Category Archives: Search Behaviors

The Elusive Goal of Ad Engagement

First published October 16, 2008 in Mediapost’s Search Insider

Last week, I talked about the nature of engagement and the neural mechanisms that underlie it. This week, I want to explore why those same mechanisms dictate that our search interactions are going to be completely different from engagement with a TV ad or a billboard.

The key thing to understand here is how we’re driven by goals. In a drastic oversimplification, goals are the objectives that drive our information processing modules, more commonly known as our brain. Our “mind” and all that we know about ourselves are shifting patterns of information being processed in these modules. At multiple levels, we sift through data, make decisions and initiate actions to get us closer to our goals.

Goal Interrupted

Most advertising is interruptive. It’s a detour on the road to our goals. The holy grail of direct marketing is to time delivery of the message so that it coincides with our pursuit of a goal. If you can get a realtor brochure to my doorstep at exactly the time I’m thinking of putting my house up for sale, you’ve substantially increased the odds of active engagement with your advertising message. But despite the advances in targeting methods, the odds of perfect coincidence are frustratingly slim. So advertising has to depend on other methods, like emotion, to trigger primal reactions and force suspension of current goal pursuit to engage with the message.

One of the comments on last week’s column, by fellow Search Insider Kaila Colbin, provides a perfect example of this. Kaila provided a link to a particularly powerful use of emotion in a TV ad from New Zealand Post. Now, despite the powerful emotional appeal, in a typical stream of ads inserted in a commercial block in network programming, the ad would still need to batter our way into our consciousness. With Kaila it succeeded once, hitting all the right emotional cues, and so her subconscious has been primed to respond to this ad should it appear on the radar screen of her constant scanning of her environment. In Kaila’s case, she would rush to the TV to change the channel, preventing her from dissolving into a messy puddle of tears.

Active Engagement

But by drawing our attention to the link, Kaila set up a totally different nature of engagement. She embedded the concept in our working memory by allowing us to create a goal around the viewing of the ad. We were engaged with the concept on a totally different level. Watching the ad was the goal, so no diversion of attention was required. We were primed to pay attention by Kaila’s recommendation. This is the power of ads that go viral in social networks, like Dove’s Evolution.

This concept of attention is at the center of two targeting tactics that have proven effective in the online environment: behavioral and contextual targeting.

Engaging Tactics

With behavioral targeting, we track behavioral cues through clickstreams, hoping that it will improve our odds of presenting our advertising message at exactly the right time to coincide with our target’s pursuit of a goal. The well-timed presentation of an ad for Chinese hotel rooms at almost the same time I was planning a trip to China was an example I’ve talked about before. Because planning for the trip had recently occupied my working memory and presumably I hadn’t yet reached my goal (the trip wasn’t completely planned yet), this message stood a pretty good chance of being engaged with (despite the fact that it creeped me out a little).

Contextual targeting employs a different but related strategy. If advertising messages are about the same topics as the content that I’m engaging with, transference of that engagement should be easier than with unrelated topics. Indeed, at Enquiro we’ve found that engagement with these ads actually occurs at two levels. There’s the initial awareness of the ad and the subsequent decision to engage with the ad. We’ve found that awareness is often higher with non-contextually targeted ads, but engagement and recall is higher with contextual ads. I have my theories about why this is so (having to do with the nature of the creative and the interplay of active consciousness and selective perception) but that could fill up an entire column in itself.

Engaging Search

Finally, we have search. In my previous examples of online targeting, we’re still using our best guess about optimum timing based on some pretty broad assumptions: click streams provide an accurate measure of intent, and interest in content means interest in related advertising messages. These targeting methods simply improve the odds in what is still essentially an interruption in the pursuit of a goal. But use of search is inherently aligned with goal pursuit. Information gathering is a key subtask in the pursuit of many goals, and search is an important tool in our information foraging arsenal. The goal is firmly embedded in our working memory and we’re on high alert for cues relevant to our end goal. This is why information scent in search results is so critical. No diversion of attention is required. Our attention is firmly focused on the results presented on the search page (both paid and algorithmic), because we believe that one of those results will take us one step closer to the goal.

This concept of active engagement is key to understanding search’s role in branding. Next week, I’ll look at how our cognitive mechanisms digest the results on a search page.

Picking and Choosing What We Pay Attention To

First published October 9, 2008 in Mediapost’s Search Insider

In a single day, you will be assaulted by hundreds of thousands of discrete bits of information. I’m writing this from a hotel room on the corner of 43rd and 8th in New York. Just a simple three-block walk down 8th Avenue will present me with hundreds bits of information: signs, posters, flyers, labels, brochures. By the time I go to sleep this evening, I will be exposed to over 3,000 advertising messages. Every second of our lives, we are immersed in a world of detail and distraction, all vying for our attention. Even the metaphors we use, such as “paying attention,” show that we consider attention a valuable commodity to be allocated wisely.

