I want to share some results from a recent trial that I conducted using a tool called Split Testing ClickFunnels. This article will tell you about the results of that trial in terms of gaining more traffic, leads, and sales. But, before we begin, let’s take a quick trip down memory lane. If you’re reading this, I assume you’ve used ClickFunnels at some point in the past.

A Quick History Of ClickFunnels

If you’re new to this space, you may not know exactly what ClickFunnels is or what it does. If this is the case, then let me give you a short summary. ClickFunnels is a tool that helps online marketers to discover the most effective conversion tactics for various landing pages.

The landing pages are the pages that you establish in your website that are designed to attract specific groups of people. For example, if you’re an online retailer, you may want to have a retail landing page, a customer service landing page, or an about us landing page. A landing page is just a page on your website that is tailored to attract potential customers.

Once you have a pool of interested leads, you can use conversion tools like ClickFunnels to increase the conversion rate from that lead pool to a paying customer. To do this, you simply set up a few test landing pages on your website, and then you split test the different approaches to see which one converts the best.

Why Should You Try Split Testing ClickFunnels?

Since we’re on the topic of testing, let’s briefly discuss the purpose of A/B testing. Basically, A/B testing is the practice of comparing two different approaches (e.g., two different landing pages), and then analyzing the results to determine which one is more successful (e.g., which one gets the best response from the target audience).

Often, digital marketers will A/B test landing pages and approaches to see which one generates the most leads or sales. Additionally, A/B testing allows you to discover the optimal conversion ratio for different platforms (e.g., social media, email marketing, etc.). For example, if you’re testing different headlines, descriptions, and social media banners for your marketing campaigns, you can use A/B testing to see which ones perform the best.

Another important thing to note about A/B testing is that you should always include a control group in your experiment. The control group is simply a comparison group that you use to establish baseline data, as well as to determine whether or not there was any significant change in the results due to random chance or fluctuations in the data (e.g., the data collected over the course of several months randomly varies).

How Important Is Tracking Data?

As a marketer, you should always keep an eye on the analytics for your experiment. Luckily, with the exception of paid social media tests, you always have access to the raw data from your experiment. This means you can always go back and review the performance of each variation you tested.

However, it’s important to note that while this data is very useful, it’s not everything. Basically, whenever you perform A/B testing, you should always track as many variables as possible, but you should still rely on your gut instinct as the deciding factor when you’re analyzing the results.

The Importance Of Getting The Most Out Of Your Test

When you’re performing A/B testing, you have to keep in mind the importance of getting the most out of your test. In other words, you have to ensure that each variation you tested is actually a) different and b) representative of what it is you’re looking for. If you don’t, then you might get a skewed result due to a number of reasons.

Firstly, if you mistyped a variation and it’s being compared to the correct one, you could end up with some seriously distorted data. For example, if you mistyped the name of a product and that product is being compared to the one with the correct name, you could seriously affect the results of your experiment. This is why it’s important to double and triple check each variation before performing your experiment.

Secondly, if you’re randomly selecting participants for your experiment (e.g., if you’re doing an online experiment via SurveyMonkey) then you run the risk of getting skewed results simply by chance. Remember, even when you’re using a tool like SurveyMonkey, you’re still running an A/B test when you’re using its randomly generated samples.

Thirdly, if one of your variations is so superior to the others that it drives all the traffic to a single landing page, that landing page might become your “default” or “go-to” page, and you’d lose track of all the traffic that was previously routed to the other pages.

The Importance Of Setting Up A Plan B

Often, when we’re testing various elements of a website, we’ll get excited about the results of one experiment and immediately jump into a new test without considering the possibility of a crash. While this might work for some basic tests, it’s not a good idea to rely on this shortcut thinking when you’re performing A/B testing.

If you find that one variation is performing very well in your test, but it doesn’t represent your ultimate goal, then you should immediately set up a plan B. Simply put, when you’re testing various elements of a website, you should assume that some of the changes you make might seriously affect the operation of the site. In other words, even if your test reveals that one variation is superior to the others in terms of increasing sales, you might run into problems when you try to implement it.

For example, if you’re changing the navigation of a website, then you should assume that some of your readers might not find their way around the new navigation as easily as they did the old one.

Additionally, if you’re testing different headlines for your articles, then you should assume that some of your readers might not be as interested in your product or service as they were in the headlines you tested.

Remember, with A/B testing, you’re not necessarily looking for the best of everything. You’re just looking for the most successful variation of what you tested, so be patient and take your time before you make any major decisions.

The Results Of My Split Testing Experiment

Since the last part of this article is just a quick summary of what we’ve discussed so far, let’s now get into the details of my experiment. If you’re following along, you’ll see that I compared three different styles of buttons for my website’s contact form. Each button was tested on a different landing page, and each landing page was tested against a control group.

To begin with, let’s take a look at the results for my plain old boring old button.

  • Button Title: Register for free
  • Button Description: Get access to the digital tools you need to succeed in business
  • Button Image: Contact Forms

If we compare this to the control group, we can see that this particular approach achieved the lowest amount of conversions among all three of the variations I tested. Even more interesting is that there wasn’t any significant change in the results when we compare this to the other two variations.

This means that the combination of the two remaining variations outperformed this one in terms of gaining new registrations.

If we compare these two variations, we can see that the button text and the button description had a significant impact on the number of registrations. However, the type of icon used on the button had almost no impact on the results.

The Results For My Second Variation

The second type of button variation I tested used the exact same text as the first one, but it swapped out the icon. In other words, this variation used a chevron instead of a square.

  • Button Title: Register for free
  • Button Description: Get access to the digital tools you need to succeed in business
  • Button Image: Contact Forms