Category Archives: User Behavior

Evolved Search Behaviors: Take Aways for Marketers

In the last two columns, I first looked at the origins of the original Golden Triangle, and then looked at how search behaviors have evolved in the last 9 years, according to a new eye tracking study from Mediative. In today’s column, I’ll try to pick out a few “so whats” for search marketers.

It’s not about Location, It’s About Intent

In 2005, search marketing as all about location. It was about grabbing a part of the Golden Triangle, and the higher, the better. The delta between scanning and clicks from the first organic result to the second was dramatic – by a factor of 2 to 1! Similar differences were seen in the top paid results. It’s as if, given the number of options available on the page (usually between 12 and 18, depending on the number of ads showing) searchers used position as a quick and dirty way to filter results, reasoning that the higher the result, the better match it would be to their intent.

In 2014, however, it’s a very different story. Because the first scan is now to find the most appropriate chunk, the importance of being high on the page is significantly lessened. Also, once the second step of scanning has begun, within a results chunk, there seems to be more vertical scanning within the chunk and less lateral scanning. Mediative found that in some instances, it was the third or fourth listing in a chunk that attracted the most attention, depending on content, format and user intent. For example, in the heat map shown below, the third organic result actually got as many clicks as the first, capturing 26% of all the clicks on the page and 15% of the time spent on page. The reason could be because it was the only listing that had the Google Ratings Rich Snippet because of the proper use of structured data mark up. In this case, the information scent that promised user reviews was a strong match with user intent, but you would only know this if you knew what that intent was.

Google-Ford-Fiesta

This change in user search scanning strategies makes it more important than ever to understand the most common user intents that would make them turn to a search engine. What will be the decision steps they go through and at which of those steps might they turn to a search engine? Would it be to discover a solution to an identified need, to find out more about a known solution, to help build a consideration set for direct comparisons, to look for one specific piece of information (ie a price) or to navigate to one particular destination, perhaps to order online? If you know why your prospects might use search, you’ll have a much better idea of what you need to do with your content to ensure you’re in the right place at the right time with the right content.  Nothing shows this clearer than the following comparison of heat maps. The one on the left was the heat map produced when searchers were given a scenario that required them to gather information. The one on the right resulted from a scenario where searchers had to find a site to navigate to. You can see the dramatic difference in scanning behaviors.

Intent-compared-2

If search used to be about location, location, location, it’s now about intent, intent, intent.

Organic Optimization Matters More than Ever!

Search marketers have been saying that organic optimization has been dying for at least two decades now, ever since I got into this industry. Guess what? Not only is organic optimization not dead, it’s now more important than ever! In Enquiro’s original 2005 study, the top two sponsored ads captured 14.1% of all clicks. In Mediative’s 2014 follow up, the number really didn’t change that much, edging up to 14.5% What did change was the relevance of the rest of the listings on the page. In 2005, all the organic results combined captured 56.7% of the clicks. That left about 29% of the users either going to the second page of results, launching a new search or clicking on one of the side sponsored ads (this only accounted for small fraction of the clicks). In 2014, the organic results, including all the different category “chunks,” captured 74.6% of the remaining clicks. This leaves only 11% either clicking on the side ads (again, a tiny percentage) or either going to the second page or launching a new search. That means that Google has upped their first page success rate to an impressive 90%.

First of all, that means you really need to break onto the first page of results to gain any visibility at all. If you can’t do it organically, make sure you pay for presence. But secondly, it means that of all the clicks on the page, some type of organic result is capturing 84% of them. The trick is to know which type of organic result will capture the click – and to do that you need to know the user’s intent (see above). But you also need to optimize across your entire content portfolio. With my own blog, two of the biggest traffic referrers happen to be image searches.

Left Gets to Lead

The Left side of the results page has always been important but the evolution of scanning behaviors now makes it vital. The heat map below shows just how important it is to seed the left hand of results with information scent.

Googlelefthand

Last week, I talked about how the categorization of results had caused us to adopt a two stage scanning strategy, the first to determine which “chunks” of result categories are the best match to intent, and the second to evaluated the listings in the most relevant chunks. The vertical scan down the left hand of the page is where we decide which “chunks” of results are the most promising. And, in the second scan, because of the improved relevancy, we often make the decision to click without a lot of horizontal scanning to qualify our choice. Remember, we’re only spending a little over a second scanning the result before we click. This is just enough to pick up the barest whiffs of information scent, and almost all of the scent comes from the left side of the listing. Look at the three choices above that captured the majority of scanning and clicks. The search was for “home decor store toronto.” The first popular result was a local result for the well known brand Crate and Barrel. This reinforces how important brands can be if they show up on the left side of the result set. The second popular result was a website listing for another well known brand – The Pottery Barn. The third was a link to Yelp – a directory site that offered a choice of options. In all cases, the scent found in the far left of the result was enough to capture a click. There was almost no lateral scanning to the right. When crafting titles, snippets and metadata, make sure you stack information scent to the left.

