He shows that form conversion increased 25-40% for the mad libs style form vs. the standard style. Credit to Ron Kurti for the vast.com test.

Other tests have been conducted with similar results, and it might be worth the effort to test this against your standard forms to see how well it does!

This raises an interesting question: How often are we guinea pigs affects the results of an online experiment?  I feel important.  The Wired article sums it up nicely:

Today, A/B is ubiquitous, and one of the strange consequences of that ubiquity is that the way we think about the web has become increasingly outdated. We talk about the Google homepage or the Amazon checkout screen, but it’s now more accurate to say that you visited a Google homepage, an Amazon checkout screen. What percentage of Google users are getting some kind of “experimental” page or results when they initiate a search? Google employees I spoke with wouldn’t give a precise answer—”decent,” chuckles Scott Huffman, who oversees testing on Google Search.

Obviously, these companies (Google, Amazon, eBay, Netflix) are conversion machines. They have very specific and measureable goals and tons of traffic volume to gauge how well those goals are being achieved.

They’re doing a fantastic job of evolving their sites, and it’s probably because they have lots of resources working on test optimization along with user experience and design specialists as the sites morph over time.  They’re doing such a good job, you don’t even know you’re being subjected to a test and as the sites evolve, the changes all seem logical and consistent.

Testing needs to be balanced with design strategy.  Most sites started with a design concept for a reason.  Ideally this concept was based on user research or performance from previous designs.  Testing ensures continuous performance improvements and insights are generated, but since tests are most often performed on small, isolated sections of websites, user experience professionals need to be included in the evolution of the site to ensure consistency across the full design.  If they’re not part of this process, it could create design islands (can I say that?) within a site that disrupt the user experience.  If a green background works best for a test on product page A, a red background works best for a test on product page B, and a blue background works best for a test on product page C, despite those discrete winning test results, it might not be best to implement different color styles to individual product pages.

So keep on testing, a lot, but be sure to consult your user experience folks and designers to prevent design islands.

I’ve had runners knee for 7 years, and recently it’s been worse.  My knee is always the reason I stop running, not physical exhaustion or muscle aches, just that annoying pain in my knee.  The longest run I’ve completed recently was about 2 miles, I was wearing a knee brace to help, and my knee started hurting after 1 mile.

After reading the benefits of barefoot running in Born To Run, I bought a pair of Merrell Barefoot Trail Glove shoes and tried them out this weekend.  The shoes are really flimsy, and have almost no support, so you really feel the ground when you run.

First test: I ran one mile yesterday with the new shoes and no knee brace, and the only pain was in my calf muscle since I was striking the ground closer to my toes. I followed the techniques he describes in the book: I kept my head high, waist pushing forward, short strides, and even tried to smile a bit. Zero knee pain.

Second test: I ran 3 miles today.  My calves were still sore from yesterday, but after 1 mile they loosened up and felt fine.  I stopped after 3 miles because I don’t want to push myself too quickly, but it was another success. No knee pain.

I can’t wait to add longer runs to see if my knees are still pain-free. I wish I read this book years ago!

UPDATE: I went for my 3rd run in the new shoes this morning (day 5) and ended up running 5 miles with zero knee pain. It looks like the shoes and new running style have made all the difference, case closed.

Ok, one last update.  It’s been three days since my last run, and I just ran 11 miles with zero knee pain.  Previously, my longest run ever was 6 miles. I’ve never going to put on regular running shoes again.

http://www.collectiveintellect.com/blog/brand-tracker-super-bowl-2012

http://caseyshead.com/2012-super-bowl-squares-odds/

Using six years of game data, you can see the probability of winning for each combination.  My zeros and ones don’t stand a chance.

Today when I visited the page I noticed a different message.  A large set of sample reports was visible, but disabled, and to enable them I had to upgrade.  I thought this was a great way to show visitors what they would get if they upgraded.  Upon going back to the page a few different times, I noticed they were running a A/B/C test with three different versions.  Below are the three versions, and I have my money on long version with the sample reports (Version A).  Version A also drew my attention because the top of it was above the fold and it made me scroll down to see what else was there.  Versions B and C and straightforward and visually caught my eye, but I think the transparency Version A provides is more effective.

I hope we see the results of this test if one of these versions eventually gets rolled out!

A/B/C Test on LinkedIn's Recently Viewed Page

Version A (Baseline):

Version B (Variation – Improved signup by 60%):

The case study mentions that having the form on the page is “best practice” because it doesn’t require two clicks (1) clicking the button to get to the form, then 2) completing the form).  I actually think B is much higher performing because it’s communicating the value proposition in a straight forward way without a huge eye-catching form on the left.  I would like to see another test with the form fields below the text in version B without a big blue box

The longer you wait to test in order to review, revise, get buy-in, socialize, justify, align, blah, blah, blah, the longer you wait to find out what works.  Assuming you have decent volume, tests usually have to be in market for just about two weeks.

Organizational alignment is important, but the quicker you test, the quicker you’ll find out what really works.

C = 4m + 3v + 2(i-f) -2a ©

C = Conversion probability
m = Motivation of visitor
i = Incentive to take action
f = Friction elements
a = Anxiety

The likelihood of conversion increases when users are motivated to take action, are presented with a clear value proposition, an attractive incentive to take action, and when friction and anxiety are addressed and reduced.  The relative importance of each attribute is indicated by the numeric coefficient in the formula.  I think this is a great way to evaluate what to improve when reviewing an experience.  The art of testing is still required, but this heuristic keeps reminding us of the important attributes to consider.

MECLABS created this formula, and here’s an example of how they have applied it.  They have dozens of examples of how it’s been applied in practice, and I’ve started to use it for my work too.

Thanks MECLABS!