Category Archives: Information Seeking & Foraging

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.

 

Foraging for Information with Search

First published July 10, 2008 in Mediapost’s Search Insider

In my last column, we looked at berrypicking as an analogy for gathering information. The theory was put forward in 1989 by Marcia Bates. Then, in 1995, two researchers found even more inherent behaviors demonstrated in the way we seek information. It turns out that we may literally hunt for information.

The Genetic Case for Searching

We didn’t come equipped with an inherent strategy to pull information from a Web search results page. There is no genetic coding specific to Google. But as two researchers at Xerox’s PARC research facility, Peter Pirolli and Stuart Card, really started to explore how humans navigated online environments looking for information in 1995, they found something fascinating. They found that the way we seek information online is very similar to an activity that is as old as evolution itself: the hunt for food. Pirolli and Card called this the information foraging theory.

The basic principle behind information foraging is not so much about gathering the maximum amount of information, but rather in maximizing our time and efforts in pursuit of the right information. This goes to the human knack for conserving our resources in pursuit of our objectives.

The Easiest Route to Information

We must remember that any interaction with a search engine is part of a much broader range of activity that will hopefully result in achieving a large objective that is aligned with a human drive: learning, bonding, acquiring or defending (Nohria/Lawrence ). We take these macro objectives and break them up into distinct tasks and allocate resources against those tasks based on the expected usefulness of the outcome. This is where the food-gathering analogy provides some useful perspective.

We eat food to survive. Food is the fuel that powers our activities. In the stripped-down logic of evolutionary survival, it doesn’t make sense to expend more energy in the pursuit of food than the food itself contains. We would starve and die. So we have become remarkably effective at finding food in the easiest way possible. The big objective of the pursuit of food and survival is broken down into discrete tasks or actions, and we instinctively determine how much time and effort to spend on each of these tasks or actions depending on how much closer it will get us to the objective: our next meal. There is a cascading series of risk/reward decisions and mental trade offs happening below the level of our rational awareness. Our evolutionary programs play themselves out subconsciously.

Born Foragers

While seeking information is a more abstract concept than finding food, Pirolli and Card argue that the same inherent skills are used, including the same trade-off decisions. In evolutionary terms, our information-seeking skills are an adaptation of our food-gathering skills. Each time we seek information, we “hunt” for it and make decisions about how much cognitive energy we want to expend in the pursuit and the optimum strategy for gathering the information. We forage for information.

This explains much of the typical behavior we see with online properties, especially search. We quickly seek and filter through information, using our heuristic guidelines and trade-offs.

And when we look at our use of search engines, there are two important concepts put forward by Pirolli and Card that must be considered: the importance of information patches and diets.

The Right Patch and The Right Diet

As we seek information, the same as seeking food, we will spend our time where the promise of successful pursuit is the greatest, based on clues or telltale hints we encounter. We look for the best information “patch,” which is determined by information “scent,” the smell of informational relevance. The greater the scent, the greater the promise of an abundant information patch.

Search engines give us the ability to create our own patches, somewhat like a spider spinning a web to catch prey. We see what we catch based on the scent, and if we don’t like what we see, we quickly spin another web with another query. There is almost no effort expended in the process, so we have little patience if we’re not presented with adequate scent. This is why so much time is spent scanning the top of the page. I call it the area of greatest promise, that tiny yet critical patch of real estate in the extreme upper left corner of the search page, where we expect the strongest scent, figuratively. We judge the value of the whole patch based on what we see in the first few words in the first few listings on the page. If we don’t find strong scent, we start questioning the value of the patch.

But we also have to make a determination of which information we include in our diet. Remember, it makes no evolutionary sense (assuming we’re using the same mechanisms we use for foraging food) to expend energy pursing food that doesn’t return an equal or greater return on our investment. So we will quickly filter out low-quality information. In fact, if we think a patch contains only low-quality information, we’ll exclude it from our diet.

Search has been remarkably successful in becoming the preferred “patch” for a diverse set of information needs, but it still comes up short in one particular category. It doesn’t do very well at helping us find information when we don’t have a clear idea of what we’re looking for. Search is still rather ineffective as a “discovery” engine. But despite its limitations in this area, we have still been increasingly conditioned to turn to search when we forage for information because of its remarkable efficiency.

