What is CRO?
Conversion Rate Optimization is the process of optimizing a webpage to get users to convert whether it is by form submission, phone calls or simply clicking on a CTA. We like to be proactive by always monitoring and looking for ways to help improve overall conversion.
We work closely with our SEO Specialists and team leads who spend time on the accounts which helps create more insight from their perspective. To be successful, we need to learn and study each of our clients’ users, this is where Google Analytics comes in.
Google Analytics helps us see where users are dropping off, where they are coming in from, and how much time they spent on the page, etc. We then start to formulate our hypothesis, for example, one of our clients, we noticed a steady decline of form submissions overall from when they launched their redesign. Our hypothesis is if we move the form to a sidebar like their old design had, we would then see an increase in form submissions instead of having the form towards the bottom.
Aside from analyzing data from Google Analytics, we also look at Hotjar where a heatmap is generated. The heatmap tells us where users are clicking the most, how far they scroll on the page, and where their mouse movement occurs. Upon reviewing the heatmaps, we noticed that a total of 30% would reach the form or the bottom of the page. This tells us a couple of things: that the user is not interested in the content, or perhaps they clicked on the contact button in the navigation, there could be many possibilities. Our goal was to get users to convert directly on the page they land.
How do we test if our recommended updates help performance?
Google Optimize is a platform that allows us to configure our A/B test, this is called an experiment in Optimize. It easily integrates with Analytics and Tag Manager where we can pull in Goals already established in Analytics to use as a metric for the experiment. The goals would need to be properly set up in Analytics before Optimize can run.
An A/B test is where we will compare two versions of the same page to see which one performs the best. Version A would be the original page while version B is the updated layout, in this case having the form in the sidebar.
There are other cases to run an A/B test such as:
- Button colors
- Rearranging elements on the page
- Content changes
You may want to test if a certain button color drives users to click on it more or we may want to test out if certain headings and content written differently drives for better conversion. These are just some examples of running an A/B test.
Once the experiment is established, we let it run for a total of 90 days while periodically checking in to ensure data is collecting correctly. During this process we can see if our hypothesis is true or not, there are cases where it is not, and version A drives more conversions. Depending on the outcome, we’ll showcase the results to the team and/or the client and move forward with the winner of the experiment.