AB testing is one of the best ways you can understand user behaviour on your website. It allows you to run different tests, to evaluate your hypothesis on your visitors behaviour.
As your website traffic grows, you will be able to run a number of AB tests, or run tests which you can get results on very quickly.
4. Make sure your test is big enough so people notice and can be tested quickly BUT not too big it will lose you money
How To Choose Metrics & Set Goals For A/b Testing
It is a way of allowing you to build tests to validate your to see whether those things have made a difference to your business.
It is a rapid, not a highly structure development process, focused on optimising your website, using data to validate what worked and didn’t work.
There a number of tools which help you deliver this. Some of the tools we have used include: Google Optimize (free option with integration with Google Analytics), Monetate (built for marketers), Attraqt (for testing merchandising).
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It will allow you to validate new designs, before they are rolled out and the potential impact they might have whether that be positive or negative.
It reduces your risk by testing on a small audience, knowing whether if it has an impact prior to a rolling it out across the whole of your customer base/website visitors.
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How To Create A Powerful And Effective A/b Testing Plan
Your tests could come from any part of the organisation. They might include improving your marketing effectiveness, showing the right products, or seeing which content best engages your audience. Remember to categorise your hypothesis so you know if it is testing User Experience (UX), Website functionality or Content vs Product.
Make sure you capture all the relevant information about your hypothesis. This will allow you to set the right metrics (in step 2) and also help your prioritise this hypothesis (in step 3).
If you set the metrics correctly know you will firstly know whether the test has been a success AND what behaviours it has also influenced.
A Beginner's Guide: How To Do A/b Testing
Start with setting your primary metric. The one thing you want to prove. In this example we have looked at Product Viewed Rate, Add to cart rate and Cart completion rate.
Once you have your primary metric set your secondary metrics which will allow you to understand why things happened. These might include page load time, bounce rate or returning visitors as some example. For some help on defining these go here.
Test length is determined on the amount of traffic your website gets coupled with the items described here, Page, Device and Number of Tests.
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To ensure you have a reliable test ensure you have enough traffic to test, but do not deploy it to the whole website as this could have a major impact.
There are a number of testing calculators out there to help you define if you test is reliable (in data terms call significant).
Define the pages which the test will run on. Lower level pages (those accessed from menus) will have less traffic and require the test to run for longer.
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The device which the test will run on will impact the test length. If you run it on all devices you will see a shorter time to results. Choosing a low volume device (such as Tablet) will take a lot longer.
Testing different things is a great idea, but the more tests the more data you will need. Therefore try to only create multiple tests on large volume pages.
The criteria can be changed, but it is important to balance the business impact against customer benefit. And then look at cost and speed to market.
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We then upweight the organisational focus for each of the criteria to ensure each test is focused on the right outcome. When you combine both you get an overall priority.
The images here show the different Proposed designs. Each audience (visitors) which see the test a mutually exclusive i.e. they only see their test design.
This is the A test. Or the current page, which you are testing against. In this example the test was to see if changing the “burger Menu” in the top left could get more clicks, as visitors were lost.
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Before deploying the test in the live environment set up your test in a development environment where only the internal team can see the test in action and the data from the test can be captured.
Once you have launched your tests, keep an eye on the performance of the test. This should be compared with the generic/current experience.
Review the category AND the outcome of each test. Compare the results of the specific test and if this improved or declined the outcome.
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What you will need to do is understand how much traffic you need to provide you with “confidence” the test is representative of your audience/website visitors.
Once you have deployed your test make sure you are able to see them metrics for each test, without this tracking you will not know if the test has made a difference.
If this is not available make sure you track the tests inside your web analytics tool. This could be as simple as creating two different landing pages with different names and seeing the conversion rate, add to cart rate, average order value of these pages compared to the generic or current page.
How To Check Whether Your A/b Testing Is Working
Below is some recommended content to help you with your analysis in marketing. This content is mixture of content, tools or our book to help you get more out of your digital marketing and data in your business.
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Define: Conversion Rate – Read about a critical metric for measuring the number of people who take action on your website. Learn how to diagnose conversion rate and understand how conversion rate impacts your cost per acquisition.
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Discover: Resource for senior marketers – See our latest research or white papers to help you get ahead. Alternatively, read our digital marketing glossary for senior leaders to understand the jargon and acronyms of digital.A/B testing (also known as split testing) is the process of comparing two versions of a web page, email, or other marketing asset and measuring the difference in performance.
You do this giving one version to one group and the other version to another group. Then you can see how each variation performs.
Think of it like a competition. You’re pitting two versions of your asset against one another to see which comes out on top.
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Knowing which marketing asset works better can help inform future decisions when it comes to web pages, email copy, or anything else.
After you create your designs, you give one landing to one group and you send the other version to the second group. Then you see how each landing page performs in metrics such as traffic, clicks, or conversions.
Creating a website or email marketing campaign is just the first step in marketing. Once you have a website, you’ll want to know if it helps or hinders sales.
How To Create A Winning A/b Testing Strategy
A/B testing lets you know what words, phrases, images, videos, testimonials, and other elements work best. Even the simplest changes can impact conversion rates.
If such a minor change can get people to click, you’ll want to know what other elements of your page might have an impact on conversions, traffic, and other metrics.
A/B testing involves comparing two versions of your marketing asset based on changing one element, such as the CTA text or image on a landing page.
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I prefer A/B testing because I want to know which elements actually contribute to the differences in data. For instance, if I compare two completely different versions of the same page, how do I know whether more people converted based on the color, the image, or the text?
The statistics or data you gather from A/B testing come from champions, challengers, and variations. Each version of a marketing asset provides you with information about your website visitors.
Your champion is a marketing asset — whether it’s a web page, email, Facebook Ad, or something else entirely — that you suspect will perform well or that has performed well in the past. You test it against a challenger, which is a variation on the champion with one element changed.
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After your A/B test, you either have a new champion or discover that the first variation performed best. You then create new variations to test against your champion.
[tweet_box design=”default”]Many people think that you can get away with a single A/B test. In reality, you should be continuously testing so you can optimize your marketing and advertising creative for your audience.[/tweet_box]
Some elements of a marketing asset contribute to conversions more than others. Changing one word in the body copy of an email, for instance, probably won’t make much of a difference in conversion or click-through rates .
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Since you have limited time, devote your energy to the most impactful elements on your web page or
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