Category Archives: Search Behaviors

What Happens When the Whole World becomes Searchable?

My Search Insider column today was big picture stuff, looking at how search can connect us to a digitized world.

Here’s an excerpt:

There is this vast binary universe out there, terabyte after terabyte of data that grows each and every second, capturing the essence of who we are and what we do. And the sole door to that world, the channel we all must pass through to gain entry, is search. In the act of searching, we connect to that universe.

Catch the rest of the column at MediaPost.

The column drew some interesting responses, both on the Search Insider blog and emailed to me.

Martin Edic truly thought globally

In the spirit of creating a ‘brain melter’, imagine the extension of search created by GPS and satellite imaging. Suppose I want to create a search engine devoted to global climate change. If I can access these sources I could literally do a planetary search that included both digital data a geographoc, geological, weather and other environmental data all viewable as imagery, maps, text, etc.

David Gust took exception to my plaudits for Pandora: I initially thought Pandora was great, but eventually it became monotonous. A descriptor genome for the music is great, but it doesn’t decipher the music consumption genome in me.

My point is that indexing means little without context. Context is about behavior and that is where the true focus must be placed to truly unlock value of “Indexing the World”

Derick Harris,w ho obviously has a lot of time on his hands, took me to task for my “pointless” vision of an Orwellian future

I do wish that these marketing rhetoricians of search, such as Mr. Hotchkiss, would “think first” about what they are asking, in terms of “big questions” — instead of wasting our time with patently pointless essays that amount to self-serving indulgences posing as questions that really amount to a whole world Googleized into an information hell.

…Ouch! Sorry Derick, I obviously hit a sore spot.

And in the spirit of wired “Big Brother”, Warren Peace (come on..that can’t be your real name. But if it is, kudos to your parents!) shared his vision of a database schema for a “global object database” or GOD for short…

whereby every kind of digital data could be stored, indexed and cross-referenced, and rated for accuracy (couldn’t find funding for it, though). One issue is that many things are analog, not digital, and digitizing them means losing important information. An image of a person and a list of their interests is NOT the person, just an avatar. Do we really need an avatar of every living thing?

Perhaps that’s what the real “God” is – an analog, searchable object database that details absolute accuracy.

Talk about your brain melters!

Google and the Future of Video

The talks that Google and Apple are currently in about video will likely start defining the future of video entertainment as we know it. And it’s just one more example of “push” going to “pull”.

The news story is about iTV, the new device that bridges the gap between the TV and the PC, letting you viewed video from your hard drive on your TV. It’s the continuation of convergence that I’ve been talking about for some time now.

But what is interesting about this to me is not so much the hardware as the extension of searchability to online entertainment. It’s just a matter of time before the walls come down between something like YouTube and the world of broadcast TV. They’re already crumbling rapidly. And setting your viewing preferences based on searchability opens up a whole new world. I’ve had just a taste of it through Microsoft’s Media Center and I like it. You can search up to two weeks of programming by keyword, looking for a particular topic, director or actor.

Now, let’s extend this the next logical step. Let’s open up the rapidly exploding world of video. All the movies, all the tv shows, all the documentaries ever made, as well as the crushing wave of consumer generated video content, all as searchable as the web thanks to Google. You in the mood for a show about 9/11 conspiracy theories? A quick search and you’re watching Loose Change. Plus, Google suggests other shows you might be interested on based on your topic. It’s just a matter of time before somebody does for video what Pandora is doing for music, allowing you to explore the world of video entertainment based on similarities to what you already like.

Social tagging opens up more possibilities, allowing you to tap into the most popular choices of the various online communities you belong to. The buzz effect takes over (as we see currently on YouTube) and suddenly watching online video becomes a communal experience.

It’s a revolution in video distribution, and the seeds are being sown currently in the chat that Steve Jobs and Eric Schmidt are likely having as we speak.

Google Dropping Sponsored from the Golden Triangle?

Whoa..this is a bold move!

Just saw a thread on Webmaster World that indicates Google is testing removing top sponsored ads after a number of searches where a user doesn’t click on anything. Tried it myself and sure enough, after 4 or 5 refreshes, top ads were gone.

After refreshing on the same query, the ads disappeared for that query, and any modifications of the query, but still showed for a totally different query. After I went through the same process with the new query, all my top ads disappeared.

If Google sticks with this, it demonstrates a huge dedication to the user experience. Our research has shown how valuable this real estate is from a monetization perspective, but Google’s feeling (and rightly so) is that if you’re skipping past it anyway, the probability of a click on these ads is minimal. Why impair the user experience but taking up prime real estate with something that the user is just filtering out anyway.