 

Lining Up for the Prefrontal Cortex

Couple this with the single-mindedness of the prefrontal cortex, home of our working memory. There, we work on one task at a time. We are creatures driven by a constant stack of goals and objectives. We pull our big goals out, one and a time, often break it into sub goals and tasks, and then pursue these with the selective engagement of the prefrontal cortex. The more demanding the task, the more we have to shut out the deluge of detail screaming for our attention.

Our minds have an amazingly effective filter that continually scans our environment, subconsciously monitoring all this detail, and then moving it into our attentive focus if our sub cortical alarm system determines we should give it conscious attention. So, as we daydream our way through our lives, we don’t unconsciously plow through pedestrians as they step in front of us. We’re jolted into conscious awareness until the crisis is dealt with, working memory is called into emergency duty, and then, post crisis, we have to try to pick up the thread of what we were doing before. This example shows that working memory is not a multi-tasker. It’s impossible to continue to mentally balance your check book while you’re trying to avoid smashing into the skateboarding teen who just careened off the side walk. Only one task at a time, thank you.

You Looked, but Did You See?

The power of our ability to focus and filter out extraneous detail is a constant source of amazement for me. We’ve done several engagement studies where we have captured physical interactions with an ad (tracked through an eye tracker) on a web page of several seconds in duration, then have participants swear there was no ad there. They looked at the ad, but their mind was somewhere else, quite literally. The extreme example of this can be found in an amusing experiment done by University of Illinois  cognitive psychologist  Daniel J. Simons and now enjoying viral fame through YouTube. Go ahead and check it out  before you read any further if you haven’t already seen it. (Count the number of times the white team passes the ball)

This selective perception is the door through which we choose to let the world into our conscious (did you see the Gorilla in the video? If not, go back and try again). And its door that advertisers have been trying to pry through for the past 200 years at least. We are almost never focused on advertising, so, in order for it to be effective, it has to convince us to divert our attention from what we’re currently doing. The strategies behind this diversion have become increasingly sophisticated. Advertising can play to our primal cues. A sexy woman is almost always guaranteed to divert a man’s attention. Advertising can throw a road block in front of our conscious objectives, forcing us to pass through them. TV ads work this way, literally bringing our stream of thought to a screeching halt and promising to pick it up again “right after these messages”. The hope is that there is enough engagement momentum for us to keep focused on the 30 second blurb for some product guaranteed to get our floors/teeth/shirts whiter.

Advertising’s Attempted Break-In

The point is, almost all advertising never enjoys the advantage of having working memory actively engaged in trying to understand its message. Every variation has to use subterfuge, emotion or sheer force to try to hammer its way into our consciousness. This need has led to the industry searching for a metric that attempts to measure the degree to which our working memory is on the job. In the industry, we call it engagement. The ARF defined engagement as “turning on a prospect to a brand idea enhanced by the surrounding media context.” Really, engagement is better described as smashing through the selective perception filter.

In a recent study, ARF acknowledged the importance of emotion as a powerful way to sneak past the guardhouse and into working memory. Perhaps more importantly, the study shows the power of emotion to ensure memories make it from short term to long term memory: “Emotion underlies engagement which affects memory of experience, thinking about the experience, and subsequent behavior.  Emotion is not a peripheral phenomenon but involves people completely.  Emotions have motivational properties, to the extent that people seek to maximize the experience of positive emotions and to minimize the experience of negative emotions.  Emotion is fundamental to engagement.  Emotion directs attention to the causally significant aspects of the experience, serves to encode and classify the ‘unusual’ (unexpected or novel) in memory, and promotes persisting rehearsal of the event-memory. In this way, thinking/feeling/memory articulates the experience to guide future behaviors.”

With this insight into the marketing mindset, honed by decades of hammering away at our prefrontal cortex, it’s little wonder why the marketing community has struggled with where search fits in the mix. Search plays by totally different neural rules. And that means its value as a branding tool also has to play by those same rules.  I’ll look at that next week.

Chrome’s Shiny, but is it enough to Break a Habit?

How ironic!

After going on at length about how Google’s competition is the victim of the search juggernaut’s ability to make searching Google a habit, now they’re running up against the same brick wall with the introduction of Chrome.

With the introduction of a new product that’s vital to future strategies, one has to account for cognitive lock in and habitual behavior. Let’s do a walk through of two examples.

