Pardot Email A/B Testing: The Complete Guide

Most B2B marketers have an opinion about what makes a good email. The subject line should be short. The CTA should be above the fold. Personalisation improves open rates. These beliefs come from blog posts, industry benchmarks, and gut instinct. A/B testing replaces opinion with evidence — and in Pardot, it is easier to set up than most people realise.

This guide covers everything you need to know about running email A/B tests in Pardot, from the basics of what you can test to interpreting your results and avoiding the mistakes that produce misleading data.

What Is A/B Testing in Pardot?

A/B testing enables you to test one change between two versions of your marketing assets. In the context of Account Engagement (Pardot), A/B testing is for list emails. The benefits are that it is quick to set up and can work even with a small sample size — though the greater the sample size, the more significant your results will be.

In practical terms: you create two versions of the same email (Version A and Version B), change one element between them, send each version to a portion of your list, measure which performs better, then automatically send the winning version to the rest of your audience.

It is a straightforward concept that, when applied consistently, compounds into meaningfully better email performance over time.

A/B Testing vs Multivariate Testing — What Is the Difference?

Pardot supports both, and they serve different purposes.

A/B testing is for list emails — it tests one change between two versions and is quick to set up. Multivariate testing, on the other hand, compares multiple changes between versions of your marketing assets. In Pardot, multivariate testing is used for landing pages. Multivariate tests take a little longer to set up and require a larger sample size.

For email, stick to A/B testing. Change one variable at a time. If you change the subject line, the sender name, and the CTA simultaneously, you will have no idea which change drove the result.

What Can You Test in Pardot Email A/B Tests?

With Account Engagement (Pardot) A/B testing, you can test the following factors — and remember, it is best to test one at a time: the email template content (body copy, images, layout, CTA), the sender name, the reply-to address, and the subject line.

Here is how to prioritise what to test first:

Subject line — The highest-impact variable for open rates. Test length (short vs descriptive), tone (question vs statement), personalisation (with vs without first name), and curiosity vs directness.

Sender name — "Acme Inc" vs "Sarah from Acme" can produce dramatically different open rates, especially in B2B where trust and familiarity matter.

CTA copy and placement — "Download the guide" vs "Get your free copy" or above the fold vs at the bottom of the email.

Email body length — Short and punchy vs detailed and informative. This depends entirely on your audience and where they are in the funnel.

Personalisation — With vs without dynamic fields, or different levels of personalisation in the opening line.

By testing different elements of your emails, you can increase open rates by discovering which subject lines or preheader text grab your audience's attention, boost click-through rates by determining which calls to action or content drive the most engagement, and improve conversion rates by identifying the elements that encourage recipients to take the desired action.

Step-by-Step: How to Set Up an A/B Test in Pardot

Note: A/B testing is available for emails sent via the classic email builder. Make sure you are working in the right interface before you start.

Step 1 — Create a new list email Go to Marketing → Emails → List Emails and click + Add List Email. Give it a clear name that indicates it is a test (e.g. "Newsletter May 2025 — Subject Line Test").

Step 2 — Enable A/B testing On the email creation screen, look for the A/B testing option and toggle it on. This activates the two-version workflow.

Step 3 — Select your template Select an email template. A copy of your existing content will automatically be created for Version B. You now have two identical emails to work with.

Step 4 — Make your single change On the building tab, you will be able to switch between versions A and B. On the sending tab, you will be able to change the sender name, reply-to address, and/or subject line between versions A and B.

Make only one change. If you are testing the subject line, keep everything else identical across both versions.

Step 5 — Configure your test parameters Continue scrolling down and you will find the section to configure how your A/B test should run. Set how long you want the test to run with the sample size before a winner is selected — any duration from 1 hour to 30 days — the criteria you want the winner selection to be based on (opens or clicks), and the percentage of your send list you would like to use for testing.

A few practical guidelines here:

• Use opens as your metric when testing subject lines or sender names
• Use clicks as your metric when testing body content or CTAs
• A test duration of 4–24 hours works for most B2B lists
• Allocate 20–30% of your list to the test (10–15% per version), then send the winner to the remaining 70–80%

Step 6 — Select your send list and schedule Choose the list you are sending to, set your send time, and review everything before confirming.

Step 7 — Send and wait Once the email is sent, Account Engagement (Pardot) will send the email to the sample group, then record the results based on your selected criteria. When the test duration ends, Pardot automatically sends the winning version to the remainder of your list.

How to Read Your A/B Test Results

After the test completes, go to the email record to view the results. You will see open rates, click rates, and the declared winner side by side.

Do not just look at which version won. Ask:

• How big was the difference? A 0.5% difference in open rates is likely noise. A 4% difference is meaningful.
• What was the sample size? A test on 200 people tells you much less than one on 2,000.
• Did the result match your hypothesis? If you predicted personalisation would win and it did not, that is worth understanding.
• Can you replicate this? Run the same test again with a different segment to validate the result before changing your permanent approach.

Keep a simple log of every test you run — what you tested, what won, and by how much. Over 10–15 tests, clear patterns about your audience's preferences will emerge.

A/B Testing in Pardot Engagement Studio

Standard A/B testing works for one-off list emails. But what about nurture sequences?

Pardot does support A/B testing within Engagement Studio, allowing you to test email variations inside automated journeys. This is particularly valuable for top-of-funnel nurture emails where small improvements in click-through rates compound across hundreds or thousands of prospects over time.

To set this up, use the A/B test step inside your Engagement Studio canvas, define your two email variants, and set the winning criteria. Pardot will track performance and route future prospects to the better-performing version.

Common A/B Testing Mistakes in Pardot

Testing too many variables at once. If Version A and Version B differ in subject line, CTA, and body length, you cannot attribute the result to any single change. Test one thing at a time, always.

Running tests with too small a sample. With fewer than 200 recipients per version, your results are statistically unreliable. The smaller the list, the more cautious you should be about acting on results.

Setting the test duration too short. A one-hour test will only capture people who happen to check email in that window. Set a minimum of four hours, and for B2B audiences, 24 hours is often better to account for time zones and work schedules.

Only testing subject lines. Subject lines are the easiest thing to test, but they are not always where the biggest gains are. Body content and CTA testing often yields more valuable insight for conversion-focused campaigns.

Not documenting results. A/B testing only builds institutional knowledge if you record and share what you learn. Keep a simple spreadsheet or Notion doc that tracks every test.

Start Testing, Stop Guessing

The difference between a marketing team that improves every quarter and one that stays flat often comes down to how systematically they test. Pardot's A/B testing is straightforward to configure and the insights it generates are genuinely useful — but only if you run tests consistently, document results, and actually change your approach based on what you learn.

Pick one element of your next email, form a hypothesis, run the test, and record what happens. That single habit, repeated across every campaign, will compound into meaningfully better results over the next 12 months.

Want to go deeper? Explore how Pardot Engagement Studio can automate multi-step nurture sequences and apply A/B testing inside automated journeys — so your best-performing email content keeps improving even while you sleep.