I did some more testing with some different patterns to see where the sponsored filter seems to be tripped. If you do a number of different searches without clicking on sponsored listings, it doesn’t seem to kick in. It’s only if you do a lot of return visits to the same set of search results without hitting a sponsored link. But once the ads are gone, they’re gone for every query from then on til you clear your cookies.

Ironically, my only hesitation with this is from the user experience perspective. My feeling is the thresholds might be set too low. Intent plays a huge part in how we interact with search listings, and this can vary greatly from search to search. It’s also very difficult to determine from the nature of the query. So, if I’m in a fact finding mode, even if I’m using what appear to be very commercial terms, and I skip over ads on 4 or 5 subsequent returns to a page, that doesn’t necessarily mean I don’t want ads on any search. One anomalous search could filter out top sponsored results for days, weeks and even months and the user would never know what happened. There is no indication on the page that Google is applying any type of filter. There is no way to turn them back on. For 99.9% of web users, they’d never know what happened.

Now, it’s not all ads, but only the top ones that disappear. But the fact is, the difference between visibility and performance of ads in the two locations is so significant, that moving the top ads over to the side is almost like removing the ads from the page. Almost everyone starts scanning at the top of the page.

Google’s intentions are noble here, but they’re actually removing control from the user. I’m a big champion of organic results, so I can’t believe I’m saying this, but Google might be too hasty in stripping out top sponsored ads. In two different eye tracking tests, we found that it was clicks on these top sponsored links that actually offered the highest success rates for users. I’ll be watching with great interest to see how the test progresses.

Tales of Pogo Sticks, Bouncy SERPs and Sticky Pages

First published September 7, 2006 in Mediapost’s Search Insider

Much of what little strategy exists in search marketing is aimed towards the first click from a results page (also called a SERP). The position, the messaging and the landing page experience all assume that we’ve captured that all-important first click. But what about the subsequent clicks? In the search business, this is called pogo sticking, the bouncing back and forth from the search page, and clicking on a number of sites in sequence in an effort to find what we’re looking for.

Desperately Seeking Pogo Stats

We know pogo sticking exists, but when I tried to quantify how common it was, I quickly ran into a lot of closed doors. I tried all the major engines and was told that they don’t divulge that type of information, even in aggregate form. I also tried the monitoring services (comScore, Nielsen, Hitwise) but again came up empty.

So, failing anything more quantitative, we had to turn to our own limited data set. The stats below come from the combination of eye-tracking sessions, where we’ve been able to look for pogo sticking. I’m not sure how accurate it is, but it’s the best we’ve got, so I present it with a whackload of caveats.

We saw pogo sticking occur in 49 percent of the sessions we looked at. We suspect the occurrence of this type of behavior would be even higher in real-world settings. So at least one out of every two searches results in a return visit to the results page. In our sessions, 21.5 percent of them results in two clicks from the SERP, 10.4 percent in three clicks, 4.9 percent in four clicks, and 5.5 percent in five clicks. The remainder (6.8 percent) clicked six times or more.

Google has the fewest pogo sticking sessions, with only 36.4 percent of them resulting in a round trip to the SERP. MSN had the highest percentage, with 59.4 percent. Even if you question the numbers (and you have every right to do so) I believe it’s a pretty safe bet that pogo sticking is a pretty common occurrence.

The Power of the Pogo

Why is this important? Because a return visit looks significantly different than the first visit. And if it happens at least half the time, it’s a factor we’d do well to consider as we lay down our search strategies.

I strongly recommend that all search strategies take into consideration the mind-set of your target customer, within the context of what else appears on the page. This exercise can help you forecast the receptiveness of your target to your position on the page, the messaging you present, and the landing page experience you provide.

Let’s walk through a typical scenario. Our target customer searches for “hybrid SUV’s.” Because we’ve done our market segmentation homework, we know our target is early in the buying cycle, and is looking for alternatives for fuel-efficient SUVs, building a consideration set.

Eye-tracking studies have shown there’s relatively little variance in the scanning activity with most searchers at the beginning. They tend to start at the top and work their way down, with a strong bias toward the No. 1 organic spot. Therefore, in this scenario, we have to look at how enticing these top listings are. In walking through this on a search engine, GM and Lexus had purchased the top sponsored spots, where the majority of searchers start their scanning. The first organic spot belongs to the site hybridcars.com, a comparison of available hybrid SUVs. Given our target and his intent, it’s very likely that this site will capture the majority of first clicks from the page.