Searching by habit

First of all, my Google analogy. Using Google as a search engine isn’t a conscious choice, it’s habit. We don’t think about it, we just do it. And because we don’t think about it, you can’t take a rational approach to convincing us to do otherwise. You have to disrupt the playing out of the habitual script. And you can’t just disrupt it once. You have to destroy the script completely and permanently.

So Microsoft’s Cashback scheme was doomed to failure from the beginning. It was a rational appeal based on Microsoft’s offering to pay you an incentive for using their search engine. It’s a fundamental human appeal and, on paper, appears to make sense. The problem is, sense isn’t really enough to change habits. Here’s what will happen. Someone will hear about the Cashback offer and may actually rationally suspend habitual behavior in order to try Live Search. Their autopilot will be switched off and they’ll consciously take over the controls. But we’re programmed to revert to autopilot in order to save energy. So unless the experience offered such a tremendous benefit that it’s worth our while to continue to rationally keep our hand on the controls, we’ll turn our attention (remember, attention is a one task at a time proposition, so we have to be very judicious about where we choose to spend it) to other things and go back to autopilot behavior. Cashback would have to blow away our previous search experiences, giving us a benefit worthy of investing the time to create a new habit. Cashback simply didn’t raise the bar enough.

What Goes Up will probably Come Down

So, with that psychological foundation, one could predict with a fair degree of confidence what would happen with the introduction of Cashback. There would be a temporary blip upwards in marketshare as the least loyal of Google’s habitual users consciously decided to give it a try, and then because the experience wasn’t a revolution in search, habitual behavior would take over and they would go back to Google. Marketshare would quickly return to previous levels. In fact, because there are a number of subtle psychological scripts built to help us maintain our habits (habits are a evolutionary advantage because they allow us to function with less cognitive effort) we might even become more frequent Google users and less frequent Live users. The bounceback could actually cause Live to lose marketshare.

Now, let’s look at what actually happened. The early summer introduction of Cashback seemed to be the answer to Live’s woes, as Compete’s Jeremy Crane was quick to point out.  Marketshare took a quick jump upwards. But two months later, Cashback’s initial glow is quickly fading. Search users are switching their auto pilots back on, and the default setting is Google.

Chrome Plated Strategies

Now, with the introduction of Chrome, Google is facing exactly the same challenge. They’re calculating that Chrome will have what it takes to break the Explorer or Firefox habit. And exactly the same pattern is emerging, as people take Chrome for a spin to decide whether it’s breaking-habit-worthy. And at this point, the answer seems to be no.

There’s one potential difference here. Chrome is much more than a browser. Google has a shiny future planned for the web app interface. If they raise the bar enough, people may make the investment required to break their existing habit and reform a new one around Google’s browser. But don’t expect any big marketshare shifts until that bar is raised.

Note to Cuil: Read My Columns!

Cuil was introduced when I had other things on my mind, namely trying to jam 2 months of work into 2 weeks so I could take my family on a long vacation to Europe. So I didn’t get a chance to caste my jaundiced eye on the much touted Google killer that has so resoundingly flopped since it’s introduction. That’s too bad, because I could have saved everyone a lot of time. I don’t care how “cuil” the technology is in the background, from a search user perspective, Cuil is a disaster!

For the past several months, I’ve been writing on MediaPost and Search Engine Land about inherent human behaviors and how they play out on search. I’ve talked about the limits of working memory, information foraging theory, how we pick up scent, how we navigate the results page, how we respond to images versus text, how we’ve been conditioned to search by habit and how what we read on the results page connects with our unexpressed intent in our minds. Cuil fails miserably on all counts. It frustrates the hell out of me that people don’t pay attention to the basic rules of human behavior. If the founders of Cuil had read our eye tracking reports, read Pirolli and Card’s information foraging theory, read any of my posts or blogs or read any post by Bryan or Jeffrey Eisenberg or Jakob Nielsen, millions of dollars of VC funding, thousands of hours of development time and a lot of actual and virtual ink could have been saved. Unless Cuil completely revamps their interface, they’re doomed to failure.

Cuil completely disregards the conditioned patterns we use to navigate results pages. This is a risk, but an acceptable one. You can change things up, but you better damn well deliver when you do. All Cuil delivers is confusion. It’s almost impossible to pick up scent. The eye is dragged all over the page because there’s no logical presentation. Functionality is ambiguous, not intuitive. The mix of images and text does nothing to establish relevance. Perceived relevance of the SERP is nil. If I would have looked at this a few months ago, I would have predicted that users would try it once because of the hype, been mildly intrigued by the look but found it almost unusable, quickly beating a path back to Google. I didn’t need to do eye tracking. A quick glance at the results page was all I needed. Unfortunately, because my mind was on the French Alps rather than the latest Google killer, my first glance was 3 months delayed and my would-be brilliant prediction just sounds like “me-too” hindsight.