Berrypicking Your Way through the Web

First published July 3, 2008 in Mediapost’s Search Insider

In the last three columns, I explored the fundamentals of humans seeking information. To refresh your memory, the purpose of this series is to explore the importance of branding on the search page. Taking several steps back to begin my run at this topic (and risking a series that is “long and extremely wind baggy,” in the words of one reader), we’re now starting to get at some of the important concepts to understand how we interact with a search results page.

Bates and Berrypicking

In 1989, Marcia Bates took a fresh look   at the classic model of information retrieval that had dominated for the previous 25 years. The model was a fairly straight equation, with on one side a collection of documents and how the contents of those documents were represented, and the seeker’s information need and the query they constructed to express that need on the other side. In the middle was the desired outcome, the match of query and document representation. Bates found this admirably simple equation didn’t hold up too well in real-world search situations, especially given the advances in information technology.

The problem with the classic model was that it assumed that the successful search for information was a relatively static event, where one search and retrieval strategy took you eventually to the desired information. Even if you took into account feedback and iterative query refinement, it still looked at the process as a continual and linear one, with incremental progress towards a constant goal. In looking at actual behavior, Bates found that the process was more complex. As we pursued the information we thought we wanted, she found the path was less a straight line and more a looping and meandering path. In fact, it reminded her of picking huckleberries, hence the title of her theory, berrypicking.

Meandering through the Web

Bates found that as we start down the path to the information we seek, we pick up bits of information a little at a time, like picking berries. What’s more, as we pick the berries, we may head off in different directions depending on the information we gather. We follow the berries to more promising clusters of berries, or “patches.” We don’t just refine our queries, we change search and retrieval strategies, the places where we think we’ll find information (our “patches”) and, in the more extreme cases, our ultimate destination. Search is an evolving behavior, not a linear one.

Bates looked at 6 different strategies that academics use to search for information: footnote chasing (backwards chaining from articles of reference, tracking back footnotes); citation searching (forward chaining, using a citation index to jump forward); journal run (using authoritative journals on a subject and going through the entire run); area scanning (using the physical location of a subject in a library on the assumption that relevant materials will be in the same location); abstracting and indexing searches (using organized bibliographies and indexes, usually arranged by subject area); and author searching. At the time of her paper (1989), Web search was still unknown. The first search engine (Archie) would be created in 1990 at McGill University. But as you look at the six methods outlined, it’s clear that Web search lets you do any and all of them.

The Web: The Ultimate Berry Patch

Bates theorized that berrypicking would play out in different environments and you would change strategies as you went from environment to environment. The timeline could be days, weeks or even months. But with the Web and search, you could go from strategy to strategy in seconds, berrypicking your way through the Web. What’s more, you could be diverted from your original path through a serendipitous display of information that catches your attention. For example, you could be footnote chasing (i.e., the source link for a snippet of a review on one page) which leads you to launch a search for other reviews. There you see results for a magazine dedicated to the topic (an example of journal run), a link for other consumer reviews (citation searching) and a book title written by an authority on the subject (author searching). You’ve just used all six of the strategies outlined by Bates in one session, as you used abstracting and indexing (this is ultimately what a search engine is) and area scanning (in this case the physical collocation is defined by the search page real estate).

When it comes to the impact of branding on search, it’s important to understand Bate’s berrypicking model. Any search result could represent a “berry” that could lead us to an entirely new patch. Our search path could evolve in a totally new direction based on what we pick from a page. We can be introduced to brands or have them reinforced as we berrypick our way along.

In the next column, we’ll continue to redefine information retrieval by looking at the Information Foraging theory.

The Quest for Information

First published June 26, 2008 in Mediapost’s Search Insider

The third in my series in looking at how we search and how it might impact our brand relationships. Today, I look at how the emergence of Web search marks a dramatic leap forward in our quest for information.

The Great Library of Alexandria, built in 300 BC, was designed to hold all the knowledge of man. The dream of Ptolemy II was to assemble all the scrolls of the world in one place. Last week we explored why we sought knowledge. The Ptolemaic library was the first attempt to create one single repository for that information. Unfortunately, the media for recording knowledge was papyrus, which proved to be unpredictably flammable. The library burned not once but several times.

One of the challenges of seeking information is that it tends to be spread out and difficult to access. As we saw last week, when we seek information, we tend to either know what it is and where to get it, know what it is but not where it is, or, most challengingly, we don’t even know what it is we’re looking for.

