bigger role than we suspected, handicapping our logic and often guiding us down non-rational paths. Tversky and Kahneman single-handedly found the new discipline of Behavioral Economics and changed our thinking in the process.

Herbert Simon – Bounded Rationality

Simon’s concept of Bounded Rationality superseded Kahneman and Tversky’s theory, but it dovetailed with it very nicely. Even if we are rationally engaged in a decision, Simon argued, we couldn’t possibly optimize it, especially in complex scenarios. There were simply too many factors to consider. So, we took “gut feeling” short cuts, which Simon called “satisficing,” a combination of satisfy and suffice. We short-listed our consideration set by using beliefs and instincts.

To make the satisficing short list is the goal of any brand campaign. At some point, logical weighing of pros and cons has to give way to calls based primarily on instinct.  And, as Kahneman and Tversky showed, those instinctive calls may well be based on irrational emotional biases.

George Akerlof – information Asymmetry

The last piece, and the one that really drove the online consumer revolution, is George Akerlof’s Information Asymmetry theory. Traditionally, there has been an imbalance of information between buyers and sellers, to the seller’s advantage. The seller always knew more about what they were selling than the buyer did. This made purchasing inherently risky.

With an absence of information, consumers created strong beliefs about brands as a way to guide their future buying decisions. Brand loyalty, whether rational or not, filled the void left by a lack of information. Manufacturers and retailers carefully controlled what information did enter the marketplace, pushing the positives and carefully suppressing the negatives.

These three concepts, intertwined, defined the psychological make-up of the market prior to the introduction of the Internet. In my next column, I’ll explore what happened when these behavioral powder kegs were exposed to the fanned flames of the digital marketplace.

Search and Decisiveness

First published February 25, 2010 in Mediapost’s Search Insider

My last two columns (column 1 | column 2) explored decisiveness within a very defined scope: college students picking courses. I did that by analyzing an interesting study conducted by Wesleyan University, which used eye tracking to show how decisive and indecisive people differed in their processing of information.

In reading the study, my mind went back seven years to one of the first research studies Enquiro ever did (and still our most popular download): Inside the Mind of the Searcher. In it, we observed the behaviors of 24 individuals as they used search engines to carry out tasks. It was the first qualitative study we did, before we used eye tracking. But the Wesleyan study reminded me of some interesting insights from that study.

As we looked at the group, we started seeing some different search strategies, which we divided into four groups: The Scan and Clicker, The 2 Step Scanner, the Deliberate Researcher and the 1,2,3 Searcher.

Here is a brief description of each:

The Scan and Clicker (12.5% of our total group). These people scanned the top three or four results and clicked right away if they found something of interest. They were less likely than the 2 Step Scanners to return to the results set.

2 Step Scanners (25% of our total group). They’d scan the top results, same as the Scan and Clickers, and might click on a listing of interest, but would tend to “pogo stick” more, clicking through to a site, but then returning to the search engine and checking out at least one or two other sites before committing to one site.

Deliberate Researchers (41.6% of our total group). This group felt they had to scan the entire results set before clicking on a result. This group spent the longest time on the page, almost 40 seconds, compared to 15 to 20 seconds average duration for the other searchers.

The 1,2,3 Searchers (20.8% of our total group) This group worked down the results in order, seeming to consider each result individually. There didn’t appear to be as much back and forth consideration as we saw in other groups. Of course, we weren’t using eye tracking, so it was difficult to accurately track specific eye movements.

Now, these sessions were recorded seven years ago now, so I suspect some of the behaviors we saw were modified as people became more familiar with search engines. I’ve talked before about how we develop conditioned strategies through repeated tasks. Search is a prime candidate for this.

Decisiveness and Search Patterns

In looking back, it does seem that the same decisiveness vs. indecisiveness behaviors identified in the Wesleyan study were also appearing in ours.