Beyond the First Click

If we’re playing in this real estate, we have to look beyond the first click to what might happen on the second and subsequent clicks. Scan patterns spread around more evenly on the page on return visits, without the very strong upper-left bias that tends to create the so-called “Golden Triangle” (so-called because we called it that). People tend to fixate on where the last listing clicked, and then can head out in multiple directions from there, either continuing down the listings, skipping up to take another look at the top sponsored, or even a quick glance across to the side sponsored ads. Whereever they choose, their interactions will now be colored by what happened in that first click.

Our strategy now has to account for the influence of that likely first click. We have to know how it will alter or reinforce the intent of our user. We also need to know how sticky the landing page behind that first click is. Is it the type of page that will hold him, and possibly send him off in another direction, or is it a quick bounce back to the SERP because it isn’t well aligned to our target’s intent? Does it reinforce our brand, or our competitor’s? What appears above the fold, and what appears below the fold? Again, we know from eye- tracking studies that this is the critical divide of the page in terms of scanning activity.

When one realizes the impact of pogo sticking, it suddenly means that our search strategy doesn’t play out in a vacuum. It’s intimately dependent on what else appears on the results page, and the most likely paths our target will take from that page. It increases the complexity of our strategy exponentially. The only way to successfully navigate it is to have a clear view of the intent of our target. Sure, it makes search marketing more difficult, but it also makes it infinitely more interesting!

What’s Up with Verticals?

First published July 27, 2006 in Mediapost’s Search Insider

You probably haven’t given a lot of thought lately to vertical search results, that thin sliver of search real estate that is sandwiched between the top sponsored ads and the top organic ads, and generally shows a few lines of news results, or local, or products. I have. Don’t panic, there’s really no reason why you should have. It’s really just a sad comment on my day-to-day activities. But I’ve noticed some things, and I think it’s incumbent upon me to share them with you. So let’s get vertical for a few moments, shall we?

In a Location Near You

First, this is prime real estate. When vertical results appear on the major engines, they appear smack in the middle of the hottest part of the page. After a number of eye tracking studies, we can say with a degree of certainty that most searchers (upwards of 80 percent) at least look at the top sponsored ads and the top three or so organic ads. That means that vertical, wedged in between, will be at least grazed over by a lot of eyeballs.

But position is not enough. Working the vertical angle is not just about grabbing some prime real estate. Verticals have to offer information scent. The information, links and visual cues they offer have to align with the user’s intent. In one bizarre example we saw during our latest study, somebody searched on Google for “digital cameras.” For some reason, Google saw fit to return news results for digital cameras. Now, just what percentage of the over two million people who searched for “digital cameras” last month (a quick estimate courtesy of Yahoo) do you guess would be looking for the scoop on how Nikon had to recall 710,000 digital camera batteries? Maybe the ex-product manager from Nikon, in between looking for new jobs on Monster, but that’s about it.

Hopelessly Devoted to OneBox?

While we’re on the subject, what’s the deal with Google and verticals anyway? Search pundit Greg Sterling said in a blog post some time ago that Google had an “almost religious devotion to OneBox,” its vertical label of choice. Could be, but it seems that a few in the temple of Google are questioning their religious affiliations. OneBox results have been a little sketchy of late. The reason this came to light is that I’ve just looked at 100-plus sessions in Google for a recent study, and there were surprisingly few of those sessions with OneBox results showing.

First of all, they hardly ever show for product-based searches. Try it for yourself. I must have tried over a dozen different common product searches before I got one that returned Froogle results via OneBox. Now why would that be? Well, for one thing, OneBox real estate competes with top sponsored ads, and perhaps advertisers are starting to resent the increased competition in their neighborhood for highly commercial searches. If that theory is correct, it flies in the face of Google’s goal to provide the most relevant results for each query, no matter what the source of the results. Another reason might be that Froogle has never really gained traction as a shopping engine. Maybe Google’s quiet dialing down the rate of appearance of Froogle results on the main page is their way of admitting that these results aren’t adding value to the user experience.

Doing Vertical Right

If you’re looking at a good example of Vertical execution, Yahoo seems to be currently leading the pack with its Shortcuts. The display of vertical results is consistent, and they seem to be one step ahead of the competition in aligning results with user intent.

Here are some examples we saw in a recent study:

One of the tasks given was to research the upcoming purchase of a digital camera. This resulted in a number of related queries being used, ranging from very general (“digital cameras”) to very specific (“Canon Powershot A530”). When these queries were thrown at Yahoo, the engine was able to differentiate and return appropriate vertical results. Broad generic phrases returned vertical results that compared known brands or allowed browsing by features. More specific queries returned links that led to reviews and best prices for that model alone. It was a great example of results matching intent, and we saw the interaction with these results go up dramatically as an example.