Organizing the World’s Information

Google’s quest, picking up where Ptolemy left off, was to organize the world’s information. This is the big hairy audacious goal of all big hairy audacious goals. It’s never been accomplished before in the history of man. But Google is betting that it can be done thanks to the migration of information to a digital format.

In seeking information, humans will take the path of least resistance. This is not to say humans are inherently lazy. Like many things that come from evolutionary psychology, we have a tendency to reduce human behaviors to overly simplified maxims — and the inherent laziness of humans is one such oversimplification. It is true, however, than humans are inherently thrifty with our energy expenditures. Harvard professors Paul R. Lawrence and Nitin Nohria, in their book “Driven: How Human Nature Shapes our Choices,” theorize that humans are driven by four basic drives: The drive to acquire, the drive to bond, the drive to learn and the drive to defend. As we pursue these drives, we constantly balance effort vs. rewards. We will pursue the things important to us, but we will generally find the easiest means to our ends. This is particularly true of intellectual effort, where many cognitive short cuts are prewired and are triggered without our conscious awareness.

The Irresistible Lure of Web Search

This is why search has become such a  fundamental human activity. The aggregation of information that sits just a few keystrokes away is a tremendously engaging prospect for us energy-efficient humans. We will take the easiest path to retrieve the information and do it in a brutally efficient way. Search interfaces have to be intuitive and sparse. The more complicated the task, the less attractive it is to us. This is why search tools that ask us to do any more than type in the bare minimum of keywords will ultimately fail if there’s an easier choice. And this is why Google has become a habit for us.

But what about intent? Different types of searches may require different interfaces and treatment of results. Again, we make expenditure/reward calculations at an instinctive level based on our experience and knowledge. We decide which actions will be most likely to yield the information we seek. As you explore human nature, one of the most striking discoveries is just how sophisticated our subconscious energy conservation mechanisms are. Habits, emotions, instincts and other non-rational drivers guide us to make split-second decisions that should provide the best results with the least effort, and they are usually remarkably accurate. They have been field-tested and encoded into our genes by natural selection for generation after generation.

Picking the Right Path to Information

There’s another factor at play here, our level of confidence that past behaviors will continue to yield satisfactory results in the future. And this is part of a largely subconscious decision process when we chose the path to the information we seek.

Remember, when we seek information, we fit into one of three categories: we know what we’re looking for and where to find it, we know what we’re looking for but don’t know where to find it, or we don’t know what we’re looking for or where to find it.

Search engines fit the first two categories quite nicely. The first category leads to the huge volume of navigational search we see online, where we’re looking at search to connect us to the right page on the right site. And the second category gives us the more typical search behavior, where we tell the engine what we’re looking for and it provides it suggestions of the best place to find it.

It’s the third category where search engines struggle. When we don’t know what we’re looking for or where to find it, it’s difficult to find the words for our query. It’s in this category where search engines are trying to break new ground, by becoming discovery engines.

So, how has evolution equipped us to look for information? In the next column, I’ll look at information foraging, information scent and berry picking.

Why Do We Search?

First published June 19, 2008 in Mediapost’s Search Insider

This is the second in a series exploring the question of how we interact with search pages and the impact on brand relationships. Today we look at why we search in the first place.

Let’s begin with perhaps the most fundamental question ever asked in this industry. Why do we search? I’ve been in this industry for over 12 years now, and I’m not sure I’ve ever heard an answer to it. Why do we seek information? Is this need cultural or inherited? Is how we seek information changing?

 

The Roots of Curiosity

We search because we are curious. And curiosity comes from chaos. Curiosity allows us to survive in a dynamic and unstable environment. The more things change, the greater our curiosity. It keeps us alert and looking for the knowledge we need to survive. So the drive to be curious is inherited, but the degree of curiosity is cultural. Our environment determines how curious we are. If nothing changed, we wouldn’t need curiosity. So it’s probably not coincidental that for some of us, curiosity declines as we age. We seek more stable environments. Our need to monitor and adapt to our environment decreases, and with it, our need to learn.

We seek information for many reasons. Remember, almost every action we take is driven by emotion, but there is usually a rational justification that accompanies it. Our emotions and our reason work together to pick the best possible path for us. Antonio Damasio has done extensive research in this area, referring to our emotional cues, our gut instincts, as “somatic markers.” Rational thought needs information, and information, in turn, feeds our emotions. Information is essential grist for our curiosity mill.