Ah well..

For others that have Google in their sights, a word of advice. Mix up the search business..shake the hell out of it. It’s time. Come up with a better algorithm, blow up the results page and see where it lands, jolt the user out of their conditioned behavior. By all means, take millions in eager VC capital and reinvent the game. It’s way past time. But please, don’t ignore the fact that humans are humans and there will always be certain rules of thumb and strategies we operate by. You can destroy the paradigm, but you can’t change generations of inherent behavior. Cuil never bothered to learn the rules. That’s going to cost them.

Emotion and the Formation of Brand Memories

First published August 21, 2008 in Mediapost’s Search Insider

In my last column, I looked at how beliefs can affix labels to brands, which forever after form our first brand impression. Beliefs are a heuristic shortcut we use to reduce the amount of sheer thinking we have to do to come to quick and efficient decisions. Today, I’d like to focus on emotions and their part in the forming of memories.

Why “Selfish Genes” Remember

First, from an evolutionary perspective, it might be helpful to cover off why humans are able to form memories in the first place. To borrow Richard Dawkins’ wording, memories are here to ensure that our “selfish genes” are passed on to future generations. While memories are incredibly complex and wonderful things, their reason for being is mindlessly simple. Memories are here to ensure that we survive long enough to procreate. This is why emotion plays such a huge role in how memories are formed and retrieved.

Researchers have long known that emotions “tag” memories, making their retrieval easier and the resulting effect more powerful. In fact, very strong emotions, such as fear or anger, get stored not just in our cortical areas but also get an “emergency” version stored in the limbic system to allow us to respond quickly and viscerally to threatening situations. When this goes wrong, it can lead to phobic behavior. Emotions add power and urgency to memories, moving them up the priority queue and causing us to act on them both subconsciously and consciously. The very meaning of the word emotion comes from the latin “emovere” — to move.

Driven by Emotions

Emotional tagging works equally well for positive memories. Our positive emotions are generally affixed to three of the four human drives identified by Nohria and Lawrence: the drive to bond, the drive to acquire and the drive to learn. For the selfish gene, each of these drives has its evolutionary purpose. We have the strongest positive emotions around the things that further these drives the most. We reserve our strongest “bonding” emotions for those that play the biggest part in ensuring our genetic survival: partners, parents, children and siblings. In some cases we share a significant portion of our genetic material; at other times, the complex sexual wiring we come with kicks into gear.

If we look at the drives to acquire or to learn, millions of pages have been written trying to decode human behavior in pursuit of these goals. For the purpose of this column, it will have to suffice to say that markets have long known about the power of these drives in shaping human behavior and have tried every way possible to tap into their ability to move us to action, usually through consumption of a product.

In summary, we reserve our strongest emotions for those things that are most aligned with the mindless purpose of the selfish gene, passing along our DNA. These emotions tag relevant memories, giving them the power to move us to immediate action. Perceived threats trigger negative memories and avoidance or confrontation, while positive memories drive us to pursue pleasurable ends.

Brand + Emotion = Power

This emotional tagging of memories can have a huge impact on our brand relationships, in both positive and negative ways. While I’ve painted a very simplistic picture of the primary objective of emotions and memories (and the heart of it is simple), the culture we have created is anything but. Memories and emotions play out in complex and surprising ways, especially when we interact with brands.

Brand advertisers have become quite adept at pushing our evolutionary hot buttons, trying to tag the right emotions to their respective memories. Their goal is to affix a particularly strong emotion (either negative, referred to in marketing parlance as prevention, or positive, which we’ve labeled promotion) to their particular brand construct so that when the memories that make up that construct are retrieved (along with the attached beliefs and brand label) they are powered with the turbo-charge that comes with emotion. If the marketer is successful in doing this, they have unleashed a powerful force.

When emotions play a role, our motivation comes not just from rational decisions, but a much more primal and powerful force that sits at the core of our subconscious brain. The most successful brands have managed to forge these emotional connections. And when the emotions remain consistent for a particular brand, there are coalesced into a strong brand belief that is almost unshakable once formed. This is why your father buys nothing but Fords, Mac fans wouldn’t be caught dead with a plain grey laptop ,or coffee connoisseurs swear that Starbucks is worth the price.

Next week, I’ll give you one particularly interesting example of how one brand belief and its corresponding emotions developed, in a fascinating study from the emerging world of neuromarketing.

Brand Labeling: Building Our Beliefs

First published August 14, 2008 in Mediapost’s Search Insider

Up to now in this series on search and branding, I’ve been looking exclusively at how and why we use search engines. But the idea of the series is to show how branding and search can work together. So in this column, I’d like to start from the opposite end of the spectrum: our brand relationships, from a memory retrieval perspective.

