A/B Testing - Run Experiment

It involves introducing all variations of your site or an application to the visitors and their actions are monitored for every variation. Visitor interaction for each variation is measured and compared to determine how this variation performs.

As discussed in the previous chapter, there are different tools that can be utilized to generate hypothesis and to run the variations −

  • Visual Website optimizer (VWO)
  • Google Content Experiments
  • Optimizely

Visual Website Optimizer

There are different A/B Testing tools that permits marketing professionals to create multiple variations of their website pages by using a point-and-click editor. It doesn’t need any HTML knowledge and you can check which version produces the maximum conversion rate or sales.

Executing VWO split testing software is very simple as you just need to copy paste the code snippet in your site and you can easily make it available to visitors. Visual Website Optimizer also gives an option of multivariate testing and contains other number of tools to perform behavioral targeting, heat maps, usability testing, and so on.

There are various features in VWO that ensures all your conversion rate optimization activities are secured by this tool. Many enterprises and small scale online stores are using A/B Testing VWO software for landing page optimization and for increasing their website sales and improving conversion rates too.

Company also provides a 30 days’ trial that can be downloaded free from − https://vwo.com/.


Some of the key features of VWO are as follows −

  • Testing and Experimentation
  • Visual Editor
  • Analysis and Reporting
  • Heat maps and Click maps
  • Platforms and Integrations


How it works?

Optimizely running on your website page collects data of site visitors, conversion rate and runs them on Stats Engine to decide, which variation is a winner and which one is a loser. Once these stats are compared with target goals and set metrics, it will assist you to make decisions about the variation to be applied on the site.


Google Content Experiments

It permits you to create up to five variations of a page and then load all these pages to Google Analytics to perform A/B Testing.

To begin with Google Analytics, you need to have a Google Analytics account and a tracking code to be installed on your site. If you don’t have an account, you can join using the following tool − http://www.google.com/analytics/

Adding tracking code directly to a website

To finish this process, you must have access to your website source code, you should also be comfortable editing HTML (or have a webmaster/developer, who can assist you with this), also you should have a Google Analytics account and property already set up.

To set up tracking code into your webpage

  • Discover the tracking code snippet and sign in to your Google Analytics account, and select the Admin tab at the top.

  • Go to the ACCOUNT and PROPERTY tab, select the property you’re working with. Click on Tracking Info → Tracking Code. Picture of where you discover your tracking code in your Analytics account → Click to expand this image and see where these options appear in the interface.

  • Discover your tracking code snippet. It's in a box with several lines of JavaScript in it. Everything in this box is your tracking code snippet. It begins with <script> and ends with </script>.

  • The tracking code contains a unique ID that corresponds to each Google Analytics property. Don’t mix up tracking code snippets from various properties, and don’t reuse the same tracking code snippet on multiple domains.

  • Copy the snippet and paste into each website page you want to track. Paste it immediately before the closing </head> tag.

  • If you use templates to dynamically generate pages for your site, you can paste the tracking code snippet into its own file, then include it in your page header.

Verify if the tracking code is working

You can confirm if the tracking code is working, check real time reports, you can also monitor user activity as it happens. If you see data in these reports, it means that your tracking code is currently gathering the data.

Content Experiments

Content Experiments is one of the fastest method to test web pages - landing pages, homepage, category pages and it requires fewer code implementations. It can be utilized to create A/B Tests inside Google Analytics.

Some of the most common features of Content Experiments are −

  • You need to utilize original page script to run tests, the standard Google Analytics tracking code will be utilized to measure goals and variations.

  • Target goals that are defined on Google Analytics can be utilized as the experiment goal, including AdSense revenue.

  • The Google Analytics segment builder can be used to segment results dependent on any segmentation criteria.

  • It permits you to set tests that automatically expires after 3 months to prevent leaving tests running, if they are unlikely to have a statistically significant winner.

How to utilize Content Experiments to create A/B Tests?

Go to the Behavior section and click on the Experiments link. It will also show you a table with all the existing experiments. Click on the “Create experiment” choice at the top of this table.

Enter → Name of the experiment, objective of the experiment, percentage of site traffic to take part, any mail notification for important changes, for distributing the traffic to all variations, set up time that investigation will run and also threshold values.


You can add URLs of unique page and all the variations that you want to create and click on the next button. Select the implementation method and click on the next button → Click on validation (If you have one code implemented it will approve. If there is no code, it will show an error message) → Start Experiment.


Once this experiment is run, you will see the following options −

  • Conversion Rate

  • Stop Experiment

  • Re-validate

  • Disable Variation

  • Segmentation − It permits you to see how each variation has performed for each segment of visitors on your webpage.

Input your Topic Name and press Enter.