Category Archives: Search Behaviors

Our Indelible Lives

First published June 3, 2010 in Mediapost’s Search Insider

It’s been a fascinating week for me. First, it was off to lovely Muncie, Ind. to meet with the group at the Center for Media Design at Ball State University. Then, it was to Chicago for the National Business Marketing Association Conference, where I was fortunate enough to be on a panel about what the B2B marketplace might look like in the near future. There was plenty of column fodder from both visits, but this week, I’ll give the nod to Ball State, simply because that visit came first.

Our Digital Footprints

Mike Bloxham, Michelle Prieb and Jen Milks (the last two joined us for our most recent Search Insider Summit) were gracious hosts, and, as with last week (when I was in Germany) I had the chance to participate in a truly fascinating conversation that I wanted to share with you. We talked about the fact that this generation will be the first to leave a permanent digital footprint. Mike Bloxham called it the Indelible Generation. That title is more than just a bon mot (being British, Mike is prone to pithy observations) — it’s a telling comment about a fundament aspect of our new society.

Imagine some far-in-the-future anthropologist recreating our culture. Up to this point in our history, the recorded narrative of any society came from a small sliver of the population. Only the wealthiest or most learned received the honor of being chronicled in any way. Average folks spent their time on this planet with nary a whisper of their lives recorded for posterity. They passed on without leaving a footprint.

Explicit and Implicit Content Creation

But today — or if not today, certainly tomorrow — all of us will leave behind a rather large digital footprint. We will leave in our wake emails, tweets, blog posts and Facebook pages. And that’s just the content we knowingly create. There’s a lot of data generated by each of us that’s simply a byproduct of our online activities and intentions. Consider, for example, our search history. Search is a unique online beast because it tends to be the thread we use to stitch together our digital lives. Each of us leaves a narrative written in search interactions that provides a frighteningly revealing glimpse into our fleeting interests, needs and passions.

 Of course, not all this data gets permanently recorded. Privacy concerns mean that search logs, for example, get scrubbed at regular intervals. But even with all that, we leave behind more data about who we were, what we cared about and what thoughts passed through our minds than any previous generation. Whether it’s personally identifiable or aggregated and anonymized, we will all leave behind footprints.

 Privacy? What Privacy?

Currently we’re struggling with this paradigm shift and its implications for our privacy. I believe in time — not that much time — we’ll simply grow to accept this archiving of our lives as the new normal, and won’t give it a second thought. We will trade personal information in return for new abilities, opportunities and entertainment. We will grow more comfortable with being the Indelible Generation.

Of course, I could be wrong. Perhaps we’ll trigger a revolt against the surrender of our secrets. Either way, we live in a new world, one where we’re always being watched. The story of how we deal with that fact is still to be written.

Google vs Apple: an Open and Closed Case

First published May 27, 2010 in Mediapost’s Search Insider

Yesterday, I was eavesdropping on a debate about open-source vs. closed systems. I found the debate fascinating because two of the most important contributors to what our search experience might look like live at opposite ends of this debate. Apple is adamant about locking down every aspect of the user experience. Google wants to open it up to any and all comers. The third player, Microsoft, sits somewhere in between. The debate was about who might prevail. I was uncharacteristically silent during all this, because I had to think about it before throwing in my two cents. Now, 24 hours later, it’s time to toss in my ante.

In theory, open source should win hands down. The open environment allows a cooperative ecosystem to evolve, guaranteeing a rate of innovation simply not possible in closed system. But I think it depends on where we are in the maturity of the market. Open source allows for more innovation, but it’s also an open invitation for more things to go wrong. This can be deadly as you try to push along market adoption.

Apple Closes the Loop

There is a reason why Apple is the darling of the early adopter. The company insist on things working. And you can only do this when you can lock down each and every aspect of the user experience. If there’s one thing Apple understands at its core (sorry, couldn’t resist), it’s how to make a user happy. The Jobs BHAG of creating “insanely great” products only works if all that insanity leads to an expected end result. And I challenge anyone who’s used both a Mac and a Windows box to tell me that the Apple user experience isn’t more refined, more elegant and more delightful.

In the early days of market adoption, this stuff is important. You don’t want to drop way more cash than you should on a new tech-toy only to find the interface is clunky, amateurish and full of glitches. With Apple’s meticulous attention to detail, you know that whatever is available on your new iToy will work near-flawlessly. Sure, the code-police from Cupertino are overly dictatorial, which isn’t winning them any friends in the programming community, but the apps that are the end result are ridiculously simple to use and frequently beautiful to look at.

Google’s UX Challenges

Now, look at Google. I tried to find a polite way to say this, but couldn’t, so I’ll just lay it on the table: Google sucks at interface design. For years we’ve been lauding the simple, spartan look of Google search. The fact is, simple was all we needed for an ordered list of text results. Google’s algorithm provided enough power in the backend to make up for an anemic interface. But today, now that everyone’s caught up in the algo department, Google’s interface looks like a Grade 8 coding project.  The new 3 column search format follows in the footsteps of Gmail, Google Docs, Google Calendars and most other Google interfaces: it looks like it was designed by an engineer.