One very bright thing that Yahoo does consistently in its vertical listings is provide a 5-star rating scale. It appears for products, some local results (restaurants, hotels) and in various other places. When it comes to attracting our eye, nothing does the trick better than a visual cue that promises ratings. We love lists that sort from most popular to least popular. It’s the paradigm of the consumer researcher, and it’s something that reeks of scent. We saw eyeballs attracted to these icons like search marketers to an open bar (come on, I know many of you are already scoping out the cocktail network for San Jose).

A Vertical Future

I still believe that verticals mark a path into search’s future, but until the engines do better at disambiguating intent, either through personalization, behavioral tracking or just really smart key phrase parsing, they will be relegated to the thin sliver of real estate they currently occupy. Their success in luring users into what Sterling called a “Page 2” vertical experience will lie solely in how well they deliver on intent.

The Rule of Three in Search

First published July 20, 2006 in Mediapost’s Search Insider

Once again, I find myself up to my earlobes in eye-tracking data. I have no one to blame, as I got myself into this mess when I made the well-intentioned but poorly thought out promise to have the first draft of a study done by the time I head out on vacation at the end of the month.

In wading through the sessions (about 420 of them) sometimes new insights rise to the top–and sometimes my eyeballs just roll back in my head as my hands jerk spasmodically on my keyboard and drool runs down my cheek. Luckily, this week it was the former.

In this study, we are looking at interactions with Google, compared to MSN and Yahoo. Recently, one finding in particular seemed to be screaming out to be noticed. Being a compassionate sort of researcher, I listened.

When we looked at interactions with the top sponsored ads, there was a notable difference between MSN, Yahoo and Google. On MSN and Google, the percentage of clicks happening on these top ads seemed to be in line with previous studies done both by us and by others. But the amount of activity on the Yahoo ads seemed to be substantially higher. We started out by looking at first fixations, or the first place people looked on the page, even for a split second. Here, the engines were all in the same ball park, with 83.7 percent of first fixations in top sponsored ads for Yahoo, compared to 86.7 percent for MSN and 80.6 percent for Google.

Then, we looked at where the first activity on listing happened; where on the page did people start actually scanning listings? Google held a good percentage of eyeballs, keeping 12.4 percent of the users, while MSN had a significant defection issue, losing 36.6 percent of the people who first fixated in the top sponsored ads. But Yahoo lost the fewest, with only 5.5 percent choosing to look elsewhere. And finally, Google had 25.8 percent click-throughs on these ads, and MSN had 16.7 percent (yes, this is low, but MSN was dealing with a number of issues at the time of the study). Yahoo led the pack with a 30.2 percent click-through rate. In fact, for the first time ever in our research, a sponsored link (the number one top sponsored) out-pulled the No. 1 organic link, at click-through rates of 25.6 percent vs. 14 percent. This was a complete reversal of the click-through ratios we saw on the other two engines.

For whatever reason, Yahoo’s top sponsored ads seemed to be locking searchers into their part of the results page to a much greater extent than Google and MSN.

Why? What the heck was going on? Better ads? Not really. If anything, Google’s ads seemed a touch more relevant.

Location, Location, Location

Part of it was real estate. Another interesting comparison we did was to look at the percentages of screen real estate devoted to various sections of the page. Yahoo has gone out of its way to make the top sponsored ads the dominant feature on a results page at 1024 by 768 screen resolution. At this size, the ads take up 23 percent of the real estate, compared to approximately 16 percent for Google and Yahoo. This pushes organic listings on Yahoo perilously close to the fold.

And there, as I stared at the screen shots of fully loaded (maximum ads and vertical results showing) Google, MSN and Yahoo results at standard resolution, a possible answer revealed itself. On Google, three top sponsored ads, three OneBox results, and three visible organic listings. On MSN, the same three:three:three presentation. But on Yahoo, there were four top sponsored ads, three vertical results, and just one and a half organic listings were visible.

The Rule of Three

Hmmm, three, three and three. There was something there, niggling in the back of my mind. Quickly, I did a search for the “Rule of Three” and sure enough, there it was. We humans tend to think in triplets. Three is a good number to wrap our mind around, and we see it in all kinds of instances. We tend to remember points best when given in groups of three, we scan visual elements best when they come in threes, and we like to have three options to consider. Think how often three comes up in our society: three little pigs, three strikes, three doors on “Let’s Make a Deal,” three competitive quotes. It’s a triordered world out there.

