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Attention all CRO managers: there is a very good chance that your A/B testing results could be invalid. In fact, some sources claim that A/B testing fails an astonishing 90% of the time. Considering all the time and effort you put into planning and executing these tests, this should be a definite wakeup call. A/B testing practices need to be improved in order to eliminate the obvious inefficiencies of the current process and to yield much more accurate results.
A Guessing Game at Best
Consider the following typical A/B test creation process:
- Step 1: Create a hypothesis (based on a hunch or assumptions) of which element you want to test.
- Step 2: Set goals for the test, like click goals, revenue goals, visit goals, or another customized goal.
- Step 3: Create two versions of the content, design, or CTAs you plan to test.
- Step 4: Set a time frame for the test based on what is being tested and the required sample size.
- Step 5: Analyze the results.
- Step 6: Repeat the process – additional testing is usually required as this method can often be inaccurate.
It is clear that this more traditional type of A/B testing process is inefficient, as it is often based solely on the theories or guesses of the marketing team, and not on actual hard data. With the time that is required to receive significant results and the resources invested in creating different variations of copy or graphics to test, this inaccurate process is a lengthy and more expensive CRO method.
With the low success rates of these types of tests, it is imperative to upgrade this process by removing the guesswork.
Data-driven Analytics Can Improve and Focus A/B testing
You can optimize A/B tests by utilizing real-time Data Analytics Tools that are designed to help you concentrate on what should be tested, eliminating the guesswork. These types of tools provide the data you need to ameliorate your testing process, allowing you to allocate your valuable resources on what will generate the best ROI for your business.
- Heatmaps: These useful tools help you leverage crucial data about your customers’ on-page behavior and discover on which pages your visitors spend most of their time.
- Form Analytics: This helps you identify which elements or fields are causing confusion for your users, or where your potential customers lose patience and interest. This real-time tool enables you to quickly identify problems with your forms, so your team can resolve them immediately.
- Session Replays: With this tool, you can pinpoint precisely where you lose potential customers in the conversion funnel and with which elements your visitors engage the most. By utilizing online consumer behavior data gleaned from the session replays, you can focus your efforts on what needs to be fixed and tested in order to improve the customer experience and reduce shopping cart abandonment.
Take Data to the Next Stage
- Step 1: Analyze the data and user behavior that you garnered from your analytics tools to determine which elements on your pages need to be optimized.
You should ask yourself the following questions:
Where are you users getting stuck? What is causing them frustration?
Where are your users abandoning their shopping carts?
Where is their attention focused? Is this where you want it to be focused?
- Step 2: Design an A/B test for a single element based on your findings from Step 1.
- Step 3: Run the A/B test and analyze the results.
- Step 4: Optimize the element based on the results of the test.
- Step 5: Repeat these steps with different elements based on the findings from Step 1.
Improve Overall Efficiencies
The data-driven process defined above will significantly strengthen your conversion rates, as it enables you to identify precisely where your customers are leaking out of the conversion funnel, and why.
However, this is just the tip of the benefits iceberg.
Integrating Data-based Analytics will enhance your company efficiencies, which translates into dollar savings, across the board:
- Company Resource Conservation: With targeted testing, your marketing team will spend less time debating what to test. Your design team will save time and money on unnecessary element creation. Your marcom department will spend less time creating content that might not need to be tested in the first place.
- Increased Accuracy: By pinpointing the elements that need to be tested, you will increase the ratio of accurate A/B tests. Elimination of the guesswork will increase your chances of efficiently optimizing your elements and getting impactful results.
- Smaller Sample Sizes: By identifying the elements that require optimizing, you can lower the sample sizes of your A/B tests, decreasing the time needed to receive results.
- Faster Test Iterations: The data-based approach decreases the time that is required for testing. It allows you to test more elements over a shorter time period, improving the customer experience, shopping cart checkout rates, user engagement, and more, much quicker.
- Improved ROI: Better click through rates, combined with decreased resource allocation for producing the changes, will boost your return on investment, allow you to channel these resources to other aspects of your business, and improve overall efficiencies.
Key Takeaways for Implementing Next-stage CRO
In your ongoing endeavor to enhance your customer experience and improve efficiencies, Data-driven Analytics can take your CRO efforts to the next stage. Advanced Analytics tools can help you scientifically pinpoint what exactly needs to be changed and tested on your website, and thus increase your ROI, by:
- Showing you precisely where your customers are disengaging and where they are feeling the most frustrated.
- Identifying what parts of your web page are performing sub-optimally.
- Enabling highly targeted A/B testing which ultimately decreases test iteration and conserves a lot of company resources.
Only 22% of businesses are satisfied with their conversion rates. By using a science-based targeted analysis that will improve click through rates and increase revenues, your company is likely to be among them.