In the end, there are no magic bullets from this latest glimpse into search behaviors. It still comes down to the five foundational planks that have always underpinned good search marketing:

  1. Understand your user’s intent
  2. Provide a rich portfolio of content and functionality aligned with those intents
  3. Ensure your content appears at or near the top of search results, either through organic optimization or well run search campaigns
  4. Provide relevant information scent to capture clicks
  5. Make sure you deliver on what you promise post-click

Sure, the game is a little more complex than it was 9 years ago, but the rules haven’t changed.

Google’s Golden Triangle – Nine Years Later

Last week, I reviewed why the Golden Triangle existed in the first place. This week, we’ll look at how the scanning patterns of Google user’s has evolved in the past 9 years.

The reason I wanted to talk about Information Foraging last week is that it really sets the stage for understanding how the patterns have changed with the present Google layout. In particular, one thing was true for Google in 2005 that is no longer true in 2014 – back then, all results sets looked pretty much the same.

Consistency and Conditioning

If humans do the same thing over and over again and usually achieve the same outcome, we stop thinking about what we’re doing and we simply do it by habit. It’s called conditioning. But habitual conditioning requires consistency.

In 2005, The Google results page was a remarkably consistent environment. There was always 10 blue organic links and usually there were up to three sponsored results at the top of the page. There may also have been a few sponsored results along the right side of the page. Also, Google would put what it determined to be the most relevant results, both sponsored and organic, at the top of the page. This meant that for any given search, no matter the user intent, the top 4 results should presumably include the most relevant one or two organic results and a few hopefully relevant sponsored options for the user. If Google did it’s job well, there should be no reason to go beyond these 4 top results, at least in terms of a first click. And our original study showed that Google generally did do a pretty good job – over 80% of first clicks came from the top 4 results.

In 2014, however, we have a much different story. The 2005 Google was a one-size-fits-all solution. All results were links to a website. Now, not only do we have a variety of results, but even the results page layout varies from search to search. Google has become better at anticipating user intent and dynamically changes the layout on each search to be a better match for intent.

google 2014 big

What this means, however, is that we need to think a little more whenever we interact with a search page. Because the Google results page is no longer the same for every single search we do, we have exchanged consistency for relevancy. This means that conditioning isn’t as important a factor as it was in 2005. Now, we must adopt a two stage foraging strategy. This is shown in the heat map above. Our first foraging step is to determine what categories – or “chunks” of results – Google has decided to show on this particular results page. This is done with a vertical scan down the left side of the results set. In this scan, we’re looking for cues on what each chunk offers – typically in category headings or other quickly scanned labels. This first step is to determine which chunks are most promising in terms of information scent. Then, in the second step, we go back to the most relevant chunks and start scanning in a more deliberate fashions. Here, scanning behaviors revert to the “F” shaped scan we saw in 2005, creating a series of smaller “Golden Triangles.”

What is interesting about this is that although Google’s “chunking” of the results page forces us to scan in two separate steps, it’s actually more efficient for us. The time spent scanning each result is half of what it was in 2005, 1.2 seconds vs. 2.5 seconds. Once we find the right “chunk” of results, the results shown tend to be more relevant, increasing our confidence in choosing them.  You’ll see that the “mini” Golden Triangles have less lateral scanning than the original. We’re picking up enough scent on the left side of each result to push our “click confidence” over the required threshold.

A Richer Visual Environment

Google also offers a much more visually appealing results page than they did 9 years ago. Then, the entire results set was text based. There were no images shown. Now, depending on the search, the page can include several images, as the example below (a search for “New Orleans art galleries”) shows.

Googleimageshot

The presence of images has a dramatic impact on our foraging strategies. First of all, images can be parsed much quicker than text. We can determine the content of an image in fractions of a second, where text requires a much slower and deliberate type of mental processing. This means that our eyes are naturally drawn to images. You’ll notice that the above heat map has a light green haze over all the images shown. This is typical of the quick scan we do immediately upon page entry to determine what the images are about. Heat in an eye tracking heat map is produced by duration of foveal focus. This can be misleading when we’re dealing with images for two reasons. First, the fovea centralis is, predictably, in the center of our eye where our focus is the sharpest. We use this extensively when reading but it’s not as important when we’re glancing at an image. We can make a coarse judgement about what a picture is without focusing on it. We don’t need our fovea to know it’s a picture of a building, or a person, or a map. It’s only when we need to determine the details of a picture that we’ll recruit the fine-grained resolution of our fovea.

