Articles written in August, 2012

August 31 2012

Use a Heat Map to Better Understand Your Web Conversion

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A lot of businesses are using analytics to test new ideas and evolve to better landing pages. A baseline question is why does a page lose searchers? Is there poor content that is not engaging? The true answer can be any combination of a number of variables that all would potentially need to be tested. Where can you begin? Heat maps!
Heat maps are a way to understand where website viewers are “looking” on your webpage by showing you the “hotspots” that viewers navigate toward. This allows a business to see what their visitors see first and rearrange a page so that the most important content is in the right place.

With this data, a web developer would be able to modify the position of where the checkout button is located, or directions to the business location, etc. There are many companies that offer this software, some are free (www.labsmedia.com) and others require subscriptions (www.crazyegg.com).

Once you have subscribed to a service, they will ask you some questions about your site and see how many pages you would like to track in order to get the process started. Once this data has been entered, they will give you some code to be inserted into the page so that users experience data can be harvested by the website and viewed through the tools. Make sure when using a tool that you give it ample time to collect good data! It is unwise to continually change a page with small sets of data to back it up. This will typically lead to very small tweaks to a site done very often. This will never allow you and your website to get ahead in the process. I would recommend at least 3 months of data before changing a page to make sure you have an accurate idea of what you are viewing.

After you have decided the changes you would like to make, do not delete the old page! It is better to test the new format based on the heat map against the current page first to make sure that these changes will in fact have a positive result.

August 28 2012

Content Experiments in Google Analytics – Next Steps and what’s New?

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(This is the third post in a series about Google Analytics Content Experiments. For more information about Content experiments in Google Analytics (GA), you can view our first post two posts: Announcing Google Analytics Content Experiments and How to Create a Content Experiment in Google Analytics. )

So you’ve run your first content experiment in GA, now what? Well to answer that, we need to take a step back.

Hopefully your experiment began when you identified either an opportunity to improve your conversion flow or perhaps reduce the bounce rate on a landing page. Either way, your next step should have been to develop a hypothesis of why the page was not effective. Perhaps there was not a clear call to action, so you added a large button to encourage visitors to convert. Whatever you decided, your steps should have been

A. Identify a testing opportunity
B. Develop a hypothesis as to why the page is not effective and how it can be improved
C. Create a new version of the page and launch your experiment to test this hypothesis
D. Let GA determine which page is more effective

At this point there are three possible results:

  1. You’re A page performed better than your B page
  2. Each page performed about the same
  3. Your new page, the B version performed better than the A page

Believe it or not, your next step is the same regardless of which result you saw. Let’s explore this. If you’re original page performed better or the same as the new one; that does not replace the original observation that this page/step/process could or should perform better. If your new page performed better than the old one then good for you; but that does not mean that it can’t still be improved. So as you may have surmised by now, the next step is to develop another hypothesis and run another experiment.

The good news is that there are new features available in Content Experiments to allow you easily pause, restart and re-launch saved experiments.

Happy Testing!

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