Essential Information

Information is key in everything we do. Either we have this information stored in our brains–allowing us to conduct the task in question or function normally–or we don’t, causing us to seek it. The problem in seeking information is not one of quantity, it’s one of quality. There has never been more information available, but it can be difficult finding the right information. In our culture, a huge part of our cognitive effort is spent filtering out the onslaught of information that bombards us every day. No culture in history has been surrounded by more information than our present one, and it’s expanding exponentially.

Sometimes our need for information is purely rational. We need information to complete a task (looking up a phone number, referring to a map, reading directions) or to learn something new. Sometimes our need for information is less clear-cut, tied in with the social machinations that make us human. Remember, gossip is a glue that binds our society, and gossip is nothing more than the gathering and sharing of personal information. So our information-seeking is often tied to an incredibly complex concept of social structure and status. Sometimes we seek information because we need it. Sometimes we seek information just because we want it. Information is a valuable currency in our society, and it can be one factor in determining social status. Obviously, the information gained from supermarket tabloids and searches for “Britney Spears” is of questionable value–but we, as humans, also have a need for this type of information. Information helps define political structure and alliances, in-groups versus out-groups, elevated status within a group and other purely social functions.

The Easiest Path to Information

Our quest for information comes from within and without. As we constantly scan our environment, we find situations we need to respond to. This can trigger a physiological and intellectual chain of events that requires information. We scan our store of information, retrieve what we have and identify what we don’t. Sometimes the need is immediate. We need the information now. Sometimes it’s far off and the information-seeking process is of much longer duration.

If we need to seek information because we don’t have it stored in our memory, most of us will take the easiest path. Our information retrieval habits will vary from person to person, but generally we seek to save energy, so we will take the shortest route to the information. And our path will be dictated by how well we know what we’re looking for. When we seek information, our quest can fall into three different categories: we don’t know what we’re looking for, we know what we’re looking for but don’t know where to find it, or we know what we’re looking for and where to find it. Which path we take to find information depends on where we feel it will be easiest to find the answer. When we talk about information-seeking and the ease of retrieval, the Web–and in particular, Web search–has been the most significant development in the history of man. That’s where we start in the next column.

Digging Still Deeper into the Search Branding Question

First published June 12, 2008 in Mediapost’s Search Insider

I love debate. I love defending my ideas, and in the process, shaping, refining and sometimes discarding them as they prove to be too unwieldy or simply incorrect. My last two columns have generated a fascinating debate around the concept of branding in search. Fellow Search Insider Aaron Goldman, comScore Chairman Gian Fulgoni, his senior vice president of search and media, James Lamberti, Erik du Plessis, Millward Brown executive and author of  “The Advertised Mind” (fascinating book, by the way), as well as a host of others, have taken up the debating gauntlet on this particular topic.

As luck would have it, we just wrapped up a study with Google in Europe — and data there seems to show that I’m dead wrong about the inability of unclicked search ads to build brand, reinforcing the view of Gian and Aaron (Aaron has his own research, and ours seems to support his findings). We saw brand lift (based on traditional metrics) of anywhere from 5 to 15% on even unclicked ads. And this was with thousands of respondents across four different product categories in three different markets, so I don’t think it’s an anomaly.

The easy thing would have been to toss in the towel and admit I was wrong. But I’m not so sure about that. I’m convinced the neurobiological underpinnings I outlined in my column two weeks ago are sound and that the reasons for the apparent contradictions lie in some aspects of the search interaction and brand recall that I overlooked and the metrics we use to measure them.

But, in looking at this, I realized that this topic lies at the heart of a fundamental and not-yet-explored aspect of search: how does it influence our brand relationships? In one regard, I’m wholly in agreement with Aaron, Gian and James. There’s a tremendous amount of branding value being left on the table with search. Where we differ is in the nature of that value. But that’s not an easy thing to explore. It’s certainly beyond the scope of a single column. So yesterday I sent an email to my MediaPost editor asking if I could use this column over the next several weeks to lay out my hypothesis for how we interact with search. Thankfully, she agreed. So, beginning this week, I’d like to begin unraveling that knot.