So is it coincidence that search results tend to be presented to us, neatly ordered in groups of three? I think not. It strikes me that this engrained human behavior would probably translate to the search engine results page as well.

The Ruler-breaker

MSN and Google tend to adhere to the rule of three in their layouts (depending on whether or not Google serves three top sponsored ads). Our choices are conveniently presented in neat trios, with logical divides between each.

Yahoo breaks the rule by tipping the balance in favor of the top sponsored ads. First, it provides four results, not three. Does this mean we need to spend a little more time up in these results, trying to fit one extra one into our limited memory slots? That appears to be the case, with people spending an average of 4.6 seconds in the Yahoo top sponsored results in our study, compared to 2.4 seconds for Google and 1.73 seconds for MSN.

Second, it only gives us one visible organic listing to consider. It breaks our natural desire to have three alternatives, thereby reducing the Promise of Interest for the organic listings. In effect, on the screen of results most people would see on Yahoo, we only have one alternative, the top sponsored ads.

An earth-shaking discovery? Perhaps not. But cut me some slack. I’ve been looking at eye-tracking data daily for three months now, spending about three hours each day looking at interactions with the three engines. I think it’s time I took the three other members of my family on a three-week vacation, during which we’ll be visiting three countries. Wait a minute! Do I sense a pattern developing?

Dear Google Search History

First published July 13, 2006 in Mediapost’s Search Insider

In the 1600s, Samuel Pepys became history’s most famous diarist. From 1660 to 1669, this English Member of Parliament kept a detailed diary, which was published posthumously. In it, we gain a fascinating eyewitness account of the Great Plague and the Great Fire of London. Most passages were not so monumental, however. Here’s one example from July of 1663:

Up betimes to my office, and there all the morning doing business, at noon to the Change, and there met with several people, among others Captain Cox, and with him to a Coffee [House], and drank with him and some other merchants. Good discourse. Thence home and to dinner, and, after a little alone at my viol, to the office, where we sat all the afternoon, and so rose at the evening, and then home to supper and to bed, after a little musique.

Sounds like Sam pretty much polished work off by noon and spent the rest of the time drinking, gossiping, playing the ol’ viol and listening to some tunes. All in all, not a bad life! No wonder he had the free time to write about it.

The Diary I Didn’t Know Existed…

I never considered myself a diarist. I’m much too busy actually trying to get through my life to spend time writing about it. I suppose the odd blog post would be autobiographical, but other than that, I didn’t think I was leaving an account of my day-to-day thoughts. I was wrong.

Some time ago, I signed up for a Google Analytics account for my blog and at the time, I somehow activated Google’s Personal Search History function. Because I have a laptop, and tend to use the same computer at work and at home, I was unknowingly capturing a pretty complete snapshot of all my search activity. Just a few days ago, I realized I was still logged in. Today, I took a look back at two months of search activity.

…A Day-by-Day, Search-by-Search History…

First of all, in the past two months, I’ve searched 540 times. That’s an average of 9 searches a day. In looking at the log of day-to-day activity, I can pretty much tell exactly what I was doing, and what thoughts preoccupied me, on any given day from May 11 to today. The topics are a little scattered. In a one-hour period on June 5, I went from looking for what an average winning percentage was on Freecell (don’t ask), to looking up the details on a new business contact, to looking for a new design template for my blog, to looking for GPS software for an upcoming trip to Europe. Can you say attention deficit?

In a quick analysis of my activity, it seems that 59 percent of my search activity is work-related, and 41 percent is personal. Twenty-eight percent of my searches were navigational (I knew what site I wanted to end up on, and was using the search engine to get there) and 71 percent were what I call “mapping” searches (where I was looking for the search engine to suggest sites I was previously unaware of). And in 34 percent of my searches, I never actually clicked on a result.

…And That Was Just Mine…

The point is not to go on about how I search. You could care less. The point is that search history gave me a snapshot of just what I was thinking about, at an average of about nine times a day. In looking back, I could remember what I was working on, what products I suddenly thought I needed, how much planning I was doing for an upcoming vacation, what new acquaintances I suddenly decided to Google to find out more about, and what arguments needed to be settled. I’d see queries come up, disappear for a few days, then suddenly re-emerge later, either in the same or modified form. It made me realize how integral online is to my life, and how much I depend on search to connect me to the vast and diverse content that sits out there. It mirrored my thoughts about upcoming purchases, life events, things that were bothering me, issues at work and just plain old time-wasters.