Storing Complex Concepts

In the computational theory of mind, the prevailing theory that seems to best explain how our minds work (although it’s not without its detractors), the elegance with which the brain processes complex patterns of information is remarkable. These are called constructs, and brands are no exception.

For any complex concept, the components of the concept are individual and scattered memory patterns, called engrams. Engrams are groups of activated neurons that fire together. But the more complex the concept, the greater the network of engrams. For a person we know well, like our mother, we could have a huge number of scattered components that make up our concept. Snatches of memories, what her voice sounds like, what she looks like, what her banana loaf tastes like. All these, and many more, individual memory components make up our concept of “mother.” And these fragments are stored in various parts of the brain. When we remember what our mother looks like, it’s an engram in our visual cortex that fires, the same part of the brain that fires when we’re actually looking at her. We’re actually picturing her in our mind. When we hear her voice, it comes from our auditory warehouse.

Our Neuronal Warehouse

The concept of a vast neuronal warehouse is actually a good analogy. When we call up our concept of “mother,” it’s assembled on the fly from the individual sections of the warehouse. The retrieval call goes out, depending on the need, to the various parts of the brain, and the required components are brought together in our working memory and assembled in the conscious part of our brain. Each memory is custom made from available parts. If we were looking at a model of the brain, we’d see maps of neurons “lighting up” across the cortex, almost like a lightning storm seen from above the clouds.

But with a construct as complex and extensive in scope as our mother, there needs to be a shorthand version. We can’t retrieve every single piece of “mother” every time we think of her.  So, the parts retrieved are restricted to the context we do the retrieval in. If we’re buying a dress for our mom, we retrieve components that include her body shape, her color preference and probably memories of other things she’s worn in the past. We don’t retrieve her banana loaf recipe because it’s not relevant.

Executive Summaries of Memories

But there’s also a labeling process that goes on. For complex constructs, like our mother or a familiar brand, we need a quick and accessible “label” that sums up our feelings about the entire construct. This is the top of mind impression of the construct, the first thing that comes to mind. It helps us keep the world straight by providing a shorthand reference for the many, many constructs stored in our memory warehouse. These labels have to be simple. In the case of people, the summing up usually determines whether we like or dislike the person. It’s a heuristic shortcut that is built up from the sum of our experience and exposure which determines whether we’re willing to invest more time in the person. The same is often true of brands.

The power of these labels for brands is absolutely essential, because they determine our attitudes to everything that makes up the construct. The brand label, or belief, is a gut feeling that impacts every feeling or attitude towards the brand.

Top-of-Mind Brand Beliefs

Often when I’m speaking, I’ll do a little exercise where I’ll show well-known brand labels and ask people to write down the first thing that comes to mind when they see it. What I’m capturing is the brand label, the top-of-mind belief about the brand. Apple generally brings out labels like “cool,” “cutting edge” or “design.” Starbucks is labeled “indulgence,” “great smell,” “delicious” or, less positively, “overpriced.” The entire scope of our experience with the brand is labeled with a few words. Obviously, our entire concept of Starbucks is usually much greater than just the way it smells or tastes, but for the people that have assigned it this label, that’s the best overall descriptor and the easiest access point. The rest of the details that make up our concept of Starbucks can be unpacked at will, but for these people, they’re all packed in a box that is labeled with “great smell” or “delicious.” If the label is “overpriced,” this may be a box we seldom unpack.

Next week, we’ll continue to look at how we store our concepts of brands, what can make up our brand constructs and the role emotion plays.

Needs, Beliefs and Search

First published August 7, 2008 in Mediapost’s Search Insider

In the last few weeks, I’ve looked at how we gather information, depending on how complete the information is we already have. But it’s not just information that colors the search interaction. Like all human interactions, we are governed by our desires, our objectives and our beliefs, and this is certainly true in search.

Computing Concepts

Steven Pinker is one of the foremost proponents of a computational theory of mind. Following in the footsteps of Alan Newell, Alan Turing, Herbert Simon   and  Marvin Minsky,  Pinker argues that our “minds” lie within the patterns of information processing and functionality founds in the specialized modules of our brains. Like a software program being executed step by step, our minds break down the incredibly complex concepts we are faced with each day and feed them through these patterns. We create objectives that get us closer to our desires, and in order to get there in the most efficient way possible, we depend on a vast library of heuristic shortcuts that include our beliefs. We don’t think everything to death. We make quick decisions and create short cuts based on existing beliefs. Simon called this  bounded rationality.

