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I’m going to be up at SMX Toronto / eMetrics Toronto in early April.  These are great conferences and you should go, too.

If you’re going to go, use this SMX discount code and save some Canadian dollars: SEDISCOVER15.

I’m going to be on a panel, so it’s not exactly a keynote, but it should be a fun discussion on important metrics for SEO and search in general.  What should you be looking at, how to interpret it, and how to avoid the pitfalls.

Here’s the description from the SMX Toronto site:

Search Analytics

[SA-2] Defining SEO and PPC Measures for Success
SEO and PPC campaigns offer unmatched opportunities for measurement, testing and refining. However, to fully take advantage of these opportunities we need to define the metrics, points of conversion, content consumption or actions completed that indicate success. In this session advanced SEM professionals will discuss how Success Metrics or Key Performance Indicators (KPI) are determined and show examples of how KPI are used both real time and historically to measure the efficiency of a campaign, the success of SEO, or the real time results of an integrated marketing program.

I’m doing a webinar next Wednesday, 2/24 at brighttalk (the date has changed!).  It’s titled “why the middle matters,” and I’ll be discussing how you can look at analytics to figure out why things are they way they are in your search campaigns.

Hope you can join me!  It’ll also be recorded, so you can watch it even if you miss it.

http://www.brighttalk.com/webcasts/8405/attend

The folks over at SiteTuners have been working on a great piece of technology for simulating eye tracking.  But be warned: it’s in beta and does come with a little bit of baggage so far.  But Tim Ash is one smart dude, and he’s out there gathering feedback on forums and blogs to make the tool a winner when it’s out for good.

People like tools like this because they are intended to solve arguments quickly.  We can use data from users or computer simulations to tell the bonehead CEO that his ideas of putting jumping pink kittens and 24 calls to actions are bad ones. And this is great, so long as the data is inherently valuable.

The trouble with AttentionWizard so far is that it evaluates web sites like you would evaluate photography or art, using design concepts like contrast, weight, etc., with an obvious dose of “top-leftedness,” meaning that the tool anticipates where headers and text would start and shows greater focus there. And it is also seemingly weighted heavily toward identifying outlier colors.

But that’s not exactly how people evaluate web sites. The classic example is banner ads and how conditioned people are to avoid them, regardless of how bright and obnoxious they are.  In AttentionWizard’s demo video, you can see this error in their demo of 1-800-flowers.com, where the house ad gets a lot more attention than it would in the real world.

But to be fair, this demo does reach good conclusions, and you can see how much more straightforward the end result is.  But the point is it reaches good conclusions with the wrong data.

Unfortunately, we live in a phase of web analytics where most of the tool data is taken at face value.  So, people see a heat map and believe that’s reality.  Or they get a report about keyword performance and assume that keyword A is better than keyword B, just because it has a higher ROI (but without seeing if the landing pages make sense, if the prices are competitive, and on and on).

Tim makes great points on his site about what this tool is and isn’t, but right now that’s like John Stewart making points about how his political opinions are just his own: it’s irresponsible because it ignores how powerful credible sources are, and to both Tim and John’s credit, they are credible sources because of their history (and charm, of course!).

Below, I’ve shown a few demos of where AttentionWizard deviates from human behavior so radically that it can actually drive the wrong decisions.  And I’m not trying to show pictures of half-naked women or anything that the tool shouldn’t or couldn’t technically be capable of, because I do think that’s an unfair test.

Test 1: Pattern recognition

Here’s one that humans will get right away.  Just try to take your eye off of the star.  AttentionWizard didn’t get it at all.

In the world of the web, this is important for low-contrast sites that might use shapes and graphical weight to point things out.  We probably won’t see an example this simple online, but it is possible. I’m envisioning package design – you see 11 identical-shaped shampoo bottles on Amazon.com and one crazy-shaped one.  Where does the eye go?

Test 2: Position-sensitivity

So here’s one where I’ve placed calls to action at 1150 pixels.  This one tests to see whether the tool will hold up to the boardroom when someone says, “See, people will see this button at the bottom of the page!” Unfortunately, it seems that the tool isn’t yet sensitive to where things are and what screen sizes are most popular, which is definitely something that needs work before AttentionWizard is ready for its close-up.

I think this is an easy win for the tool – something that shouldn’t be too tough to change.

So Tim is to be applauded on creating a great technology.  But I would strongly urge people to not circulate the data it renders quite yet, not because the tool is bad, but because data is notoriously misinterpreted in the average company – taken for face value.

People can caveat their tools all day long, just like Charles Barkley could say he was not a role model, but we have to be responsible to the real world and produce things that don’t send mixed messages with the expectation that people are smart enough to filter the data.  They aren’t.  Not yet.