Optimize Your Email Marketing Strategy With A/B Tests

What Is A/B Testing?

Once you’ve set up your basic email marketing strategy with some automations and campaigns, you’re ready to start A/B testing emails.

A/B testing in email marketing is when you create two versions of the same email, which only have one different variable between them — this variable is what you’ll be testing.

It’s important to test only one variable at a time, so that any results can be attributed to that variable.

In contrast, testing multiple variables at a time means you won’t know what made one email perform better than the other.

How To A/B Test Your Emails

A/B tests are commonly used in all forms of marketing, and is the most scientific thing about marketing.

The A/B testing process can be broken down into 4 different steps for email marketing:

1. Establish benchmarks
2. Test a variable
3. Measure results
4. Repeat

1. Establish Your Benchmarks

There are four key metrics that are measured in email marketing:

1. Open rates
2. Click rates
3. Click-through rates
4. Conversion rate

To start A/B testing, record the initial results for your emails — these will be your benchmarks.

With your benchmarks recorded, decide which metric you want to optimize first.

Most email marketers prefer to optimize open rates first, then click rates / click-through rates, and then revenue last.

Why? Because to make more revenue, more people need to click on your emails, but to get more clicks, your emails need to be opened first!

Industry Averages

If you have good benchmark metrics then you could skip testing open rates or click rates.

Here are the industry averages for email marketing metrics:

Metric	Industry Average
Open rate	20%
Click rate	2%
Click-through rate	10%

If your open rates are greater than 20%, then you can prioritize testing your click rates or click-through rates.

If your click rates are greater than 2% or if your click-through rates are greater than 10%, you can focus on optimizing revenue.

Conversion rate is not listed in the table above since it varies between different businesses.

2. Testing Variables

Once you’ve identified a metric you want to improve for an email, you can start A/B testing variables.

Here are some commonly tested variables for each email metric:

Optimizing Email Open Rates

Optimizing your emails’ open rates means testing your header information. This includes:

• subject line
• preview text
• ‘from’ address

---

Example: Subject Line & Preview Text A/B Test

Here is an example of a subject line A/B test for an abandoned cart email; the winner of the test will be whichever version has the higher open rate.

---

In advertising, your headline copy is the most important part of your ad, because without a strong headline you won’t get any attention at all.

In email marketing, your subject line is what gets peoples’ attention. A strong subject line and preview text means more people will open your emails!

However, with recent consumer privacy software updates in 2022, open rates have not been as reliable as they used to be…

(stay tuned for a post about open rate accuracy — subscribe to my newsletter so you don’t miss out!)

Common Variables for Testing Click Rates

Optimizing your click rates means getting more people to take action on your emails.

There are a number of variables that can drive click rates, including:

• CTA placements
• design
  • hero images
  • animated GIFs
  • product images
• copy
  • copy format and clarity
  • voice and tone
  • exclusivity language
  • FOMO: fear of missing out

… among others.

Email copy is the largest factor that affects click rates, because this is where you build the readers’ desire to take action.

A good click rate means your email is doing a good job of communicating your offer, and that people are interested in shopping with you.

Conversion Rate Optimization

If your email has a good click rate but not enough people are buying from it, then it’s time to optimize your conversion rates.

There are two main reasons why clickers don’t buy:

1. technical issues: your email has a broken link, linked to the wrong page, your website is slow or their internet connection is slow

OR

2. the offer isn’t right for them

Technical issues happen quite often, which is why it’s important to always perform quality assurance checks before you send them to subscribers!

But if your email doesn’t have any technical issues, then you should try a/b testing different offers or audiences.

3. Measuring Results

How you will measure results from your A/B tests will depend on whether you’re optimizing campaigns or automations.

Luckily, most ESPs have A/B testing features built into their platforms.

4. Concluding Your Test

Your test is only conclusive if your results are statistically significant (stat-sig for short).

This could take months of testing the same variable in your workflows or campaigns!

Once you’ve obtained stat-sig results, you’ve officially completed your test and can apply these changes to your future emails.

Email marketing optimization is an ongoing process! Since marketers can’t predict consumer behaviours, there is an unlimited number of variables to test.

The best marketers test everything.

Summary Notes

• A/B testing used in marketing to optimize ads by changing one variable between two ad variants
• Open rates are often optimized first, then click rates / click-through rates, and lastly conversion rates
• Email marketing optimization never ends; when one test is finished, another will soon begin

Optimization is a long-term process, but it’s an essential part to every email marketing strategy.

It can be a lot to manage for small marketing agencies, which is why they would rather outsource their work to a white label marketing agency like ours, so that we can build the best emails while they focus on managing clients.

Learn more →