In my weekly columns over the next few months I’d like to explore several questions:

Why do we search: This goes to Aaron’s comment that we don’t always search for information about a purchase. And this is absolutely true. We search for many different reasons. I’ll look at what motivates us to search and our mental frame of mind when do so. Is searching a conditioned behavior?

Why we search the way we do: Through all Enquiro’s research, we have found very consistent search patterns. Why do we search the way we do? How do we forage for information? And why is a search engagement “thin,” while a Web site engagement is “thick”?

Why does searching trigger information retrieval, but doesn’t necessarily create new memories: I’ll look at how memory works, specific to the act of searching, and how this differs from other types of advertising.

Why we use search differently at different stages in our purchasing behavior: The way we use search early in the process can be significantly different than the way we use it later. And it’s not the classic search “funnel” you may think.

Why the traditional brand metrics used are not accurate measures of likelihood to purchase, especially when applied to a search interaction.

Why search can be the most important brand tool in a marketer’s arsenal, if it’s used in the right place. It’s a matter of understanding what search can do and what it can’t. And, even more importantly, understanding how to measure that value.

And finally, will the changing nature of search change the way it acts as a branding strategy?

In this process I hope to provide supporting research where I can (there’s little empirical research in this area). I’ll also be reaching out to others, including my debating partners, to capture their views as well. And, as always, I invite you all to join the conversation.

Branding, The Mind and Search

First published June 5, 2008 in Mediapost’s Search Insider

In my last column, I opened up the search “branding” can of worms regarding unclicked search ads and generated a fascinating discussion with Gian Fulgoni and James Lamberti from comScore, as well as Aaron Goldman from Resolution Media, who has unpublished research that sheds new light on the subject and counters my argument. I think it’s fair to say that the value of an unclicked search ad still needs further research to resolve the question.

If it proves that there is brand lift created, then the question of pricing models currently used comes back into play. As Lamberti mentioned, perhaps the problem is not the pricing model but the measurement methods. And, as Jonathon Mendez from Ramp Digital added, “Is Google leaving lots of money on the table? They’re the most insanely profitable company of our time — I think they know what they’re doing.”

How Much Value is There in Search?

Could it be that we’re all right? Could it be that there’s so much value in the search interaction that Google can be leaving money on the table and still be insanely profitable? I do believe that in the case of branding impact, there is a distinct difference in the nature of the impact of the search ad from almost any other form of advertising, which is the topic of this column.

As I said a few columns back, search is more than a channel. It’s a fundamental human activity, and the same things that may be working against search in an implicit engagement way are very much working for search in an explicit way. The nature of our engagement with search is much different from other advertising.

Daring to Define Engagement

The Advertising Research Foundation has been struggling with defining engagement as a cross-channel effectiveness metric for years now, without making much headway. The problem is that engagement with a TV ad is a totally different proposition than engagement with a search ad.

Let’s look first at TV. In the 1980’s, the ARF conducted a major research study called the Copy Research Validation Project (as referenced in “The Advertised Mind,” by Erik Du Plessis). The purpose of the study was to isolate the factors that were common in successful ads. What was the one factor most predictive of success, which was actually thrown in as an after-thought? Whether people liked the ad.

Before most ads can work, they have to get our attention. And we pay more attention to things we like. This led to a hyper-creative explosion in the advertising biz, as agencies churned out ads designed first and foremost to make us like them. Unfortunately, most ads forgot that once you get someone’s attention, you also have to sell something. And that can be a difficult balance to maintain. Our cues to switch selective perception to something that captures our attention and our natural defenses against unsolicited persuasion usually work counter to each other. And it’s in that dynamic abyss that 250 billion dollars of advertising — in the U.S alone — gets poured every year,.

Search: Likability is Not a Prerequisite

But search is different. You don’t need to like a search ad, because it doesn’t have to capture your attention. You’ve already volunteered that attention. Search is used to gather information about an upcoming purchase. You’re fully engaged. You’re focusing on it. There are no cognitive guards on duty, protecting you from unscrupulous persuasion.

There’s another difference. Other advertising interrupts you when you have no intention of considering purchasing the featured product or service. Search reaches you just at the time you’re most fully engaged in consideration. And there lies the tremendous value of search, as it opens the door to the most engaging interaction with a brand that there can be: the online visit.

The Most Effective Engagement Point

Once consumers have knocked on your door through search, you have a tremendous opportunity to engage them. They have expressed interest, they are actively and fully engaged, they’re looking for information and they are ready to be persuaded. In the universe of consumer motivation, all the planets are perfectly aligned. You simply cannot find a better touch point with a consumer than this.