Now consider the implications of this. I’m one person, who actually lived the life in question, and I was amazed by the insight gained by looking back. Consider this data in aggregate form. No wonder John Battelle was blown away by what he called the “database of intentions,” this gargantuan deposit of data that is owned by the search engines, providing intimate glimpses into individuals at the micro level, and incredibly granular macro mosaics as we step back. Based on the search trail and clickstream I looked at, Google, if it chooses to, would know more about me than my wife (keep the snarky comments to yourself). And remember, search history is just the data Google chooses to make public. Through the tool bar, it’s capturing a lot more clickstream data on you.

…What About Yours?

The whole “Big Brother” aspect of this has been commented on numerous times in the past. Sure, it’s frightening, but I think it’s tied up in the new reality of our online world. Is the fact that it sits in the hands of a private corporation any more troubling than the huge amount of personal information that sits in government files? Theoretically, we have democratic recourse with the government, but we all know how much weight that holds. Take some comfort in the fact that Google, with all its billions and resources, has exactly 1.5 people working in its sales and market research department (although I’m hearing rumors of a new addition). For the foreseeable future, Google might have a frightening amount of data, but it doesn’t have anyone with the time to look at it.
Read more: http://www.mediapost.com/publications/article/45508/dear-google-search-history.html#ixzz2ZoaFoUTS

Branded Terms in Search Results: Pre-Mapping in Action

First published July 6, 2006 in Mediapost’s Search Insider

Two separate occurrences in the last little while have lent credence to a behavioral occurrence we’ve seen in many of our studies.

First, I was sitting in on a meeting where an agency (not ours) was reporting on the performance of its sponsored search campaigns and was ecstatic with the performance of its branded term phrases, which were outperforming every other keyword bucket both in terms of click-throughs and conversions. While giddy with delight, company executives were at a bit of a loss to explain why.

On a similar track, a search marketing firm has recently released some results that looked at cannibalization of search campaigns when you are buying terms where you also hold top organic position. Again, they found this is most likely to happen when you’re buying branded terms.

While neither of these examples should be surprising to a seasoned search marketer, we’re all interested to know the reasons behind this interplay between organic and sponsored, particularly on branded terms. The answer, as it so often does, lies in looking more closely at what the search user is doing.

Pre-Mapping: A Theory

After looking at thousands of search sessions in detail, one thing is becoming clear. Searchers are incredibly adept at focusing in on just the portion of the results page that interests them. The time required to relocate to the prime real estate is literally a fraction of a second. Yet that real estate isn’t always the same spot. It varies depending on query and intent. It also varies by user, but even the same users will navigate the real estate of the listings in very different ways, depending on what they’re looking for.

Pre-Mapping supposes that we’ve interacted with search results pages enough to know the sections of real estate we typically deal with. We know where the top sponsored ads are and what they are. We know about where the top organic listings start. And in our minds, we already have a good idea of the type of site we’re looking for and approximately where we expect it to appear. Before the page ever loads, we’ve already mapped out the sections that would appear to hold the greatest promise to deliver on our intent. As the page loads, we do a split-second scan to get our bearings (orient in the top left corner, see how many top ads there are, see where organic starts) and then we go to the part of the map we’ve predetermined to be our best starting point.

Theory in Practice

Let’s run through a few examples. Imagine you’re looking for the possible side effects of a medication. The types of sites you would be looking for would be authoritative information sites, either the official site for the medication, a recognized health portal or possibly a government information site. In this case, you may be leaning more towards objective sites, rather than the pharmaceutical company’s own site. After launching the search (the name of the drug) you’ll quickly filter out, or thin slice, any commercially oriented sites. In this type of interaction, you’ve determined through pre-mapping that your area of greatest promise is not likely to be in the sponsored ads. You also expect the official site to rank No. 1 organically, so your area of greatest promise is probably in the No. 2 to 5 organic rankings, where you expect the types of sites you’re looking for to sit. In a split second, you’ve narrowed the real estate where you’ll start your active scanning to about 10 percent of the total real estate.

Now, let’s say you’re looking to renew your auto insurance. You’ve already checked out a few quotes online, but before you commit to any, you want to see how your current carrier compares. You’ve also pre-mapped the page in this case. Here, you expect your company to be bidding for the term ( “Brand Name auto insurance”) and because it’s a commercially oriented query, you assume that the sponsored listing would take you to a page where you could get a quote. Your area of greatest promise is the top sponsored ads. Again, you do your orientation scan to find your bearings in the upper left, but in this case, you would start right at the top sponsored link and work your way down the page until you find a link to the carrier in question that offers the promise of giving you a quote.

