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How to Do A/B Testing Effectively
No matter what business youโre in, youโre putting words out there.
Website content. Ads. Social media posts. Emails. Pop-ups. Call to action.
Thereโs a ton of information that youโre sharing with your audience every day!
But how often do you test the effectiveness of what youโre saying?
And if you arenโt testingโฆ How do you know whatโs working and what isnโt?
Learning how to do A/B testing could be the biggest skill you learn this year!
Hereโs everything you need to know about testing your campaigns for effectiveness.
What is A/B testing?
A/B testing (also called split testing) is a simple comparison test between two similar versions of the same thing.
The point is to see which one performs better.
This can give you interesting and important insight into your audience’s mindset!
Analysing how people respond to certain content will help you to make more effective decisions about your own marketing campaigns.
How Does A/B Testing Work?
A/B testing is a simple principle.
You take a particular digital assetโฆ
And create two slightly different versions of it.
The key is to only change a single variable.
Maybe it’s a personalised greeting vs a generic greeting.
Maybe it’s a more direct CTA vs a less direct one.
It could be a bit more humour in the content vs more formal content.
Or even something like changing the colour of your CTA button.
And then see how people respond.
You can change multiple variables if you wantโฆ
But it becomes more difficult to keep track of which change really makes a difference with your audience.
Most platformsโwebsite, email, social mediaโcome with built-in split testing tools.
So donโt worry if comparing two assets seems complicated!
Itโs easy when you know how to set it up and analyse the results (which weโll discuss later).
Why Should You Do A/B Testing?
How will you ever know what works best for your audience if you donโt test it?
A/B testing can provide insights into how customers feel about your product, service, and customer experience.
Which means you can use this info to tweak things that arenโt quite workingโฆ
To improve your customersโ experience.
And an improved customer experience means more sales for you.
Possibly more referrals.
And definitely happier customers!
Itโs a win-win situation for you and them.
- Not sure if your pop-up is catching attention? A/B test it.
- Wondering if you could make more sales with your welcome email? A/B test it.
- Not totally sure if your offer works for your target market? A/B test that too.
If you find that certain things donโt get a great response, you know what not to do.
And you can try to replicate the things that do get a good reaction.
What Can You A/B Test?
Once you know how to do A/B testing, you can test almost any digital resource you have.
You can get very detailed in terms of testing marketing messages, design, colours, and almost every variable that goes into designing resources.
- Pop-ups
- Offers
- Landing pages
- Emails
- Lead magnets
- Page layouts
- Colours
- Social media posts
- CTA text & delivery methods
- Photos and product images
- Keyword volume
- Push notifications
When Should You Use A/B Testing?
One of the great things about A/B testing is that you can do it whenever you feel the need.
If you notice that your latest pop-up isnโt getting the results you expected, an A/B test can give some insight into why.
Similarly, if your welcome email/landing pages/social media posts arenโt converting well, an A/B test could determine the cause.
You can do random A/B testing throughout the year whenever you feel like you want a bit of insight into whatโs going on in your customersโ minds.
That being said, rather than just randomly testing stuff, itโs a good idea to use your analytics to get a clear idea of what to test and why you want to test it.
Using analytics, you can see things like:
- Your most popular pages
- Where traffic arrives from
- How long readers spend on a page
- Which pages have high bounce rates
- What readers click on
- How long viewers pause and where
This will help you decide where to focus your A/B tests to get the greatest ROI when it comes to finding our info on what your customers want.
Itโs also a great idea to make use of user tests, which allow you to watch readers in real-time to see how they navigate your website and where they get stuck on things.
If you need more direct information, you can always send out a survey. This way, youโll get direct feedback from your customers on their pain points.
Remember, customersโ wants and needs change over time.
Itโs in your best interest to perform research on a regular basis so you know you’re always providing practical, easy solutions!
How Long Should A/B Tests Run?
To get accurate numbers, youโll need to get a certain number of traffic to the asset.
You canโt get accurate results if only 100 people test it!
Most platforms come with built-in A/B testing software that show you when the test has reached the point where itโs considered โstatistically significantโ.
Now, most marketers will end the test here.
It means you have enough data to make reasonable assumptions about your customersโ behaviour and adjust your assets based on that.