Our ability to quickly parse images makes it likely that they will play an important role in our initial orientation scan of the results page. We’ll quickly scan the available images looking for information scent. It the image does offer scent, it will also act as a natural entry point for further scanning. Typically, when we see a relevant image, we look in the immediate vicinity to find more reinforcing scent. We often see scanning hot spots on titles or other text adjacent to relevant images.

We Cover More Territory – But We’re Also More Efficient

So, to sum up, it appears that with our new two step foraging strategy, we’re covering more of the page, at least on our first scan, but Google is offering richer information scent, allowing us to zero in on the most promising “chunks” of information on the page. Once we find them, we are quicker to click on a promising result.

Next week, I’ll look at the implications of this new behavior on organic optimization strategies.

The Evolution of Google’s Golden Triangle

In search marketing circles, most everyone has heard of Google’s Golden Triangle. It even has it’s own Wikipedia entry (which is more than I can say). The “Triangle” is rapidly coming up to its 10th birthday (it was March of 2005 when Did It and Enquiro – now Mediative – first released the study). This year, Mediative conducted a new study to see if what we found a decade ago still continues to be true. Another study from the Institute of Communication and Media Research in Cologne, Germany also looked at the evolution of search user behaviors. I’ll run through the findings of both studies to see if the Golden Triangle still exists. But before we dive in, let’s look back at the original study.

Why We Had a Golden Triangle in the First Place

To understand why the Golden Triangle appeared in the first place, you have to understand about how humans look for relevant information. For this, I’m borrowing heavily from Peter Pirolli and Stuart Card at PARC and their Information Foraging Theory (by the way, absolutely every online marketer, web designer and usability consultant should be intimately familiar with this theory).

Foraging for Information

Humans “forage” for information. In doing so, they are very judicious about the amount of effort they go to find the available information. This is largely a subconscious activity, with our eyes rapidly scanning for cues of relevancy. Pirolli and Card refer to this as “information scent.” Picture a field mouse scrambling across a table looking for morsels to eat and you’ll have an appropriate mental context in which to understand the concept of information foraging. In most online contexts, our initial evaluation of the amount of scent on a page takes no more than a second or two. In that time, we also find the areas that promise the greatest scent and go directly to them. To use our mouse analogy, the first thing she does is to scurry quickly across the table and see where the scent of possible food is the greatest.

The Area of Greatest Promise

Now, Imagine that same mouse comes back day after day to the same table and every time she returns, she finds the greatest amount of food is always in the same corner. After a week or so, she learns that she doesn’t have to scurry across the entire table. All she has to do is go directly to that corner and start there. If, by some fluke, there is no food there, then the mouse can again check out the rest of the table to see if there are better offerings elsewhere. The mouse has been conditioned to go directly to the “Area of Greatest Promise” first.

Golden Triangle original

F Shaped Scanning

This was exactly the case when we did the first eye tracking study in 2005. Google had set a table of available information, but they always put the best information in the upper right corner. We became conditioned to go directly to the area of greatest promise. The triangle shape came about because of the conventions of how we read in the western world. We read top to bottom, left to right. So, to pick up information scent, we would first scan down the beginning of each of the top 4 or 5 listings. If we saw something that seemed to be a good match, we would scan across the title of the listing. If it was still a good match, we would quickly scan the description and the URL. If Google was doing it’s job right, there would be more of this lateral scanning on the top listing than there would be on the subsequent listings. This F shaped scanning strategy would naturally produce the Golden Triangle scanning pattern we saw.

Working Memory and Chunking

There was another behavior we saw that helped explain the heat maps that emerged. Our ability to actively compare options requires us to hold in our mind information about each of the options. This means that the number of options we can compare at any one time is restricted by the limits of our working memory. George Miller, in a famous paper in 1956, determined this to be 7 pieces of information, plus or minus two. The actual number depends on the type of information to be retained and the dimension of variability. In search foraging, the dimension is relevancy and the inputs to the calculation will be quick judgments of information scent based on a split second scan of the listing. This is a fairly complex assessment, so we found that the number of options to be compared at once by the user tends to max out about 3 or 4 listings. This means that the user “chunks” the page into groupings of 3 or 4 listings and determines if one of the listings is worthy of a click. If not, the user moves on to the next chunk. We also see this in the heat map shown. Scanning activity drops dramatically after the first 4 listings. In our original study, we found that over 80% of first clicks on all the results pages tested came from the top 4 listings. This is also likely why Google restricted the paid ads shown above organic to 3 at the most.

So, that’s a quick summary of our findings from the 2005 study. Next week, we’ll look how search scanning has changed in the past 9 years.

Note: Mediative and SEMPO will be hosting a Google+ Hang Out talking about their research on October 14th. Full details can be found here.

