We may have the answer in a patent granted to Google today. That answer, if it is indeed the route Google is taking, is eye tracking. The patent is “Unlocking a screen using eye tracking information.” The abstract says:

Methods and systems for unlocking a screen using eye tracking information are described. A computing system may include a display screen. The computing system may be in a locked mode of operation after a period of inactivity by a user. Locked mode of operation may include a locked screen and reduced functionality of the computing system. The user may attempt to unlock the screen. The computing system may generate a display of a moving object on the display screen of the computing system. An eye tracking system may be coupled to the computing system. The eye tracking system may track eye movement of the user. The computing system may determine that a path associated with the eye movement of the user substantially matches a path associated with the moving object on the display and switch to be in an unlocked mode of operation including unlocking the screen.

The following diagram from the patent explains an example process of how this could work:

If you want to read a lot of patent jargon, you can do so here.

[via Hot Hardware]

Tobii in collaboration with their research partner AnswerLab were using their new X1 Light Eye Tracker technology to showcase the main benefit of the new product to researchers. They found their samples at a San Francisco coffee shop and asked them to participate in a study that would have them looking at dating profiles of the opposite sex according to All Things D.

The test had participants viewing mock-up pages at eHarmony and Match.com. After thoroughly perusing the results, they came to a few interesting conclusions. Men spent 65 percent more time than women did reviewing photos in profiles. Women spent about 50 percent more time than men reading the text of a person’s background and interests.

Women spent an average of 84 seconds looking at a profile to find out if the profile was to their liking, compared to 58 seconds for men.

The study also found that people tend to relate better to dating profiles that reflect how they would build their own. If a person would share a lot of personal information about themselves, they were more likely to search out the profiles that were very personal. On the flip side of that, people who don’t like to share much about themselves went for the profiles that were just straight facts without much elaboration.

This is just the first test in many where Tobii will be testing their new eye-tracking technology. The eye tracker can pinpoint exactly where a person’s eye is looking within a centimeter. They will be using the X1 Eye Tracker in more scenarios to demonstrate how researchers can use it to obtain accurate results.

They also feel that their studies may help dating sites develop a better interface for their users.

The test involved 40 people which is a decent sample size. They will be conducting further research to demonstrate their eye tracker’s capabilities to the market research community.

Google of course obtains this knowledge through extensive eye tracking research. The company has a post up today revealing some findings from their latest efforts in this area.

"Based on eye-tracking studies, we know that people tend to scan the search results in order," says the post written by User Experience Researchers Anne Aula and Kerry Rodden. "They start from the first result and continue down the list until they find a result they consider helpful and click it — or until they decide to refine their query. The heatmap below shows the activity of 34 usability study participants scanning a typical Google results page. The darker the pattern, the more time they spent looking at that part of the page. This pattern suggests that the order in which Google returned the results was successful; most users found what they were looking for among the first two results and they never needed to go further down the page."

One interesting finding, which Google’s Universal Search Team considers a success is that even on results pages where there are images embedded further down the page (such as in the example below), people still generally look at the results in order. There was concern that perhaps the images would capture users’ attention first. I believe I looked at the images first myself though, so I don’t know, maybe I’m a weirdo. Their findings would suggest that I’m not in the majority either way.

"For the Universal Search team, this was a successful outcome. It showed that we had managed to design a subtle user interface that gives people helpful information without getting in the way of their primary task: finding relevant information," the post says.

They note that Google is conducting similar eye tracking tests with image search and Google News. They have discussed such testing with different features in the past as well. Overall, such tests theoretically lead to enhanced usability of products. The results found for SERPs, will make people strive to get that number 1 ranking all the more.

We who are to any degree, professionally involved with the search engine and technology industries often take things for granted. We know what certain words and phrases mean, and often expect others to, when the reality is that they don’t. I’m not saying I’m the smartest guy out there either. I am constantly looking up words and phrases myself (just one of the many useful yet simple features Google offers).