But the key is, you have to let consumers drive that interaction. They may simply be looking for rational purchase validation information, they may be researching alternatives, or they may be looking to be emotionally persuaded. A Web site can do any and all of the above, but it has to be at the visitor’s imperative.

Do I think there’s tremendous brand value left on the table with search? Absolutely. And as James Lamberti from comScore said, uncovering that value lies first in better measurement. If we can prove the value, whether it’s implicit or explicit, that may indeed lead to a different pricing model. Let’s face it; we’re a long way from understanding online consumer behavior. As we gain more understanding, expect changes. Expect lots of them.

 

How Much Would You Pay for this Unclicked Search Ad?

First published May 29, 2008 in Mediapost’s Search Insider

As David Berkowitz mentioned a few columns back, comScore CEO Gian Fulgoni pondered the implications of the fact that 95% of Google’s search advertising inventory never gets clicked. All those millions and millions of impressions get thrown out there, just to fade away as a non event as soon as one leaves the results page. Our own research, which Fulgoni refered to, shows that presence at the top of the page does have an impact on brand awareness and propensity to buy. So, logically, even if a link is not clicked, there must be value there. Fulgoni wondered if perhaps Google was leaving significant amounts of money on the table with their cost per click model.

David looked at the implications of Fulgoni’s musings from a business model. I, staying on more familiar ground, would like to explore this from the user’s view. Ironically, although Fulgoni used our research to prove his point, I’m not so sure there is a latent brand impact from search if a link remains unclicked. Let me explain why.
Will You Remember Me?

There’s a distinct divide between the impact realized from interaction with the search results page and interaction after the click-through, on the Web site. And the difference lies in how the interactions get loaded into our brains. When the spotlight of attention is turned on, things go directly into the executive function mode of our brains, which is commonly called working memory. This is like a white board, where we gather the details needed to make decisions and store them. There are two limiting factors to working memory, capacity and duration. We can only load so much on this whiteboard, and it will remain only as long as we’re actively using it. After that, the board gets wiped clean, ready for the next decision.

When we’re using working memory, we’re fully engaging our rational loop. Things go directly to working memory. Depending on the importance of the information for us in the long term, we’ll either start creating the long-term memory hooks to retain it, or it will be left to be erased from short-term memory. Think of when you look up a phone number. Obviously, there is lots of other information on the page or Web site where you go, but you’re focused on just the number you need. You find the number and begin repeating it to yourself, effectively beginning the transition from short-term to long-term memory. The rest of the information you saw on the page, even if you were actively focused on it during the task, is almost mmediately wiped from your memory.

The memory hooks you create will depend on how long you need the number, and how often you use it. If this is going to be an oft-used piece of information, it will get stored for the long run in your semantic memory. If not, it will eventually wither away in memory purgatory, caught between the transience of short term and the enduring stability of long term.

Focus of Attention

When we interact with a search engine, our working memory is in high gear. We are very much focused on the task at hand, “berry picking” our way through the information presented on the search page. In split seconds, we filter our way through incredible amounts of information, seeking the cues of relevancy, or information scent, required to indicate which result best matches our intent. We don’t spend a lot of time qualifying the quality of the match. Click-throughs are low-risk investments. If we click through on a listing and it doesn’t provide what we’re looking for, we can easily click back to the results page and try another one. So we don’t spend a lot of time considering the results. We scan, filter and click. There’s little opportunity for unclicked messaging to pass beyond working memory and stick.

Fulgoni’s theory has one other thing working against it. Much brand impact is acquired implicitly. Even when we’re not focused on acquiring information, images, sounds and messaging are filtering into our brains at a subconscious level, there to help create our brand perceptions. But all interaction with the search results page is explicit, a very focused acquisition of information. Everything passes through executive function and working memory. There is no opportunity for brand messaging to sneak past the guard and find a nook or cranny of our cortex to lodge itself in. We’re diligently wiping the slate clean.

Fulgoni’s theory is interesting, but I’m not sure it holds up when we look at the neurobiology involved in the process. There is a tremendous branding opportunity in search, but unfortunately, it doesn’t lie in the unclicked ad. But more on that next column, when we look at the interaction on the search page, and what happens after the click-through.