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Pixel Count: 32 Pixels. 27% More Signups.

30th Jul, 2012

At Agile Australia, Doug Blue from seek.com.au (Australia’s premier job search site) gave a great talk explaining elements of their product strategy and A/B feature testing. Doug included an example that perfectly illustrates just how much impact a few pixels can have.

Seek wanted to increase the number of people signing up for email alerts. This is not a primary task for a user looking for a job, its a second- or third-order goal. This means a balancing act between over emphasizing an action that’s not critical and having users miss a useful feature entirely.

The existing UI for the job search results page is pretty complex, providing the results themselves, refinement options for the search criteria and leaving some space for sponsored ads. I don’t have screenshots, but a sketch gives you some idea of the screen’s layout and the position of the link for email notifications:

Sketch of Seek results screen with A/B test.

Blue/pink/white are the colours of Seek’s brand. While there’s a often risk of bad branding over powering the information hierarchy on a page, Seek keeps it under control: blue for highlighted regions, pink for key information and calls to action. Even if you’re not a fan of the colours, the consistent use throughout the site works reasonably well.

In Option ‘B’ you can see just one small change. Taking the pink “call to action” colour, they added a 2-pixel stripe across the top of the envelop icon:

Closeup sketch of email icon A/B test.

Such a small change! Just a 2 by 16 pixels region. A total of just 32 pixels. On a typical laptop with a 13 inch screen at 1440×900 resolution, 32 pixels is an almost insignificant 0.0003% of the screen!

So, what was the measured impact? A massive 27% increase in signups. That’s almost 1% per pixel. If your UI is crunched for space, maybe you should consider measuring conversion impact per pixel and see how you compare.

One of the key attributes of visual processing is our uncanny ability to easily detect tiny amounts of contrasting colour. One theory of the origin of this ability relates plants and animals evolving in tandem for mutual benefit. As vision evolved and became able to detect colour, one key use was detecting the few ripe pieces of fruit in a forest of green. Plants evolved at the same time to paint their fruit brightly to entice animals to eat, encouraging animals transport their seeds. For the animal, improved colour vision became directly linked to how efficiently they could scan the jungle for a hint of blushing colour.

It may just be a theory, but its one that goes some way to explain why we are so good at detecting small contrasts in colour:

it is to the plants’ advantage to have its fruit remain un-eaten until the seeds are ready for dispersal, so the color change in ripening fruit is a signal that the plants are sending to the animals. In turn the animal gets the greatest benefit from eating the ripened fruit, so it is to the animals’ advantage to recognize when the fruit is ripe.

While the origins of “ripe fruit detection” may be hypothetical, there are many simple experiments that show its power today in many animals. Even lizards.

Whether or not Seek knew it, their A/B test was testing visual processing that’s evolved over millions of years.