Want to Be More Strategic? Stand Up!

article-1388357-0050C69D00000258-771_472x345One of the things that always frustrated me in my professional experience was my difficulty in switching from tactical to strategic thinking. For many years, I served on a board that was responsible for the strategic direction of an organization. A friend of mine, Andy Freed, served as an advisor to the board. He constantly lectured us on the difference between strategy and tactics:

“Strategy is your job. Tactics are mine. Stick to your job and I’ll stick to mine.”

Despite this constant reminder, our discussions always seemed to quickly spiral down to the tactical level. We all caught ourselves doing it. It seemed that as soon as we started thinking about what needed to be done and why, we automatically shifted gears and thought about how it should be done.

A recent study may have found the problem. We were sitting down. We should have stood up. Better yet, we should have taken the elevator to the top of the building (we actually did do this at one board retreat in Scottsdale, Arizona). Two researchers at the University of Toronto (home, I should point out, of what was the tallest free standing structure in the world for many years – the CN Tower), Pankaj Aggarwal and Min Zhao, found that a subject’s physical situation impacted how strategic they were. When subjects were physically higher up, say standing on a tall stool, they were more likely to look at the “big picture.”

Our physical context has more than a little impact on how we think. It’s a phenomenon called Mental Construal. And it’s not just restricted to how strategic our thinking is. It can impact thinks like social judgment as well. In a 2006 paper, University of Michigan professor Norbert Schwartz gave some examples that fall under the category called “situated concepts.” For example, the mental images you retrieve when I say “chair” might be different if we’re standing in a living room rather than an airplane or movie theatre. Another example, which unfortunately speaks to a darker side of human nature, is how you would respond to the face of a young African American when shown in the context of a church scene versus the context of a street corner scene.

Schwartz also talks about levels of construal. We’re more successful staying at strategic levels when our planning is trouble free. The minute we hit a problem, we tend to revert to finer grained tactical thinking. Again, in my board experience, the minute we started hitting problems we immediately tried to solve them, which effectively derailed any strategic discussion.

In his book, Creativity: Flow and the Psychology of Discovery and Invention, Mihaly Csikszentmihalyi found that physical contexts can also impact creativity. Physicist Freeman Dyson found that walking was essential to drive the creative process,

“Again, I never went to a class that (Richard) Feynman taught. I never had any official connection with him at all, in fact. But we went for walks. Most of the time that I spent with him was actually walking, like the old style of philosophers who used to walk around under the cloisters.”

In a study where subjects were given pagers and were signaled at random times of the day, they were asked to rate how creative they felt. It turned out the highest level of creativity came while they were walking, driving or swimming. Perhaps it was the physical stimulation, but it may have also been mental construal at work. Perhaps physical movement primed the brain for mental movement.

So, if you need to be strategic, find the highest vantage point possible, with room to walk around, preferably with the smartest person you know.

Two Views of the Promise of Technology

technologybrainIn the last two columns, I’ve looked at how technology may be making us intellectually lazy. The human brain tends to follow the path of least resistance and technology’s goal is to eliminate resistance. Last week, I cautioned that this may end up making us both more shallow in our thinking and more fickle in our social ties. We may become an attention deficit society, skipping across the surface of the world. But, this doesn’t necessarily have to be the case.

The debate is not a new one. Momentous technologies generally come complete with their own chorus of naysayers. Whether it’s the invention of writing, the printing press, electronic communication or digital media, the refrain is the same – this will be the end of the world as we know it. But if history has taught us anything, it’s that new technologies are seldom completely beneficial or harmful. Their lasting impact lies somewhere in the middle. With the good comes some bad.

The same will be true for the current digital technologies. The world will change, both for the positive and for the negative. The difference will come in how individuals use the technology. This will spread out along the inevitable bell curve.

watchingTVLook at television, for instance. A sociologist could make a pretty convincing case for the benefits of TV. A better understanding of the global community helped ease our xenophobic biases. Public demand lead to increased international pressure on repressive regimes. There was a sociological leveling that is still happening across cultures. Civil rights and sexual equality were propelled by the coverage they received. Atrocities still happen with far too much regularity, but I personally believe the world is a less savage and brutal place than it was 100 years ago, partially due to the spread of TV.

On the flip side, we have developed a certain laziness of spirit that is fed by TV’s never ending parade of entertainment to be passively consumed. We spend less time visiting our neighbors. We volunteer less. We’re less involved in our communities. Ironically, we’re  a more idealistic society but we make poorer neighbors.

The type of programming to be found on TV also shows that despite the passive nature of the medium, we didn’t become stupider en masse. Some of us use TV for enlightenment, and some of us use it to induce ourselves into a coma. At the end of the day, I think the positives and negatives of TV as a technology probably net out a little better than neutral.