Irrational Short Cuts

The challenge with these short cuts, as  Amos Tversky,  Daniel Kahneman, and more recently,  Dan Ariely, have discovered, is that they’re often quite irrational. Our beliefs are often driven by inherent patterns that have evolved over thousands of years. While they may be triggered by information at hand, the beliefs lie within, formed from a strange brew of inherent drivers, cultural influences and personal experience. In this brew, it’s almost impossible to see where one belief shaper begins and another leaves off. Our beliefs are largely formed in our vast mental sub-cortical and subterranean basement, below the hard white light of rational thought. But, once formed, beliefs are incredibly stubborn. Because we rely on beliefs to save our cognitive horsepower, we have an evolutionary interest in keeping them rigidly in place. Heuristic shortcuts don’t work very well if they’re based on ever-changing rules.

And there you have the crux of marketing. Every time we’re presented with a symbol that represents a concept, whether it be a word, a picture, a sound or a logo, it unlocks a mental concept complete with corresponding beliefs. Unless it’s a brand we’ve never heard of before (in itself a significant marketing challenge), that brand comes with corresponding belief luggage, some of it undoubtedly highly irrational. We are built to quickly categorize every new presentation of information into existing belief filing cabinets or “schemas.” The contents of those filing cabinets are difficult to explore, because they exist at a subconscious level. Consultants such as  Gerald Zaltman and  Clotaire Rappaille have carved out lucrative careers by creating methods to unlock the subconscious codes that lie behind brands.

Search and Our Subconscious Baggage

So, when we interact with a search engine, it’s important to understand that this is not entering new information onto a blank canvas. Each word (or now, image) on a search page has the potential to trigger an existing concept. This is especially true for the appearance of brands on a page. Brands are neat little labels that can sum up huge bundles of beliefs.

It’s actually amazing to consider how quickly we can filter through the degree of information presented on a search page. We quickly slice away the irrelevant and the items that don’t fit within our existing belief schemas.

It’s not just the information on the page that we have to filter through. It’s all the corresponding baggage that it unlocks within us. Somehow, through the power of our subconscious mind, we can scan 4 or 5 listings, let the words we scan trigger corresponding concepts in our minds, quickly evaluate which listing is most likely to get us closer to our objective (based on beliefs, aligned with our desire) and click, all within a few seconds.

This simple act of using a search engine is actually a very impressive and intricate cognitive ballet using the power of our conscious and subconscious minds.

Search Behavior: I Don’t Know What I Want, or Where to Find It

First published July 31, 2008 in Mediapost’s Search Insider

In my last two columns, I looked at how search plays a part when we’re in two information gathering states: I know what I’m looking for and where to find it; and, I know what I’m looking for but not where to find it. Today, I’ll look at what happens when we don’t know what we’re looking for or where to find it.

In the first two states, our intent is pretty well defined. We’re looking for a piece of a puzzle and we know the shape of that piece when we see it. In information-foraging terms, we’ve already defined our diet. It’s just a question of which patch we look in. When we extend that to search engine usage, we have already defined our query, and it’s just a question of how we interact with the results page. In both these states, search engines work pretty well.

The Missing Puzzle Piece

But what if we have no idea what the puzzle piece looks like. We don’t know the shape, we haven’t assembled the adjacent pieces and we only have some vague idea what the finished picture should look like. This is the ultimate challenge for online search, and one that all search engines have largely failed to meet until this point. This is where we need a guide and advisor, a connector between ourselves and the universe of potential knowledge available. Because our knowledge is imperfect, we need a sage whose knowledge is perfect — or, at least, much less imperfect than our own.

Of Disambiguation, Discovery and Berrypicking

This is where three concepts play an important role: the need to disambiguate, the thrill of discovery, and a revisit of Marcia Bates’ concept of berrypicking. Let’s begin with disambiguation.

When we have no idea what we’re looking for, we don’t know how to define it. We don’t know the right query to present to the search engine. The more imperfect our knowledge, the more ambiguous our query. This is where search needs better knowledge of who we are. It needs to know — through implicit signals such as our areas of interest, our past history and our social connections –what it is we might be searching for. If a search engine is successful in lending more definition to our query, it stands a chance of connecting us to the right information.

The second piece is discovery. If a search engine is successful in introducing potentially relevant information to us, our interaction is quite a bit different than it is in the first two information gathering states. We spend more time in our interaction and “graze” the page more. We’re also open to more types of content. In the first state (know what we want and where to find it) we’re just looking for the fastest navigation route. In the second state (know what we want but not where to find it) we’re looking for confirmation of information scent to judge the quality of the patch. But in the third state, we could be enticed by a website, an image, a news story, a video or a product listing. We’re pretty much open to discovering anything.