But itโs not the most accurate the test can get.
If you donโt have a lot of time, you can stop when you reach this stage.
But if you want proper insight into your customersโ behaviourโฆ
As well as what drives certain behavioursโฆ
Itโs best to run your A/B tests through one full business cycle at least.
If not two.
This allows you insight into how customer behaviour changes based on what the economy is doing at the time.
Benefits of A/B Testing
Unsure about doing A/B testing?
Here are some benefits you can expect.
- Better understanding of your audience
- Keeping up with trends
- Improved customer experience
- Informed marketing choices
- Lower bounce rates
- Better conversion rates
- Increased ROI
How to Conduct A/B Testing
Want to try A/B testing on one of your resources? Hereโs a quick checklist of how to do it effectively and with as little stress as possible.
Choose Your Resource to Test
Is your pop-up not converting well?
Maybe youโre trying to make more sales with your welcome email.
You can choose whatever resource you want to test.
I advise sticking to one at a time, at least in the beginning.
That will prevent information overload!
Set a Goal
Donโt just A/B test for the sake of it.
Set a goal for your test, otherwise itโs hard to tell if itโs successful or not!
For example, are you testing to see which pop-up gets more emails?
Or which web page design has the longest time spent on it?
Set your goal so you know what youโre looking for when it comes to analysing results.
Choose One Variable to Change
Donโt be tempted to change everything.
Rather, choose one thing to test at first.
Analyse your resource and try to figure out whatโs causing it to convert poorly.
It could be:
- The design
- The colours
- Your message/language
- Your CTA (style or text)
Aside from being much easier, choosing just one variable has another practical advantage.
It means you know exactly which variable is the problem.
If you change the colour and you still donโt see results, you know itโs not the colour causing the problem.
But if you change the colour, the design, and the CTA and then you see resultsโฆ
Youโll never know what the actual issue was.
Once youโre good at single-variable A/B tests, you can try multivariate ones.
Change Your Variable
Once youโve chosen your variable to test, create two separate versions of the resource.
The only change will be your chosen variable.
They should look almost like carbon copies, just with one specific change.
The original one is known as the โcontrolโ.
The one with the change is called the โchallengerโ.
Create Your Splits
The next thing to do is split your audience into two.
This should be done randomly and equally.
For example, letโs assume youโre testing an email on your list of 5,000.
Split it straight down the middle: 2,500 and 2,500.
If youโre testing another resource and using an A/B testing tool, some of them automatically split your traffic for you.
You should also make sure this split is completely random.
No choosing your most engaged email subscribers for one split and quiet ones for the other!
This will give you the most honest and accurate results.
Determine Sample Size
If youโre testing an email, sample size is easy.
But what if youโre testing something like a web page?
Thereโs no way to determine how much traffic might land up there on any given day.
In cases like these, youโll need to run the test for long enough to get results that are โstatistically significantโ.
You canโt get super accurate results on a sample size of 500 people.
But if you get 5,000 visitorsโฆ
Thatโs got a lot more weight behind it.
Run One Test At a Time
Although it may seem like the slow way of doing it, stick to one test at a time.
Donโt test an emailโฆ
And your pop-upโฆ
And a new web page design at the same time.
Basically, the simpler the better.
Do one test at a time so thereโs no over-complicating things.
How to Analyse A/B Test Results
Thereโs no such thing as winning or losing an A/B test.
Every result is significant.
Keep an eye on your results on the dashboard of whatever tool youโre using.
You need to understand that your A/B testing tool wonโt do the analysis for you.
Itโs up to you to scan through your results and gani insight!
Remember your original goal when you analyse your results.
Were you aiming to find out which pop-up converted the best?
Then donโt waste time looking at any other metric.
Study the patterns and find your answer.
If the answer isnโt what you expected, donโt be upset or worried.
Itโs valuable insight into what works and what doesnโt.
Donโt be afraid to make changes based on your analysis!
That’s the whole point of an A/B test.
Final Thoughts: How to Do A/B Testing
Learning how to A/B testing could be one of the best things you learn for your business.
Itโs easy and can even be fun!
But it does require some patience and a discerning eye.
Why not start small and A/b test something on your website today?
You may be shocked at the resultsโฆ
But it could make positive changes in your business.
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