I suspect the same thing is happening with digital media. Some of us are diving deeper and learning more than ever. Others are clicking their way through site after site of brain-porn. Perhaps there are universal effects that will show up over generations that will type the scale one way or the other, but we’re too early in the trend to see those yet. The fact is, digital technologies are not changing our brains in a vacuum. Our environment is also changing and perhaps our brains are just keeping up. The 13 year old who is frustrating the hell out of us today may be a much better match for the world 20 years from now.

I’ll wrap up by leaving three pieces of advice that seem to provide useful guides for getting the best out of new technologies.

First: A healthy curiosity is something we should never stop nurturing. In particular, I find it helpful to constantly ask “how” and “why.”

Second: Practice mindfulness. Be aware of your emotions and cognitive biases and recognize them for what they are. This will help you steer things back on track when they’re leading down an unhealthy path

Third: Move from consuming content to contributing something meaningful. The discipline of publishing tends to push you beyond the shallows.

If you embrace the potential of technology, you may still find yourself as an outlier, but technology has done much to allow a few outliers to make a huge difference.

Are Our Brains Trading Breadth for Depth?

ebrain1In last week’s column, I looked at how efficient our brains are. Essentially, if there’s a short cut to an end goal identified by the brain, it will find it. I explained how Google is eliminating the need for us to remember easily retrievable information. I also speculated about how our brains may be defaulting to an easier form of communication, such as texting rather than face-to-face communication.

Personally, I am not entirely pessimistic about the “Google Effect,” where we put less effort into memorizing information that can be easily retrieved on demand. This is an extension of Daniel Wegner’s “transactive memory”, and I would put it in the category of coping mechanisms. It makes no sense to expend brainpower on something that technology can do easier, faster and more reliably. As John Mallin commented, this is like using a calculator rather than memorizing times tables.

Reams of research has shown that our memories can be notoriously inaccurate. In this case, I partially disagree with Nicholas Carr. I don’t think Google is necessarily making us stupid. It may be freeing up the incredibly flexible power of our minds, giving us the opportunity to redefine what it means to be knowledgeable. Rather than a storehouse of random information, our minds may have the opportunity to become more creative integrators of available information. We may be able to expand our “meta-memory”, Wegner’s term for the layer of memory that keeps track of where to turn for certain kinds of knowledge. Our memory could become index of interesting concepts and useful resources, rather than ad-hoc scraps of knowledge.

Of course, this positive evolution of our brains is far from a given. And here Carr may have a point. There is a difference between “lazy” and “efficient.” Technology’s freeing up of the processing power of our brain is only a good thing if that power is then put to a higher purpose. Carr’s title, “The Shallows” is a warning that rather than freeing up our brains to dive deeper into new territory, technology may just give us the ability to skip across the surface of the titillating. Will we waste our extra time and cognitive power going from one piece of brain candy to the other, or will we invest it by sinking our teeth into something important and meaningful?

A historical perspective gives us little reason to be optimistic. We evolved to balance the efforts required to find food with the nutritional value we got from that food. It used to be damned hard to feed ourselves, so we developed preferences for high calorie, high fat foods that would go a long way once we found them. Thanks to technology, the only effort required today to get these foods is to pick them off the shelf and pay for them. We could have used technology to produce healthier and more nutritious foods, but market demands determined that we’d become an obese nation of junk food eaters. Will the same thing happen to our brains?

I am even more concerned with the short cuts that seem to be developing in our social networking activities. Typically, our social networks are built both from strong ties and weak ties. Mark Granovetter identified these two types of social ties in the 70’s. Strong ties bind us to family and close friends. Weak ties connect us with acquaintances. When we hit rough patches, as we inevitably do, we treat those ties very differently. Strong ties are typically much more resilient to adversity. When we hit the lowest points in our lives, it’s the strong ties we depend on to pull us through. Our lifelines are made up of strong ties. If we have a disagreement with someone with whom we have a strong tie, we work harder to resolve it. We have made large investments in these relationships, so we are reluctant to let them go. When there are disruptions in our strong tie network, there is a strong motivation to eliminate the disruption, rather than sacrifice the network.

Weak ties are a whole different matter. We have minimal emotional investments in these relationships. Typically, we connect with these either through serendipity or when we need something that only they can offer. For example, we typically reinstate our weak tie network when we’re on the hunt for a job. LinkedIn is the virtual embodiment of a weak tie network. And if we have a difference of opinion with someone to whom we’re weakly tied, we just shut down the connection. We have plenty of them so one more or less won’t make that much of a difference. When there are disruptions in our weak tie network, we just change the network, deactivating parts of it and reactivating others.

Weak ties are easily built. All we need is just one thing in common at one point in our lives. It could be working in the same company, serving on the same committee, living in the same neighborhood or attending the same convention. Then, we just need some way to remember them in the future. Strong ties are different. Strong ties develop over time, which means they evolve through shared experiences, both positive and negative. They also demand consistent communication, including painful communication that sometimes requires us to say we were wrong and we’re sorry. It’s the type of conversation that leaves you either emotionally drained or supercharged that is the stuff of strong ties. And a healthy percentage of these conversations should happen face-to-face. Could you build a strong tie relationship without ever meeting face-to-face? We’ve all heard examples, but I’d always place my bets on face-to-face – every time.