Theory Applied

Considering these two examples of user behavior, you can easily see what was happening in the two anecdotes I cited at the beginning of this piece. Brand terms will convert like gangbusters in the top sponsored location, because when a brand term is used, it’s very likely that the user has pre-mapped and is expecting to find that site in those top sponsored spots.

Similarly, you will find significant cannibalization because when users have pre-mapped, they start at the top and work down. They’ll hit the sponsored result before they hit any organic result that might appear. They’re looking for the quickest route, and in this case, the sponsored listing is giving it to them.

The likelihood to pre-map, and what this means for interaction for the page, lies in that deep dark place where all the answers to search engine success lie, the mind of your target prospect. Spend some time exploring it.

Google, Microsoft, Print, TV and other Thoughts on a Rainy Day

It’s raining and I’m not feeling particularly industrious, so I’ll push back the “To do” pile a little bit farther and catch up on some blog posts.

There’s been a lot of buzz lately about the search engine’s foray into the world of print advertising, and Tacoda CEO Dave Morgan tries to pinpoint where Google’s attempt to introduce an auction based model to print could have gone wrong.

One point put forth in the column (although not Dave’s) that’s worth considering is that an auction based market is a tremendously efficient one. It has little overhead and it allows prices to find their own sustainable levels, based on the value in the buyer’s mind. This worked well for search because it presented untapped value. There was no place for search to go but up. Which it did.

Print is another matter. It represents an entire food chain with an accompanying industry that subsists on it. That comes with built in inefficiencies and therefore, pricing inflation. Arguably, when introduced to an open, dynamic, buyer controlled pricing market, print had nowhere to go but down. Which it did. And that was the problem.

But Dave points to another issue, and that’s the significant differences between print and search. Search is driven by intent, which means that search interactions generally lead to a purchase event in the not too distant future. And each click is an expression of that intent, which makes it easy for markets to start assessing value to the click. This measurable value provides easy justification for the bid price. In fact, it’s this direct response approach to search that’s introducing many of the challenges we face in trying to quantify value to search touch points as we move further away from the purchase.

Print is a different animal. It’s often used for branding, a much less quantifiable objective, and it’s not clickable. There’s no way to immediately and easily assign value, which makes bidding a guessing game at best, rather than a provable strategy.

In the end, it comes to down to a number of factors, including underestimating the inertia of the print market, the fact that in a price inflated market, an auction based model will find efficiencies, not profit, and, once again, Google thinking that as soon as they enter a new market and affix a Google label, the world will change rotational direction to accommodate them.

And yes, there is a theme emerging in my posts. I’m not a Google basher. I like much of what they do, I like their cocky optimism, I love what they’ve done for search and deep down inside, I do hope they reinvent at least part of the way we do business (nods to John Battelle) but the fact remains that I don’t agree with their strategy of attacking everything at once. It’s not sustainable.

I was in an interesting conversation yesterday with a multi year veteran of the technology wars. He said that Google takes a typical engineer’s view of the universe, and that is in any model, including business models, the more points you have between the producer and the end consumer, the more friction that is introduced. Google’s view is that friction is inefficient and should be eliminated, disintermediated, freeing the flow to go direct. Other companies, through long experience, including Microsoft, have learned differently. Friction is good, friction is valuable, and friction is inevitable in a world populated by people, not machines. Each friction point is an opportunity to add value.

With the two different views of the universe, it’s interesting to note that Microsoft is looking to enter the offline world as well. They announced that their vision of adCenter is a multi channel platform, that will introduce an auction based model and search like accountability to other channels, including television and print. Boy, if you thought print was a tough model to crack, wait til you take on television! Google’s problem, says Microsoft, is that they didn’t understand the print medium. By the way, in this story near the bottom there’s a really interesting line that speaks of many blog posts to come:

Bradford also indicated that Microsoft was gearing up to compete with Google for employees. She said Microsoft hopes to lure staff from Google when the company’s stock options begin vesting next year.

But another post, another day.

I don’t disagree with introducing efficiencies in the ad buying market. I believe it’s long, long, long over due. And I love the idea of introducing more accountability. But everyone has to understand going in that this means the tearing apart of an existing and considerable power construct (or several) and reinventing from the ground up. That takes time and resources. It takes patience. It takes adoption. Each of these speaks to a strategy that will take a considerable time for execution and to turn a profit. The fact that everyone is jumping on the Google print experiment (including Google themselves) because it wasn’t profitable out of the gate is a little ridiculous. Did Google really think they were going to change the world that quickly? Did the analysts? Did we learn nothing from the Dotcom bust?

Speaking of Google and TV, there’s an interesting column over at iMedia by Alan Shulman about the Googleization of TV. Check it out.

