Developing A/B Testing Parameters With Quantitative Data

A couple of days ago, I posted some info about Qualitative Data which used pre-qualifying questions a the front of a funnel to help direct your traffic to the right offers and landing pages.

Today, I am switching it up to talk a bit about Quantitative Data to come up with split testing ideas and optimization ideas. With Qualitative you allow the pre-qualifying questions to automatically split the traffic into specific split testing funnels. With Quantitative Data you will use something like your Google Analytics account to determine what your traffic behavior is.

Split testing is done with many aspects and combinations of our ads, headlines, triggers, angles, banners, media, graphics, etc. Using the quantitative data of behavior will help you see key elements of your visitors to optimize ads, headlines, triggers, etc.

For example, just go to your Google Analytics Dashboard (if you aren't using GA, get an account and give it a go). Once you are logged in, select one of your sites, scroll down to Behavior and click on Behavior Flow. This section shows you how visitors move through your site. What their patterns are. This will give great data about what you should be testing and where you should be testing it. You will see where you should ramp up and/or divide your traffic.

When looking at the Behavior Flow, you will see the page they land on, the 1st Interaction Page, as well as the 2nd and 3rd Interaction pages, etc. Place you mouse over any page interaction bar and you will see backlink information, a pie chart representing through traffic by percentage, as well as the drop off data.



Next, also under behavior Flow click on Site Content and click on Exit pages. Here you will see patterns in the pages. Patterns that reveal which pages people are most likely to leave the site from. Look at the last column labeled % Exit. This is going to give you the % of your visitors according to the last page they visited before leaving your site. It is an indicator that there may elements on the high% pages causing visitors to leave. As well, the pages with a low% may be worth examining to see why fewer people leave those pages. This can help you understand how to keep people on the pages with a high % exit.

Now lets talk about conversions a little bit. let's go to the landing pages under Site Content. Here you want to focus on the columns that have your goals. For example, you may have a goal for click throughs, a column for opt-ins, and a column for conversions. you will see % per page that tells you what visitors are converting on which pages giving you data about which pages are not converting and which ones are. Now compare the optin data with the conversion and drop off daa. This will give you indicators as to what does reach your goals per page and why.

I promise you, if you learn to use these analytical quantitative data sets, you will understand the visitors to your sites better, you will see where and why they interact with your site, and you will be able to replicate those values on the other parts of your sites, or on other sites altogether, to optimize for maximum results.