It’s the hard work of building strong ties that I fear we may miss as we build our relationships through online channels. I worry that the brain, given an easy choice and a hard choice, will naturally opt for the easy one. Online, our network of weak ties can grow beyond the inherent limits of our social inventory, known as Dunbar’s Number (which is 150, by the way). We could always find someone with which to spend a few minutes texting or chatting online. Then we can run off to the next one. We will skip across the surface of our social network, rather than invest the effort and time required to build strong ties. Just like our brains, our social connections may trade breadth for depth.

The Pros and Cons of a Fuel Efficient Brain

Transactive dyadic memory Candice Condon3Your brain will only work as hard as it has to. And if it makes you feel any better, my brain is exactly the same. That’s the way brains work. They conserve horsepower until when it’s absolutely needed. In the background, the brain is doing a constant calculation: “What do I want to achieve and based on everything I know, what is the easiest way to get there?” You could call it lazy, but I prefer the term “efficient.”

The brain has a number of tricks to do this that involve relatively little thinking. In most cases, they involve swapping something that’s easy for your brain to do in place of something difficult. For instance, consider when you vote. It would be extraordinarily difficult to weigh all the factors involved to truly make an informed vote. It would require a ton of brainpower. But it’s very easy to vote for whom you like. We have a number of tricks we use to immediately assess whether we like and trust another individual. They require next to no brainpower. Guess how most people vote? Even those of us who pride ourselves on being informed voters rely on these brain short cuts more than we would like to admit.

Here’s another example that’s just emerging, thanks to search engines. It’s called the Google Effect and it’s an extension of a concept called Transactive Memory. Researchers Betsy Sparrow, Jenny Liu and Daniel Wegner identified the Google Effect in 2011. Wegner first explained transactive memory back in the 80’s. Essentially, it means that we won’t both to remember something that we can easily reference when we need it. When Wegner first talked about transactive memory in the 80’s, he used the example of a husband and wife. The wife was good at remembering important dates, such as anniversaries and birthdays. The husband was good at remembering financial information, such as bank balances and when bills were due. The wife didn’t have to remember financial details and the husband didn’t have to worry about dates. All they had to remember was what each other was good at memorizing. Wegner called this “chunking” of our memory requirements “metamemory.”

If we fast-forward 30 years from Wegner’s original paper, we find a whole new relevance for transactive memory, because we now have the mother of all “metamemories”, called Google. If we hear a fact but know that this is something that can easily be looked up on Google, our brains automatically decide to expend little to no effort in trying to memorize it. Subconsciously, the brain goes into power-saver mode. All we remember is that when we do need to retrieve the fact, it will be a few clicks away on Google. Nicholar Carr fretted about whether this and other cognitive short cuts were making us stupid in his book “The Shallows.”

But there are other side effects that come from the brain’s tendency to look for short cuts without our awareness. I suspect the same thing is happening with social connections. Which would you think required more cognitive effort: a face-to-face conversation with someone or texting them on a smartphone?

Face-to-face conversation can put a huge cognitive load on our brains. We’re receiving communication at a much greater bandwidth than with text.   When we’re across from a person, we not only hear what they’re saying, we’re reading emotional cues, watching facial expressions, interpreting body language and monitoring vocal tones. It’s a much richer communication experience, but it’s also much more work. It demands our full attention. Texting, on the other hand, can easily be done along with other tasks. It’s asynchronous – we can pause and pick up when ever we want. I suspect its no coincidence that younger generations are moving more and more to text based digital communication. Their brains are pushing them in that direction because it’s less work.

One of the great things about technology is that it makes our life easier. But is that also a bad thing? If we know that our brains will always opt for the easiest path, are we putting ourselves in a long, technology aided death spiral? That was Nicholas Carr’s contention. Or, are we freeing up our brains for more important work?

More on this to come next week.

When Are Crowds Not So Wise?

the-wisdom-of-crowdsSince James Surowiecki published his book “The Wisdom of Crowds”, the common wisdom is – well – that we are commonly wise. In other words, if we average the knowledge of many people, we’ll be smarter than any of us would be individually. And that is true – to an extent. But new research suggests that there are group decision dynamics at play where bigger (crowds) may not always be better.

A recent study by Iain Couzin and Albert Kao at Princeton suggests that in real world situations, where information is more complex and spotty, the benefits of crowd wisdom peaks in groups of 5 to 20 participants and then decreases after that. The difference comes in how the group processes the information available to them.