Google has acknowledged this though by making its advanced search tool simpler. Search Quality Researcher Daniel Russell says at the Official Google Blog:

Armed with this insight from field studies, we redesigned the page, simplifying it by removing terms that were unclear to the average user (the word "occurrences," for example, just didn’t mean anything to many of the Advanced Search page users), moving rarely used features (numeric range searches, date searches, etc.) into a part of the page that was expandable with a single click. That made them easy to get to for people who knew they wanted to search with those restrictions, but out of the way in a non-threatening way.

One of the other things we noted in the field study was that people often didn’t understand how the Advanced Search page worked. So we added a "visible query builder" region at the top of the page. As you fill in the blanks, the box at the top of the page fills in with the query that you could type into Google. It was our way of making visible the effects of advanced search operators.

The product of redesigning the page looks like this(you can see the old version here). That wasn’t what the whole field study was about though. In Google’s ongoing quest to improve search quality, they observed people’s search habits, and found that in the end, while some of the information retrieved was useful, much of it was unreliable. In other words, when people are being watched by researchers, they act differently than they would otherwise.

Eye tracking was an additional component of the field study. They provided an interesting look at this with the following video. The red dot in the video represents the movement of eyes on the page for three different users.

I suggest reading Russell’s post in its entirety to get a better feel for the kind of research he has been doing. In fact, his post is really only the latest in a series on search quality from the Google Blog. The series itself is definitely worth checking out for gaining insight into Google’s search quality quest.

How a subject views a book page, a store display, an advertisement or other visual stimuli is measured using sophisticated tools that track eye scan, also called eye movement. These tools measure which design elements capture visitors’ attention and which don’t.
 
Eye tracking is used in virtually every kind of marketing – TV ads, billboards, product packaging and web sites – to determine what works and what doesn’t with consumers.

What Does a Visitor See on Your Site?

The layout of a site page is scanned differently by each visitor based on individual perception, interest, need, age, education level, computer monitor, browser settings and other variables that can be tracked in empirical, eye tracking studies.

The results of numerous eye tracking studies  have been quantified, enabling web site designers and owners to optimize site pages for maximum impact and “stickiness.”

Single- and Multi-Variant Testing

Single-variant testing involves changing one site element and measuring the impact on conversion rate, for instance. Multi-variant testing employs a series of simple A/B comparisons conducted simultaneously or sequentially depending on what’s being tested.

Using statistical analysis, and eye tracking data across broad-spectrum demographics provides numerical sums based on number of observations and length of observations of different elements on any site page. That’s something you want to know. What captures the attention of site visitors? What is ignored?

Single-variant testing is the simplest to initiate and track. However it’s time-consuming and may lead to unsubstantiated conclusions. Multi-variant testing is a more efficient means of determining which site appearances and features deliver optimum results, i.e. the highest conversion rate.

However, multi-variant testing is more complex than changing a single variable and waiting to gather the A/B test results. It could take months to optimize a site for conversion. Further, single-variant testing often requires the tester to make certain assumptions that may or may not be true. 

For example, a change in type font shows a boost in conversion ratio. Is it logical to assume the change in font style is responsible for the improvement? No. In fact, this fallacy is called “post hoc ergo propter hoc” in the world of statistical analysis. Roughly translated, it means “after this therefore because of this.”

Simply because something occurs (an improvement in conversion rate, for example) after a single-variable change has been made (the change in font) does not mean that the improvement in conversion rate is due to the font change. The improvement could be based on another factor entirely.  

Planning Your Test Model

“If you don’t know where you’re going, any road will take you there.”

If you blindly (or wildly) change design elements without a thought to site improvements,  all you’ve done is collect a lot of data. In order to determine which changes to a site improve conversion rates, it’s important to first define what you’re looking for – your test metric. What site element or elements will be compared?

Next, in order to develop useful data, you must determine how you’ll measure and compare functionality. What methodology  or “conventions” will you employ to determine a reliable outcome?

And finally, you must be able to develop a strategy that optimizes site success, however that success is defined by you. Here’s an example.

Let’s say you want to determine which checkout software is better for your bottom line.

Before you can conduct your test, you must first create a test metric – a measurement that defines the term “better” in your query:  which checkout software is better?