Okay, the rain is stopping, I thinned a few items out of my “blog fodder” in box, my “To do” pile is inching closer and the hordes are starting to gather at my door. Time to get back to work!

American “Idol”izing Google Trends

First published June 8, 2006 in Mediapost’s Search Insider

Let me apologize right off the bat. I’m going to jump on a pop culture bandwagon, but I’m doing it to prove a point. Search trends reflect the interests of our society, and they can provide an invaluable way to gain intelligence about what’s on the public’s mind.

First of all, some facts to consider:

  • The most votes ever cast for a presidential candidate were 54.5 million, for Ronald Reagan in 1984.
  • On Wednesday, May 24, 63 million votes were cast in the final voting episode of “American Idol”
  • All votes for “American Idol” were cast in a 2-hour window. Typically polls are open for most elections for 13 hours, not including advance polling.
  • In “American Idol,” there was not one hanging chad.

Obviously, “American Idol” struck a chord with the public this year. Some say the final choice of Taylor Hicks was a surprise, but was it? With the help of Google Trends, I did a little forensic investigation and charted the rise in popularity of the contestants, as captured on Google.

A couple of caveats. Total search volumes are an approximation, as Google Trends doesn’t show actual numbers, and currently Google is only showing trends up to the end of April. But as you’ll see, for the purposes of this column, that’s enough.

I divided the contestants into three groups based on indicated search volumes: the Front Runners, the Also-Rans and the Basement Dwellers. I’ve included a link to the chart for each.

The Front Runners

Taylor Hicks started the strongest out of the gate, dominating search volumes in February during the early rounds. Although he lost ground to Kellie Pickler and Chris Daughtry in March, he came back strong in April, only being edged out in total volume for the month by Kellie, due to a surge in searches the week she was voted off.

Pretty boy Ace Young was No. 2 in February, but lost steam moving into March and never seemed to recover. Chris Daughtry was a slow starter in February, but built steam through strong performances in March. Unfortunately, he seemed to lose his edge in April, as search volumes started to drop from their high in mid-March.

The sleeper in this group was Katherine McPhee, who slowly built up steam through late February, March and April, with a huge peak towards the end of April.

If one was to predict outcomes based on search trends from February through April, I would have called it this way

1. Taylor Hicks

2. Katherine McPhee

3. Chris Daughtry

4. Kellie Pickler (one has to adjust for the spike on the week she was voted off)

Remember, this was almost a full month before the final show.

The Also-Rans

In the middle of the “Idol” pack was a group that just couldn’t seem to spark the interest of America, despite significant talent.

  • Lisa Tucker started off the strongest of the group, but could never seem to rise above the search volumes generated mid-February. There was no “buzz” around her. Kevin Covais, on the other hand, emerged out of nowhere and did build through February and March. It’s also interesting to note that when many of the contestants were voted off, their search volumes dropped off the Google trend radar. However, Kevin was voted off March 22, but kept showing up well into April.
  • Diva Mandisa started from nowhere, but generated some of the highest search volumes of all on the night she was voted off. Sometimes you don’t know what you’ve got till it’s gone. And poor Elliott Yamin didn’t have a chance. Despite a great voice (maybe the best, if you believe the judges) he just didn’t turn America’s crank. Although he built search volume slowly, he never emerged as a contender.

The Basement Dwellers

The three who were certified “buzz”-less were Paris Bennett (maybe she should change her name to Hilton), Bucky Covington and Melissa McGhee.

Paris started off hot right out of the starting gate in January, but never went anywhere from there. It seems we got used to the dynamic vocals, the pixie-like speaking voice and the cool hats–and ceased to care. Bucky and Melissa really only attracted significant volumes on the days they were voted off.

The point of this exercise is this. Search volumes do mirror public opinion, and can act as an amazingly accurate indicator of our collective interests. If you would have had access to search volume information, you could have called the results of “American Idol” long before the final show.

The other thing that was interesting was to see the power of community, both in the search results and the actual results. When you look at the top locations for searching, they are, in order: Greensboro, N.C., Charlottesville, Va., Raleigh, N.C., Charlotte, N.C. and Atlanta.

The North Carolina contingent was incredibly active in its quest for information on Chris, Kellie and to a lesser extent, Bucky, far out-searching the rest of the country for those individuals. The search demands for Taylor, Katharine and Ace were spread evenly throughout the country.

If you haven’t played with Google Trends yet, give it a spin. It can provide a fascinating glimpse into search buzz, and through it, what’s on our collective minds at any given time, on any given subject.