The 3 Levels of Conversion Rate Optimization Maturity

If you’re reading this article, I hope you realize that split testing is no longer optional if you want to increase the performance of your web site. So, what is split testing? It’s simply presenting different versions of content to different visitors and measuring which version of your content gets the most desired results. Here are what I consider to be the three levels of conversion rate optimization maturity with an emphasis on split testing.

1 – Lowest Common Denominator

The first level of conversion rate optimization maturity is what I like to call “Lowest Common Denominator Split Testing”. This means treating all of your visitors the same. You simply split test all of your traffic together and see what performs best.

Not so long ago, if you were doing any split testing, you were ahead of the game since most of your competitors weren’t. That’s not the case anymore. I’m willing to bet the vast majority of the top 100 eCommerce sites are already doing some form of split testing.

The problem with lowest common¬†denominator¬†split testing is that your visitors are not all the same. While you’ve found what works best for the group as a whole, you are not taking advantage of obvious differences in terms of why they came to your site and what will get them to take action.This brings us to the second level of maturity.

2 – Segmentation

The second level of conversion rate optimization maturity takes advantage of “standard” information you know about your visitors. For example, where they came from – was it search (organic or paid), direct traffic (they typed in your url directly), a referral (a link from another site) or maybe an internal email. Have they come to your site before (new or returning users). Where are they located? What Browser are they using? etc.

This is the type of information you’ll usually find in a web analytics tool. Most of it is what’s available to you at the time of the visit itself.

This type of targeting is also known as segmentation. Basically, instead of putting everyone in a single bucket, you can now segment your visitors into several buckets. Instead of split testing all of your site traffic together you can measure the difference in behavior for each segment and more importantly serve up different tests to different segments.

The analogy I like to use is that of a sales person at a store who greets someone who just walked into the store. A good salesperson will try to put that visitor into a “segment” such as male, female, age, income, etc and propose products that person will most likely be interested in. If you’re not segmenting, it’s like having a blind and deaf salesperson.

Using segments together with split testing is way better than just split testing on it’s own, but you’re still treating everyone in each segment the same. What if you could actually treat every visitor as an individual? This brings us to the next level.

3 – Profiling

The final level of conversion rate optimization looks at each visitor as an individual. While segmenting on it’s own takes advantage of what you know about a visitor at the time of the visit, profiling also takes advantage of everything a visitor previously did as well as everything all of your other visitors have done.

Profiling gives each visitor a history that you can fully take advantage of. If a visitor bought shoes on their last visit, show them a banner for socks. You can even track what type of shoes they purchased in order to know what type of socks to offer.

Going back to the salesperson analogy, using segmentation on it’s own is like never having the same salesperson at your store. Every visit for every visitor has a different salesperson. Profiling is like having one single super-salesperson that remembers everything every visitor ever did.

Profiling can also be automated. If most people who purchased products A & B also bought product C, then automatically show product C to anyone who purchases products A & B. While profiling on it’s own is very powerful, but the ultimate in optimization is profiling together with split testing.

Netflix and Amazon are two examples of companies that are already doing profiling (and split testing).¬†Wouldn’t you like to be like them?

As always, please leave questions and comments in the comments section.

Thank you