And this brings us back to Bates’ theory of berrypicking. Because we have no preset criteria for the type of information we’re looking for, we can change direction on the turn of a dime. In our pursuit, we fill in the definition of our prey as we go. We follow new leads, change our information-gathering strategies and sometimes completely change direction. Our interactions with search turn into a serendipitous journey of discovery. It is in the third state where our patience is generally higher and our scanning pattern the broadest. Any cues on the page that trigger potential areas of interest for us, including brands or cultural references, could catch our attention and lead us down a new path.

Search Pursues Discovery

It’s this type of search that Ask’s 3D interface or Google’s Universal results set was built for. It’s also the thorny problem of disambiguation that has spawned a number of approaches, from Google’s exploration of personalization to the human assisted approaches of ChaCha and Mahalo . Even Yahoo’s Answers is a discovery tool, using the more natural approach of question and answer to lend some definition to our information quest. But even though we are defining our criteria as we go, we still seek to conserve cognitive energy. We have a little more patience in our seeking of information scent, but just a little. We still spend seconds rather than minutes looking for it, and because search is still trying to get discovery right, our sense of frustration can mount rapidly. We’re still a long way from finding a universally satisfying online source for discovery.

Search Behavior: I Know What I Want, But Not Where to Find It

First published July 24, 2008 in Mediapost’s Search Insider

Last week I looked at search behaviors when we knew what we were looking for and where to find it (http://www.mediapost.com/blogs/search_insider/?p=832). This week we’ll look at what happens when you know what you’re looking for — but you’re not sure where to find it.

Judging a Patch By its Scent

In the first instance, when you know what you’re looking for and where to find it, you have defined your patch and you have a pretty good idea what route to take to find your specific piece of information. In the second instance, you don’t know in which patch you’ll find the piece of information. This is where classic way-finding behaviors and information scent can play a critical role in seeking information.

When you’re not sure which information patch contains the right information, you have to judge each patch by its relative “scent.” This pretty much guarantees you’ll visit more than one patch, which for our purposes translates to Web sites. You’ll try to do a preliminary assessment of scent based on what you see on the results page, but you’ll reserve most of your judgment for when you click through to the site.

Looking for Greener Grass

One of the interesting aspects of optimal foraging for food is that there are costs to move from patch to patch. You have to literally assess whether the grass is truly greener on the other side of the fence, or whether it would just be a senseless waste of effort. Most animals have a highly developed heuristic instinct about when the time is right to move on to the next patch. Biologist Eric Charnov, who reached out to me (I’m still following up with Eric to get a follow-up interview for a future column) after my original information-foraging column, called it the  Marginal Value Theorem. In a nutshell, Charnov’s Theorem says that we decide how long to stay in a patch based on how rich the current patch is and how distant the next patch is.

One of the challenges of the Marginal Value Theorem is that we often have no way of knowing what the “richness” of the next patch might be until we commit to expending the energy to go see it. We risk the effort based on our assessment of the current patch and the hope that better patches lie ahead. And the risk lies in the fact that it takes energy to move from patch to patch. The degree of risk lies in the distance to the next patch, our expectation of the richness of that patch and the value of the patch we’re currently in.

Patch Hopping with Search

But online, the Internet is non-dimensional in the traditional sense. There is no distance; the only dimension is time. How much time are we willing to expend to find the next patch? And search gives us the ability to greatly reduce the time needed to navigate from patch to patch. We structure queries to define the “diet” we hope to find in each patch. We then can click through to see if the scent matches our definition of diet.

Remember, time is the resource we hope to conserve, so these explorations from the search page are very quick. We can visit a number of patches in seconds. We define the diet (what we’re looking for) and start down the page visiting the most promising patches. Based on user research we’ve done at Enquiro, searchers typically take 10 to 12 seconds for the first click from the search results page, and spend about 15 seconds assessing the scent on the pages they visit.

Because we are programmed to save effort, if we visit a few patches and come up short, we’ll use a new query to define a new collection of patches. Because we have no defined notion of which patch will be the right one, we have to use shortcuts to judge each patch quickly and efficiently. We have little patience for unpromising patches.

Of course, our level of patience is also determined by how rare the prey is we’re pursuing. If we believe it should be rather plentiful, we also believe the scent should be easy to pick up. But if our prey is elusive, we’ll be more patient in our quest to pick up its scent. Those are the searches that will drive us to the second or third page of results.

We Don’t Consume Information

If we find a rich patch, we file it away for future consideration. This is another area where information foraging diverges from biological foraging. Looking for food is a zero-sum game. If we don’t eat the food we find, someone else will. So when we find a rich patch, we stay put until we eat as much as we can (or until a richer patch beckons).

