It’s pretty much common knowledge: Web developers hate SEO experts. In all fairness, however, the feeling is mutual. But there are some good reasons for this culture clash.
“Same Thing” Sickness
One thing that SEO’s hate about web developers has to do with the way they execute or fail to carry out a very specific request.
A case in point: An SEO requests a developer to create a 301 redirect between pages. The developer does a meta-redirect or a 302 redirect citing that it’s the “same thing”.
From the developer’s perspective, it’s the same thing for the user, but from an SEO standpoint, it affects the search engine rankings.
The Death of Optimization
Developer skills and SEO techniques go hand in hand, so when if a developer fails to do their job, then it doesn’t matter what the SEO team does. Even with a copy of Google’s secret algorithm in hand, the site won’t rank if the site won’t work.
A case in point: A client implements some redesign elements. Suddenly, traffic drops by 30%.
The problem: Many of the pages don’t load like they should and the ones that do load show 500 server errors. The developer failed to spot the errors during the development process.
The result: 3 weeks of seriously diminished traffic.
The “I Know SEO” Syndrome
This is a contagious disease that developers get that can quickly spread to other developers. If you have ever heard a developer say something like I’m pretty good at SEO, it can usually be translated into I’ve read a little about SEO and therefore I pretty much know more than you do.
But wait a minute, SEO’s. You aren’t immune, either. There is a related syndrome called “I can code”.
A case in point: An SEO expert successfully builds a Word Press site and suddenly deems themselves a web developer.
The Real Problem
At the root of the culture clash between coders and SEO’s are their driving philosophies. Business classes that teach search engine optimization focus on uniqueness. After all, differentiating yourself from the competition is a good thing. On the other hand, computer science classes center on making everything the same. Each discipline takes a different approach to reaching the same result: stability and efficiency.
Like any other art form, web design is completely subjective. A web site might look like a thing of beauty to one person, and a complete mess to another person. There is, after all, no accounting for taste, and everyone’s tastes are different. However, there’s more to a web site’s design than merely its appearance. A web site design can have an enormous impact on conversions and even the most subtle design decisions can have a big effect. For example, a user might be more inclined to click on a green “Buy Now!” button more so than a red one. Finding a good balance between a site that looks good and a site that performs well in terms of conversions can be a real challenge.
How then can something as subjective as web design be analyzed in an objective manner to find the most effective design? One widely technique is A/B testing. In a nut shell, A/B testing sets up two or more control groups: Group A will see one version of the site, while Group B will see another version. This way various design elements can be tested and compared.
But is A/B testing really the best way to determine the most effective web design? Perhaps not. This excellent blog post by Steve Hanov suggests another method for finding the best design. Best of all its fully automated. Set it, forget it, and the page will “learn” which elements result in the most conversions.
In his post, Steve outlines the epsilon-greedy algorithm, also known as the multi-arm banded problem. Given a set of variations for a particular page element, the algorithm can make an ‘educated’ decision on which element to show based on its past performance. The best performing page elements are displayed the most frequently.
The algorithm records of the number of times a particular page element was displayed, and the number of times the element resulted in a conversion. However, the algorithm will also adapt to change. If a page element’s conversions begin to decrease, the algorithm will start to adapt and display different variations. The best part of this is that you can set up different variations of page elements one time, and let the computer do the work of figuring out which variations are the most successful. Pretty neat stuff!
Armed with this knowledge, I set out to try a few experiments with it, the result of which is Robo_AB_Tester, a small PHP class library I created which implements the epsilon-greedy algorithm. You can give it a try here.
Robo_AB_Tester tries to abstract away as many implementation details as possible and create a simple interface that is, hopefully, easy to integrate into a PHP based website. Once it is set up, it will:
For more details, see the demo page.
