A/B Testing Tools 101: Interpreting the Instapage Dashboard

A/B Testing Tools 101: Interpreting Your Instapage Analytics

Last updated on October 5, 2016 by Fahad Muhammad in A/B Split Testing, Instapage Updates
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What’s the one thing we all do as soon as we publish our landing page?

We expect our conversion rates to soar.

With all the thought you put into creating an optimized landing page, it’s only natural that you'd expect scores of new visitors to be filling out your lead capture form. You’d almost swear you can hear the pitter-patter of thousands of CTA button clicks as new customers start their journey down your marketing funnel.  

Things don’t always turn out this way as only 22% of businesses are satisfied with their current conversion rates.

Statistics as small as that show why A/B testing tools are necessary and why A/B testing is becoming more popular with each passing year.

Why do you need to run A/B tests?

The purpose of A/B testing is to find the optimal version of your page to increase your conversion rate.

Compare different variations of your landing page and identify what your audience responds best to. You can try out new tactics, and iterate until you find the perfect combination of landing page elements that resonates with your audience.

You can A/B test everything, from your headline to form length to your customer testimonials.

To master the testing process, it’s important that you have the right A/B testing tool by your side.

Enter Instapage.

Instapage makes it easy for you to create and test multiple variations of your landing pages in just a few easy clicks. The analytics dashboard allows you to easily interpret your testing results — even if you’re new to landing pages and A/B testing

How to understand A/B testing tools

Interpreting an A/B testing dashboard is not as daunting as it may seem. Even if you’re not a numbers person, understanding your analytics is easy when you break the dashboard down into bite-sized pieces.

When you sign in to your Instapage account and view your analytics, you will see a screen format similar to this:

This picture shows how Instapage's A/B testing dashboard is neatly organized.

Each landing page variation tracks these four metrics:

  1. Visitors: The number of unique visitors that landed on a particular landing page variation.
  2. Conversions: The number of visitors that have filled out a form or clicked on a CTA button on a particular variation.
  3. Conversion Rate: The percentage of visitors that turned into a conversion on that page variation.
  4. Improvement: The difference in the conversion rate tested against the “control page,” or variation A of your landing page. For example, if variation A has a 40% conversion rate and variation B has a 20% conversion rate; your improvement would be 20%.

To see how desktop compares to mobile (vice versa), you can toggle back and forth with these buttons:

This picture shows how users can toggle between desktop and mobile variations within the Instapage dashboard.

Your dashboard also has “pause” and “delete” buttons that allow you to pause or delete a variation in just one click:

This picture shows how users can pause or delete page variations within the Instapage dashboard.

Downloading your analytics is easy, too, by clicking the down arrow:

This picture shows how Instapage users can download their landing page analytics from the dashboard.

To makes things even easier, let’s see some analytics dashboard examples and analyze how each test is progressing.

Analytics dashboard examples

A/B testing helps you validate changes you’ve made on your landing pages and take the guesswork out of your conversion optimization equation.

Predicting what your results will be before you begin is the wrong approach to take with A/B testing. Don’t be surprised if you find out you had the winning landing page all along, as is true with this Instapage customer:

This picture shows a winning page variation within the Instapage dashboard.

Variation A has 835 visitors, of which 315 clicked on the CTA button — giving Variation A its 37.7% conversion rate. Although variations B and C still haven’t generated equal visitors, variation A is the winner of the group.

However, this particular test still needs to reach statistical significance.

In contrast, here is a test that has reached statistical significance:

This picture shows why statistical significance is important for A/B testing landing pages.

Variation A is the clear winner here with a 12.5% conversion rate, variation B has a conversion rate of 8.7% — meaning that variation B decreased conversions by 3.8%.

Sometimes your A/B test reveals a close match between the two variations. But oftentimes this means you still need to reach statistical significance, and to keep testing.

This picture shows an A and B version with very similar results and why you should keep testing to find a winner.

If you’re more of a visual learner, the color-coded graph displays page visits, conversions, and conversion rate. In the case of this customer, for the past 7 days, they have 44 total visits, 32 conversions, and a 73% conversion rate:

This color-coded graph shows how easy Instapage's A/B testing tool is with dates and both page variations.

The graph only shows data for the previous 7 days, but you also have the option to view 30 days and 3 months timeframes.

In the end

To ensure you’re running accurate tests, please remember it takes time for your tests to reach statistical significance. If, for whatever reason, your new variation doesn't win, you've still won because you've collected valuable data — and leads and conversions.

It’s best to not conduct more than two variations at a time (this is why we have a pause button next to every variation). It’s called, “A/B” testing for a reason!

A/B testing is a crucial part of your landing page marketing; you need to test your pages accurately to really improve your customer acquisition process.

P.S.: Instapage Basic users get 2 live A/B split tests while Professional and Premium users enjoy unlimited A/B testing variations. Not on a paid plan yet? Create your first landing page, begin A/B testing, and keep repeating the process!

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