In Surowiecki’s book, he uses the famous example of Sir Francis Galton’s 1907 observation of a contest where villagers were asked to guess the weight of an ox. While no individual correctly guessed the weight, the average of all the guesses came in just one pound short of the correct number. But this example has one unique characteristic that would be rare in the real world – every guesser had access to the same information. They could all see the ox and make their guess. Unless you’re guessing the number of jellybeans in a jar, this is almost never the case in actual decision scenarios.

Couzin and Kao say this information “patchiness” is the reason why accuracy tends to diminish as the crowd gets bigger. In most situations, there is commonly understood and known information, which the researchers refer to as “correlated information.” But there is also information that only some of the members of the group have, which is “uncorrelated information.” To make matters even more complex, the nature of uncorrelated information will be unique to each individual member. In real life, this would be our own experience, expertise and beliefs.  To use a technical term, the correlated information would be the “signal” and the uncorrelated information would be the “noise.” The irony here is that this noise is actually beneficial to the decision process.

In big groups, the collected “noise” gets so noisy it becomes difficult to manage and so it tends to get ignored. It drowns itself out. The collective focuses instead on the correlated information. In engineering terms this higher signal-to-noise ratio would seem to be ideal, but in decision-making, it turns out a certain amount of noise is a good thing. By focusing just on the commonly known information, the bigger crowd over-simplifies the situation.

Smaller groups, in contrast, tend to be more random in their make up. The differences in experiences, knowledge, beliefs and attitudes, even if not directly correlated to the question at hand, have a better chance of being preserved. They don’t get “averaged” out like they would in a bigger group. And this “noise” leads to better decisions if the situation involves imperfect information. Call it the averaging of intuition, or hunches. In a big group, the power of human intuition gets sacrificed in favor of the commonly knowable. But in a small group, it’s preserved.

In the world of corporate strategy, this has some interesting implications. Business decisions are almost always complex and involve imperfectly distributed information. This research seems to indicate that we should carefully consider our decision-making units. There is a wisdom of crowds benefit as long as the crowd doesn’t get too big. We need to find a balance where we have the advantage of different viewpoints and experiences, but this aggregate “noise” doesn’t become unmanageable.

The Power of Meta

meta111First published April 24, 2014 in Mediapost’s Search Insider

To the best of our knowledge, humans are the only species capable of thinking about thinking, even though most of us don’t do it very often. We use the Greek word “meta” to talk about this ability.  Basically, “meta” refers to a concept which is an abstraction of another concept –an instruction sheet for whatever the original thing is.

Because humans can grasp this concept, it can be a powerful way to overcome the limits of our genetic programming. Daniel Kahneman’s book, Thinking Fast and Slow, is essentially a meta-guide to the act of thinking – an owner’s guide for our minds. In it, he catalogs evolutions extensive list of cognitive “gotch-yas” that can way lay our rational reasoning.

In our digital world, we use the word “metadata” a lot. Essentially, metadata is a guide to the subject data. It sits above the data in question, providing essential information about it, such as sources, structure, indexing guides, etc. Increasingly, as we get data from more and more disparate sources, metadata will be required to use it. Ideally, it will provide universally understood implementation guide.  This, of course, requires a common schema for metadata; something that organizations like schema.org is currently working on.

Meta is a relatively new concept that has exploded in the last few decades. It’s one of those words we throw around, but we probably don’t stop to think about. It’s power lies in its ability to both “mark up” the complexity of real world, giving us another functional layer in which to operate. But it also allows us to examine ourselves and overcome some of the mental foibles we’re subject to.

According to Wikipedia, there are over 160 cognitive biases that can impact our ability to rationally choose the optimal path. They include such biases as the Cheerleader Effect, where individuals are more attractive in a group, the IKEA Effect, where we overvalue something we assemble ourselves, and the Google Effect, where we tend to forget information we know we can look up on Google. These are like little bugs in our operating software and most times, they impact our rational performance without us even being aware of them.  But if we have a meta-awareness of them, we can mitigate them to a large degree. We can step back from our decision process and see where biases may be clouding our judgment.

Meta also allows us to model and categorize complexity. It allows us to append data to data, exponentially increasing the value of the aggregated data set. This becomes increasingly important in the new era of Big Data. The challenge with Big Data is that it’s not only more data, because in this case, more is different. Big Data typically comes from multiple structured sources and when it’s removed from the guidance of it’s native contextual schema, it becomes unwieldy. A metadata layer gives us a Rosetta’s Stone with which we can integrate these various data sources. And it’s in the combining of data in new combinations that the value of Big Data can be found.