In my company, we tried to move to using Google’s suite of tools based on the fact that in an open-source environment, we should see more rapid innovation. Well, that and the price was hard to argue with. But the fact is, everyone on our team is completely fed up with clunky Google interfaces that seem full of quirks. It doesn’t feel like we’re using leading-edge innovation, it feels like we’re using freeware. And I, for one, expect more from Google.

Google … Give me that GUI Feeling!

That’s the problem with open source early in the market adoption model. There’s not enough maturity in the market to force developers to worry about nuance. User experience is considered the polish — the last thing to be applied. You can’t lock down all the details needed to guarantee a consistently acceptable user experience.

I still have tremendous respect for the innovation engine that sits at the heart of Google, but if I had one piece of advice to pass along, it would be this: Worry less about changing the world, and  more about polishing up the Gmail interface. You can always change the world tomorrow, but today I’d like to retrieve my email from something that doesn’t look like a dog’s breakfast.

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 Our Online “Set Point”

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

Derek Gordon’s piece on Siri this week gave concrete proof of what I’ve been saying about the transition of search from a destination to a utility. Consider the example Derek gave of Siri’s functionality:

make action-oriented queries into your iPhone like “find me a good French restaurant for two tonight.”  Using your iPhone’s location coordinates, it will search Yelp for positive reviews of restaurants in your area, find a reservation for the most popular one via OpenTable and ask if you’d like to confirm a reservation.  Once you’ve confirmed the time, Siri will book the reservation for you. 

Notice the words Derek uses: “search” Yelp, “find” a reservation, both as intermediate steps to the end goal, allowing you to take action. And the Siri interface sits between you and the sources of the information. It’s exactly this interposing of a layer of functionality between the information and the user that I was talking about two weeks ago when I said that Steve Ballmer was thinking about the future of the search revenue model.

An application like Siri is only as good as the number of things it can do. Functionality, not information, is the new promise of the Internet. As John Battelle said in a recent chat with me, we quickly adjusted to the fact that the Internet could make us smarter. Now we expect it to let us do things better and faster. Information is only a means to an end.

Our Online ‘Set Point’

University of Pennsylvania psychologist Martin Seligman believes that we have a happiness “set point.” For example, winning a lottery doesn’t really make us happier in the long run. We just ratchet up our level of expectation to accommodate our new circumstance. I believe the same is true about our feelings towards advanced technology.

In the early days of the Internet, we were consistently amazed when we found information “out there.”  It seemed that no matter what we were looking for, with enough diligence, we could find some source for it. The Internet was one big information archive, and search was the key we used to unlock it. But as with happiness , we’re very quick to reset our expectations. Amazement quickly gives way to a sense of entitlement. We now accept the fact that the information is out there somewhere.  We now expect applications to gather it for us and present us with an opportunity to act on it.

The Road Ahead for Search

In a few short weeks, we’ll be gathering on Captiva Island in Florida to discuss where search is going. I believe a central theme will be this idea of search as a step towards usefulness.  We have reset our expectations and we need more from search. And this raises an interesting possibility. I have talked before about how Google became a habit for us. But habits only remain stable as long as they produce the expected results. Once we stop getting what we expect, we ready ourselves to break the habit and build a new one. It’s hard cognitive work, but we will undertake it if the payoff is worth it in terms of expected utility. As our expectations, fueled by glimpses of potential functionality through apps like Siri, are raised to a new set point, we will be less satisfied with the vanilla search experience offered by Google. This means, finally, we may be ready to break the Google Habit.

Google’s counter to that will be that Siri benefits from having a very focused purpose, supported through a dedicated interface and structured data. It’s impossible to match that functionality across all categories and use cases. Very true and very rational — but it doesn’t matter. If our online “set point” gets reset, our loyalty to Google will suffer. Suddenly, we won’t be satisfied anymore, because we believe something better is out there.

Steve Ballmer and the Future of Search Revenues

First published March 4, 2010 in Mediapost’s Search Insider

Steve Ballmer is an enthusiastic guy. As he climbed on stage with Danny Sullivan at SMX West, everyone was wondering how long it would be before he cranked up the volume and slipped into his typical Ballmeresque bombastic delivery. Steve didn’t disappoint. A few minutes into the interview, with Sullivan probing about Microsoft’s aspirations around search, Ballmer was yelling “Sell, Danny, don’t yell!” (ironic in the extreme) and roughhousing with poor Danny like a good-natured football coach having a little fun with the class math geek. I half expected Steve to give Sullivan a noogie.

I suspect there will be no shortage of coverage on the keynote and the areas explored. Ballmer was careful to tone down his enthusiasm about Bing with a realistic nod to Google’s current dominance. But there was one comment in particular that I want to explore a little further today. Ballmer made all the obligatory comments about us being very early in the game a search, an observation that has become rote in search interviews. And usually, that observation refers to the user experience, the functionality or the platform from which we search.  But Ballmer purposely singled out one area that is not generally talked about when we discuss the nascence of search — the revenue model.