You might determine the test metric to simply be the number of visitors who convert. That’s easy to measure, but it may not provide the complete picture. Perhaps a more useful measurement of which checkout software is better is the dollar amount each visitor spends. Or the number of repeat buyers you see. An increase in the number of page views, number of unique visitors or a jump in bandwidth, indicating an increase in downloads from your site – all of these are reasonable test metrics depending on your mission.

This leads to the next step in developing accurate statistical analyses: how will comparisons between the A/B elements be measured or quantified. What test “conventions” or methods will be employed? Will you count all site visitors in the study – even those that bounce – or will you limit the test pool to those who actually put something in their cart? Or actually reach the checkout but abandon the shopping cart? Or actually complete a transaction? Determining the methodology of your single-variant or multi-variant testing prevents jumping to unsubstantiated conclusions.

And finally, what steps can be taken based on the test results you develop? If you can’t answer this last question, why are you going to all the trouble to conduct the test and collate the data? If you get result Y, what can you do with that information versus result Z? This is where statistical analysis is turned into a practical, organized strategy for improving conversion ratios.

Once the test metric(s) and conventions are established, you run an A/B comparison test using the two different checkout models.

Checkout A requires two clicks to complete a transaction. Checkout B requires six clicks to complete the same transaction. Your test results reveal that the more complicated checkout model leads to a higher percentage of shopping cart abandonments. So can you assume that checkout Software A is better than Software B?

If your test metric was a simple count of software usability, Software A is the clear winner. But what if your test metric was to determine which checkout software led to the highest “per visitor” purchase amounts? And test results reveal that checkout Software B delivers fewer purchases but purchases of higher value. In this case, Software B would be the better choice. That’s why it’s essential to determine each test’s metrics and  conventions.

Measurement Tools

There are a lot of software packages to help in gathering test data. One, called Crazy Egg provides different GUIs of site activity – an overlay view, a list summary and even a heat map showing what’s hot and what’s not on your site. Easy and effective analysis.

Another popular conversion rate analysis software is Click Density, which provides real-time visitor data to help improve everything from content architecture to link placements.

Click Tale tracks every movement of visitors as they move through your site. This data is then translated into animated graphics to help you understand visitor behaviors from the time they arrive until they leave.

Finally, consider using Google Analytics – the simplest statistical analysis tool available. And it’s free. Google Analytics provides snapshot views of your site’s activity, allowing you to perform tests and analyze data in seconds instead of spending hours poring through report after report.

The point is this: to improve site conversion rates requires an understanding of eye tracking and statistical analysis to produce a useful optimization strategy. The hit-or-miss approach is simply too time consuming. So, if statistical analysis makes you light-headed, hire a professional who can design and validate test metrics and translate those findings into actionable strategies.

That’s how you improve site performance systemically and efficiently.

If It Looks Like An Ad They Ignore It

Editor’s Note: Studies are great and all, but sometimes real-world examples are more powerful. Have you recently redesigned your site and seen drastic results? Let us know how you did that in the comments section.

Usability expert Jakob Nielsen, who’s been studying how people interact with webpages since there were webpages to interact with, follows up on previous explorations to show once again that people not only ignore content that looks like advertising, but need things plainly spelled out for them.

The task was simple enough: find the country’s current population. Nielsen even gave them the website to use. But 86 percent of users failed to find the answer even though it was displayed in large red letters in plain sight.

"Users tend to ignore heavily formatted areas because they look like advertisements. Thus, about 1/3 of users never even saw the Population Clock. However, most people did fixate on this area because it’s not as overly formatted as most promotional features. So, most users saw the Population Clock; they just didn’t use it, even though it contained the exact information they were looking for."

Okay, so a third doesn’t exactly make up 86 percent. Why did the others fail when, in my grandmother’s language, if it was a snake it woulda bit them? There are many reasons, but a large chunk of it, says Nielsen, lies in the language.