One of the interesting things I’ve found in our own research, and something also alluded to in the Wesleyan study, is that you need to track behaviors in minute detail before you start to see the nuances that may indicate different underlying strategies. For example, we’ve seen aggregate heat maps that look almost identical between two groups, but it was only when we walked through the eye movements on a second-by-second (even a quarter-second-by-quarter-second) basis that we saw people taking significantly different paths to end up at the same destination.

The Wesleyan study found that under the pressure of time, indecisive people might abandon maximizing strategies to adopt “satisficing” behavior. This may yield similar results at the end, but can generate greater levels of stress and anxiety on the way to a decision.

I suspect decisiveness could be a critical factor in how we might navigate any Web page, including a set of search results. For example, how would decisiveness impact our interaction with the sponsored ads at the top of the page, or visually richer results? Great questions — currently with few answers.

I’ll see what I can do about that.

Maximizers vs. Satisficers: Why It’s Tough to Decide

First published February 18, 2010 in Mediapost’s Search Insider

In last week’s column, I introduced the study from Wesleyan University about how decisiveness played out for a group of 54 university students as they chose their courses.  The student’s eye movements were tracked as they looked at a course comparison matrix.

Weighing all the Options vs Saying No

In the previous column, I talked about two different strategies: the compensatory one, where we weigh all the options, and the non-compensatory one, where we start eliminating candidates based on the criterion most important to us. Indecisive people tend to start with the compensatory strategy and decisive people go right for the linear approach.  I also talked about Barry Schwartz’s theory (in his book “The Paradox of Choice”) that indecisiveness can lead to a lot of anxiety and stress.

The biggest factor for indecisive people seems to be a fear of lost opportunity. They hate to turn away from any option for fear that something truly valuable lies down that path. Again, this is territory well explored in Tversky and Kahnemann’s famous Prospect Theory.

The Curse of the Maximizer

Part of the problem is perfectionism, identified by Schwartz as a strong corollary to anxiety caused by impending decisions. The Wesleyan research cites previous work that shows indecisive people tend to want a lot more information at hand before making any decisions. And, once they’ve gone to the trouble to gather that information, they feel compelled to use it. Not only do they use it, they try to use it all at once.

The Wesleyan eye tracking showed that the more indecisive participants went back and forth between the five different course attributes fairly evenly, apparently trying to weigh them all at the same time.  Not only that, they spent more time staring at the blank parts of the page. This indicated that they were trying to crunch the data, literally staring into space.  The maximizing approach to decision-making places a high cognitive load on the brain. The brain has to juggle a lot more information to try to come to an optimal decision.

Decisive people embrace the promise of “good enough,” known as satisficing. They are less afraid to eliminate options for consideration because the remaining choices are adequate (the word satisficing is a portmanteau of “satisfy” and “suffice”) to meet their requirements. They are quicker to turn away from lost opportunity. For them, decision-making is much easier. Rather than trying to juggle multiple attributes, they go sequentially down the list, starting with the attribute that is most important to them.

In the case of this study, this became clear in looking at the spread of fixations spread amongst the five attributes: time of the class, the instructor, the work load, the person’s own goals and the level of interest. For decisive people, the most important thing was the time of class. This makes sense. If you don’t have the time available, why even consider what the course has to offer? If the time didn’t work, the decisive group eliminated it from consideration. They then moved onto the instructor, the next most important criterion. And so on down the list.

Tick…Tick…Tick…

Another interesting finding was that even though indecisive people start by trying to weigh all the options to look for the optimal solution, if the clock is ticking, they often become overwhelmed by the decision and shift to a non-compensatory strategy by starting to eliminate candidates for consideration. The difference is that for the indecisive maximizers, this feels like surrender, or, at best, a compromise. For the decisive satisficers, it’s simply the way they operate. If the indecisive people are given the choice between delaying the decision and being forced to eliminate promising alternatives, they’ll choose to delay.

This sets up a fascinating question for search engine behavior: do satisficers search differently than maximizers? I suspect so. We’ll dive deeper into this question next week.