Perhaps the most interesting potential of meta is in how we might create a meta-model of ourselves. I’ve talked about this before in the context of social media.  Increasingly, our interactions with technology will gain value from personalization. Each of us will be generating reams of personal data. There needs to be an efficient connection between the two. We can’t invest the time required to train all these platforms, tools and apps to know us better. It makes sense to consolidate the most universally applicable data about us into a meta-profile of our goals, preferences and requirements. In effect, it will be a technologically friendly abstraction of who we are.  If we can agree on a common schema for these meta-profiles, the developers of technology can develop their various tools to recognize them and reconfigure their functionality tailor made for us.

As our world becomes more complex, the power of meta will become more and more important.

Five Years Later – An Answer to Lance’s Question (kind of)

112309-woman-internetIt never ceases to amaze me how writing can take you down the most unexpected paths, if you let it. Over 5 years ago now, I wrote a post called “Chasing Digital Fluff – Who Cares about What’s Hot?” It was a rant, and it was aimed at marketer’s preoccupation with what the latest bright shiny object was. At the time, it was social. My point was that true loyalty needs stabilization in habits to emerge. If you’re constantly chasing the latest thing, your audience will be in a constant state of churn. You’d be practicing “drive-by” marketing. If you want to find stability, target what your audience finds useful.

This post caused my friend Lance Loveday to ask a very valid question…”What about entertainment?” Do we develop loyalty to things that are entertaining? So, I started with a series of posts on the Psychology of Entertainment. What types of things do we find entertaining? How do we react to stories, or humor, or violence? And how do audiences build around entertainment? As I explored the research on the topic, I came to the conclusion that entertainment is a by-product of several human needs – the need to bond socially, the need to be special, our appreciation for others whom we believe to be special, a quest for social status and artificially stimulated tweaks to our oldest instincts – to survive and to procreate. In other words, after a long and exhausting journey, I concluded that entertainment lives in our phenotype, not our genotype. Entertainment serves no direct evolutionary purpose, but it lives in the shadows of many things that do.

So, what does this mean for stability of an audience for entertainment? Here, there is good news, and bad news. The good news is that the raw elements of entertainment haven’t really changed that much in the last several thousand years. We can still be entertained by a story that the ancient Romans might have told. Shakespeare still plays well to a modern audience. Dickens is my favorite author and it’s been 144 years since his last novel was published. We haven’t lost our evolved tastes for the basic building blocks of entertainment. But, on the bad news side, we do have a pretty fickle history when it comes to the platforms we use to consume our entertainment.

This then introduces a conundrum for the marketer. Typically, our marketing channels are linked to platforms, not content. And technology has made this an increasingly difficult challenge. While we may connect to, and develop a loyalty for, specific entertainment content, it’s hard for marketers to know which platform we may consume that content on. Take Dickens for example. Even if you, the marketer, knows there’s a high likelihood that I may enjoy something by Dickens in the next year, you won’t know if I’ll read a book on my iPad, pick up an actual book or watch a movie on any one of several screens. I’m loyal to Dickens, but I’m agnostic as to which platform I use to connect with his work. As long as marketing is tied to entertainment channels, and not entertainment content, we are restricted to targeting our audience in an ad hoc and transitory manner. This is one reason why brands have rushed to use product placement and other types of embedded advertising, where the message is set free from the fickleness of platform delivery challenges. If you happen to be a fan of American Idol, you’re going to see the Coke and Ford brands displayed prominently whether you watch on TV, your laptop, your tablet or your smartphone.

It’s interesting to reflect on the evolution of electronic media advertising and how it’s come full circle in this one regard. In the beginning, brands sponsored specific shows. Advertising messages were embedded in the content. Soon, however, networks, which controlled the only consumption choice available, realized it was far more profitable to decouple advertising from the content and run it in freestanding blocks during breaks in their programming. This decoupling was fine as long as there was no fragmentation in the channels available to consume the content, but obviously this is no longer the case. We now watch TV on our schedule, at our convenience, through the device of our choice. Content has been decoupled from the platform, leaving the owners of those platforms scrambling to evolve their revenue models.

So – we’re back to the beginning. If we want to stabilize our audience to allow for longer-term relationship building, what are our options? Obviously, entertainment offers some significant challenges in this regard, due mainly to the fragmentation of platforms we use to consume that content. If we use usefulness as a measure, the main factor in determining loyalty is frequency and stability. If you provide a platform that becomes a habit, as Google has, then you’ll have a fairly stable audience. It won’t destabilize until there is a significant enough resetting of user expectations, forcing the audience to abandon habits (always very tough to do) and start searching for another useful tool that is a better match for the reset expectations. If this happens, you’ll be continually following your audience through multiple technology adoption curves. Still, it seems that usefulness offers a better shot at a stable audience than entertainment.

But there’s still one factor we haven’t explored – what part does social connection play? Obviously, this is a huge question that the revenue models of Facebook, Twitter, Snapchat and others will depend on. So, with entertainment and usefulness explored ad nauseum, in the series of posts, I’ll start tracking down the Psychology of Social connection.