Most users scanned the big red number U.S. 302, 781, 150, as of today, but only made it to 302 before skipping off to the search box labeled "Population Finder" or some other area. (Or in one case, a man after my own heart, frustrated with poor site search, said "forget it, I’m going to Google.")

The big red number was labeled "Population Clocks," which isn’t exactly an intuitive label. It sounds more related to time than it does to number of people. It’s a classic case of leveraging core competencies rather than using your strengths. As users didn’t automatically grasp what a population clock was, they skipped it.

The suggestion here then is that a simpler label of "Current US Population" would have worked much better, giving the user what the user expects, which is the end goal.

Andy Beal, editor and Internet marketing consultant for MarketingPilgrim.com has another take on it, which might make sense to you. Users may have taught themselves not just the look and feel of advertising, but also the location of advertising.

"The study demonstrates that it’s not just paid ads users are filtering from web sites, but areas that might contain ads. Web users are conditioned to focus on the main area of a web site, when looking for meaningful information.

"They’ve been taught that the areas to the left or right are typically reserved for navigation or advertisements. As Neilsen suggests, it’s important to make sure important information is located in the area of the web page users expect to find it." 

If It Looks Like An Ad, They’re Not Looking At It

"[Y]ou should bid less for network ads than for customized ads that you place yourself," Nielsen concludes, as nobody’s looking at the advertising network ads anyway.

This was among other conclusions, as well as an admission of secret knowledge – the "if this falls into the wrong hands" type Nielsen’s kept under wraps since 1997 for ethical reasons.

His exposition generate from an eye-tracking study that shows fairly conclusively that Internet users have learned to completely ignore ads on webpage and even real content that looks like an ad.

Nielsen provides video from the study as well, both in 19-seconds of real time and one minute of slow motion – pick the slow-mo one, as the normal speed one is impossible to follow.

In that video, the subject ignored ads altogether, automatically judging them as an impediment to completing the task.

"If users are looking for a quick fact," he writes, "they want to get done and aren’t diverted by banners; and if users are engrossed in a story, they’re not going to look away from the content."

Therefore, advertisers have three options when designing their advertisements, three techniques nearly guaranteed to earn a look in the ad’s direction. (Actually, there are four, but the fourth one is for those lacking some scruples. We’ll get to that later.)

The three most effective ad design elements are:

·    Plain text
·    Faces
·    Cleavage and other "private" body parts

Apply to affected area, as appropriate.

The study mirrors other studies done on the subject, even ones dating back to 1997, which showed, Nielsen begrudgingly admits, that banner ads that mimic computer dialog boxes – with fake exit buttons that take you to the advertiser’s website – were clicked often by users.

Make no mistake though, this creates a negative association with your brand name, as this deceptive method is in the top 3 of the most-hated advertising tricks.

Nielsen didn’t want to tell us, but figured the word would get out eventually. However, he does manage to turn that knowledge into practical advice that stops short of crossing ethical boundaries.

The key takeaway from that is a reversal of the notion that if users don’t fixate on content that looks like advertising, they will give a gander at advertising that looks like content.

Of course, this is fraught for potential for abuse, and violates traditional publisher "church and state" separation of ads and content. And reputable outfits don’t allow ad insertions that match their templates.

"But, to maximize fixations, that’s exactly what you should do in a Web ad." Judging whether a particular ad crosses the ethical line may one day decided by a tribunal like the one that decides on human experiments, but until then, it may remain a gray area.

Given the blindness to things that look like ads, though, Nielsen recommends away from building ad networks. 

Baidu Rivalry

A “preliminary full report” is available through Enquiro, and even the summary, posted by Hotchkiss on Search England Land, is over 2,000 words.  By this, I mean to say that there’s a lot of valuable information, but you’ll need a fair amount of time to process it.  We’ll just be hitting the highlights here.

In short, it appears that, compared to Baidu, Google offers Chinese searchers a more efficient experience.  The heatmaps’ hot spots are more condensed, and Hotchkiss notes, “In our study, an average interaction with Google.cn lasted about 30 seconds, and with Baidu over 55 seconds.”

A blind test between Baidu and Google, conducted by another company, even found that Chinese users might prefer the American offering.