The Crystallization of a Revenue Model

Search as it exists today proved to be the perfect crystallization of a revenue model, a beautifully simple evolution that had all the right pieces falling into place at just the right time. It was a rare occurrence in the messy and organic online world, one that Google capitalized on to the tune of several billion dollars. But it’s unrealistic to think that this crystallization of revenue opportunity can survive for long or morph into something equally universal, simple and effective.

Here’s what happened: Search solved a fundamental human need  — the need to access information. Google did search better than anyone else. All this searching happened in a small handful of places, with Google as the dominant destination. Much of this searching was for information that came from consumer intent.  And, because consumers were searching for information, sponsored messages could be informational in tone rather than overtly promotional. Search was a “click,” the natural and simple connection of burgeoning need with marketing opportunity.

It’s Not That Simple Anymore

But here’s what’s happening now: Search is not as simple as it was. Increasingly, our search activity is splintering over more platforms and through more interface layers. Search is going “under the hood,”  powering a number of different apps for a number of different needs. This means the ubiquitous and universal intersection point for search is going away. We’re demanding more from search — more functionality, more integration, more understanding of how we intend to use the information we seek. This raising of the bar of our expectations means it will become increasingly difficult for one interface to serve all those needs.

As we start doing more online — finding the functionality we need to take us not just from point A to B, but allowing us to continue on to C, D and even Z, with digital servants assisting with, or even allowing us to completely ignore, the interim steps — search will just be another piece of that functionality. This “usefulness” explosion is very unlikely to happen in one place. It will happen in thousands or millions of places. And search will be relegated from being an online destination to an online utility.

Google, Microsoft, and any other search provider, will lose the critical revenue-producing high ground, the touch point with the consumer, at least in the form it currently exists. This will require a rapid shift in revenue models, and I suspect it’s this impending shift that Ballmer was alluding to in his keynote. There will be revenue to be made — far more revenue, in fact. But Google and Microsoft may find themselves in the position of taking a much smaller slice of a much larger pie.

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.

Decisiveness and Search: Two Different Strategies

First published February 11, 2010 in Mediapost’s Search Insider

In “The Paradox of Choice,” author Barry Schwartz speculates that we all might be happier if we had fewer options in life. Our consumer-based society continually pumps out more and more options, forcing us into making more and more decisions. Schwartz convincingly draws a parallel between decisiveness and happiness. The less time we spend making decisions, the more we’ll be satisfied with our lives, he says.

A new study out of Wesleyan University explores the actual cognitive mechanisms of decisiveness. This has direct implications for search marketers, because every time we use a search engine, we’re forced to make decisions. In fact, every online interaction is a branching tree of decisions. The study provides new insight into the decision-making process we use as we guide ourselves through the online landscape.

Study Set-Up

The researchers at Wesleyan used a scenario familiar to their sample of 54 students: they had to pick courses for the upcoming semester. Course options were set up on a matrix that allowed students to evaluate their options on a few different criteria: time of the course, instructor quality, relevance, amount of work required and interest in topic. There were no “no-brainer” options. In each alternative, trade-offs were required.

The researchers also introduced a variable into the mix: the opportunity to delay final course selection.

Finally, they asked the students to use the course grid to help make their selections while using an eye-tracker to capture exactly what they looked at on the grid. After the task was completed, participants were asked to grade themselves on a standard decisiveness scale.

Decisive vs. Indecisive Strategies

Building on previous academic work on decisiveness, the researchers found that individuals tend to use two different strategies when making decisions.  The compensatory strategy tries to weigh all the decision attributes together, literally creating an evaluation formula in the decision-maker’s mind.  If there are five different decision criteria, all are considered at the same time and are weighted by the importance of each to the individual.

In a purely rational world, this would seem to be the optimal strategy, but as Schwartz pointed out, we are not rational decision-making machines. In their Nobel prize-winning work on Prospect Theory, Amos Tversky and Daniel Kahnemann  (and more recently, Dan Ariely) showed that we use irrational risk-triggered biases in our decision-making. These throw some significant wrenches into the workings of our decisiveness. Emotions get involved and we start feeling anxious. Decisions, even about things that will bring eventual rewards, start to cause us stress.

The other decision strategy is a non-compensatory, linear strategy. This is the foundation of Herbert Simon’s famous “satisficing” approach. Here, alternatives are quickly cut down by a sequential consideration of criteria, beginning with the one most important to the decision-maker. In the study scenario of picking courses, many looked first at the time the class would be taught, reasoning that if the time didn’t work for them, there was little point in considering the other things the course might offer. This quickly narrowed the consideration set. From there, they moved on to the next most important criterion. This sequential approach is relatively ruthless in eliminating candidates for consideration.

This study, along with others, found that indecisive decision-makers tend to start with a compensatory strategy, while decisive people start short-listing immediately with a non-compensatory strategy. In the next column, we’ll see how this difference in strategies was clearly shown in the eye tracking results. I’ll also explore how indecisive individuals are often forced to abandon one strategy for the other, which can cause significant stress.