But online, information is not really consumed. Even if we use it, it’s still there for the next visitor. There’s no risk to move on and find other information patches. This is where traditional way-finding strategies come in. As we explore for information, we define the landscape based on the richest information patches. These become landmarks which we return to again and again. So we quickly use search to define the best patches and tag them for future reference. Then, we return to them at our leisure, knowing the information will still be there, waiting for us.

Next week, we’ll looking at the third state of information-seeking — where we don’t know what we’re looking for or where to find it — and how this impacts our search behavior.

 

Search Behavior: I Know Just What I’m Looking For

First published July 17, 2008 in Mediapost’s Search Insider

We seek information to fill gaps in our existing knowledge. The extent of that current knowledge and how we’ve structured it will play a large part in determining intent. It will help shape our knowledge requirements, our strategies for retrieval and how we will evaluate information scent. As stated in my previous two columns, we’re generally in one of three states when we turn online for information; we know what we’re looking for and where to find it; we know what we’re looking for, but not where to find it; or, we don’t know what we’re looking for or where to find it. Today, I want to explore intent in the first of these states:

We Know What We’re Looking For — and Where to Find It

In the first case, we have a solid idea of the information we’re looking for. Our mental representation has a defined structure and we have a good idea of what the missing piece looks like. For example, we’re looking for a phone number, an address or another missing detail. Because the structure of the information in our minds is almost complete, we have a similarly clear cut idea of where we’re most likely to find the information. We know the right “patch” to look in and where to find the information in the “patch.” In this case, we’re looking for the simplest route from point A to point B.

Googling Google on Google

One of the ongoing anomalies in search is the number of people who go to their favorite engine to search for proper domain names. Some of the most popular queries on every engine are the URLs of their competitors. People search for Yahoo.com on Live Search, or Google.com on Yahoo. People even search for Google on Google. In looking at the query logs, the only explanation seems to be mass stupidity. But in actual fact, this is foraging playing itself out. We habitually use engines to navigate the Web, so even when we know the Web site, why should our behavior be any different? (This still doesn’t explain the searching for Google on Google. Perhaps stupidity is the right answer here.)

Let’s say you’re looking for the address of the head office for a corporation. You know it will be on their site somewhere, and you have a pretty good idea it will be somewhere within the “about us” section. Rather than go directly to the site and navigate through it, you choose to search for “Company X head office address.” Or, even more likely, you just search for “Company X,” knowing that the official site will come up high in the results.

Pre-Mapping the Search Results Page

In this case, before the results page even loads, you know exactly what you’re looking for and where you’re likely to find it. If you’re searching on Google, it’s likely that you’ll get an extended result in the number one organic spot with Site Links to key parts of the site. This is a great match for your expected information scent. Previous to this introduction by Google, we saw that for navigational searches where we knew the destination we were looking for, there was a higher degree of scanning of the site URL at the bottom of the result listing. Normally there’s not much interaction with this part of the listing.

In this first category, we look at search as a tool, the quickest possible route to the information we know exists. We will quickly zero in on the only relevant information on the results page, the listing for the site we’re looking for. Now, the question for marketers is, what happens when there’s both an organic and sponsored listing for the same site on the same page? Will one cannibalize the other? While we’ve never tested for this specific intent, I can speculate based on what we’ve seen in other research.

Habitual Scanning Behaviors

In one study, we split our group in half, giving one a purchase-type task and the other an information-gathering task. In both cases, we looked at scan patterns in the top sponsored and organic results. We expected to see our information-gathering group relocate their scanning down to the organic results. But this didn’t happen. What we realized is that we scan the search page out of habit. We’re not rationally optimizing our scan path based on intent. We’re following the same pattern we always do, the top to bottom, left to right, F-shaped pattern that’s common across all users. That behavior is conditioned and engrained. It’s been etched at the sub-cortical level of our brain in our basal ganglia and executes subconsciously (see Ann Graybiel’s work  on this for more). But what does change is how we respond to the information scent cues on the page.

Although scanning followed the same pattern for both groups (in fact, the interaction was even higher with sponsored listings for the information-gathering group, likely because they weren’t exactly sure what they were looking for and so were in a more deliberate mode) the click patterns were significantly different. The official site that marked the successful destination in the scenario was in both the top organic and sponsored location. In the commercial task, the clicks split almost 50/50, with half happening in the sponsored listings, and half in the organic listings. But in the information-gathering group, all the clicks happened in the organic listing. Based on our preconceived idea of the information we were seeking, that particular “patch” seemed more promising.

Next column, we’ll look at intent and how it impacts search behavior when we know what we’re looking for, but not where to find it.