So why is Baidu’s market share three times the size of Google’s?  Well, we’re moving away from those heatmaps, but Hotchkiss’s ideas are entirely plausible (and are backed by evidence).  “There’s a strong preference for a true Chinese search experience,” he writes.  “I noticed in a blog that picked up our very early findings that several Chinese users commented that they use Baidu because it is Chinese.”

Then there’s the matter of entertainment, the one area of the blind test in which Baidu beat Google.  “Baidu is the primary vehicle to locate and download free MP3 files,” states Hotchkiss.  “This generates a huge amount of traffic, as this is one of China’s most popular online activities.  There’s no way of knowing what Baidu’s search share might be if you separate the MP3 traffic out, but my suspicion, backed by a conversation with Piewen at Microsoft, is that it would drop dramatically.”

These findings may not help Google much, but they at least help explain how and why the search giant has been minimized in the Chinese market.

Instead, we should represent numbers with numerals – a recent eye-tracking study suggests that they’re much more likely to capture online readers’ interest.

“[N]umerals often stop the wandering eye and attract fixations, even when they’re embedded within a mass of words that users otherwise ignore,” revealed Jakob Nielsen.

So if I was, for example, pointing out problems with a certain American car company, Nielsen thinks it’s best to write that the 2000 Ford Focus was recalled 14 times – not “fourteen times.”

Nielsen is in a good position to know this sort of thing – he’s a co-founder and principal of the Nielsen Norman Group, which, in turn, describes itself as “an expert on corporate culture and the human-centered product development process.”

As for my complaint that Nielsen’s advice goes against several well-regarded style manuals . . . well, “the guidelines for online writing differ from those for writing for print,” he pointed out.

It seems best, then, to let numerals rule the day, but with the provision that common sense and courtesy to your readers should still prevail overall (“Two trillion is better than 2,000,000,000,000 because most people can’t interpret that many zeros,” wrote Nielsen).

This new guideline wouldn’t have pleased William Strunk Jr., but E.B. White, at least, might approve.

In conducting the reserch, Poynter enlisted nearly 600 regular readers in four markets, which is a pretty good sized sample. They gauged the eye patterns of readers from the Rocky Mountain News in Denver, The St. Petersburg (Fla.) Times, the Star Tribune of Minneapolis and the Philadelphia Daily News.

The complete report of the study’s findings won’t be released until June, but Poynter has already come forward with some very interesting findings. Here is a complete overview of the online attention span study.

One of the major findings from the eye tracking study centers on amount of text read for online readers versus print readers:

People in our study selected what they wanted to read, of course, and then … they read a lot! We were amazed by these numbers.

A big surprise was that a much larger percentage of story text was read online than in print.

To look at a comparison, on average, online readers read 77 percent of what they chose to read. Broadsheet readers read an average of 62 percent. Tabloid readers read an average of 57 percent.

For a medium that’s notorious for producing users with short attention spans, it appears that the Internet is actually more conducive to reading than originally anticipated. The continuous flow of web pages may have something to do with this trend, as readers aren’t plagued by the spacing limits of traditional print publications such as newspapers and magazines.

Another theory is that online readers are, by nature, more focused on seeking out material. Your average household has a newspaper delivered daily and reading it is more an act of leisure at the end of the day, whereas surfing for news online reflects a mindset of greater intentionality.

Format also played a large factor in story retention:

The prototype portion of our study showed the value of alternative story forms as they related to comprehension and retention of information. By alternative, we mean things like a Q&A, a timeline, a short sidebar or a list.

Subjects were asked to read one of six different versions of a story about the spread of bird flu.

At the end of the test, subjects were quizzed about the story in an exit interview.

In both the print and online, subjects who answered the most questions correctly had read the version of the story with the most alternative structure — no traditional narrative.

This offers an even greater incentive for online content producers to continue developing new and innovative ways to deliver story items to readers. Print journalism is pretty much locked in to its particular delivery format, so Internet publications should continue looking for alternative methods of developing content for readers, as the Poynter study reflects increased interest and retention in that regard.