Multivariate Testing vs. A/B Testing: Which Works Better in Email Marketing?

Have you ever sent an email and wondered if it could’ve been better? Maybe you thought, “What if I used a different color or image?” “Maybe the call-to-action button felt out of place?” or “Should I have made the subject line a bit humorous?” Well, you’re not alone. Lots of people who send marketing emails think like this all the time.

That’s where testing comes in. Imagine cooking—tasting the dish to check if it needs more salt. We can’t exactly taste emails, but we can test them to make sure they’re more appealing to those who receive them.

You are not just guessing but testing scenarios and choosing the one that people click on. Is it the subject line? The time of day you send it? The picture at the top? By trying different things, you can find out what works best for your readers.

Now, let’s talk about two main ways to test emails: multivariate testing and A/B testing. Don’t worry if those sound like fancy math terms—they’re actually pretty simple ideas. Why are these important? Because we need to craft emails that convert, but this requires constant optimizations. And this is where testing helps in email marketing.

Let’s break down what each means and how they can help you send stellar emails.

Two Ways to Test: Multivariate and A/B

A/B testing is like when you can’t decide between two shirts, so you ask a friend which one looks better. You’re comparing two options to see which one wins.

A multivariate test is more like trying on different combinations of shirts, pants, and shoes to see which outfit looks best overall. You’re changing a few things at once to see how they all work together.

A/B testing is the simpler sibling and works in a similar way in email marketing. You make two versions of your email campaign and test each to a small email list segment. The version that receives a better response (more clicks, opens, etc.) becomes your winning recipe. Multivariate testing takes things a step further than A/B testing. Instead of simply comparing two versions of one thing, like a subject line, you can test different versions of several elements all at once. This way, you can figure out which mix of elements works best.

Now, we’ll take a closer look at the multivariate test.

What Is Multivariate Testing?

Definition and basics

So, what is a multivariate test? It’s a way of trying out lots of different things in your email all at once. Imagine you’re redecorating your room. Instead of just changing the curtains and seeing if you like it, you change the curtains, the bedspread, and the rug all at the same time. That’s kind of like multivariate testing for emails.

Here are a few things you might test in an email:

• The picture at the top: Maybe a photo of people using your product or a funny cartoon?
• The words in the subject line: Should it be funny, serious, or mysterious?
• The color of the “Buy Now” button: Red, blue, or green?
• Where do you put different bits of information: Price at the top or bottom? Product details first or last?

You can see from the above multivariate testing examples how all these changes work together. It’s like finding out that your blue curtains look great with the green rug but not so great with the red bedspread.

How it’s different from A/B testing

A/B testing is simpler. It’s like those spot-the-difference puzzles where you have two almost identical pictures side by side. You change just one thing and see what happens. 

For example, you might send out two exactly the same email versions, except one has a picture at the top and one doesn’t. Then you see which one gets opened more.

Multivariate testing lets you try more stuff at once. But it can get tricky, kind of like juggling. The more balls you add, the harder it gets to keep track of everything. You need lots of people to send emails to, or it might not work well.

Advantages of multivariate testing compared to A/B testing 

Multivariate testing is great in certain situations:

1. You can test multiple variables at once. Multivariate testing allows you to change several elements simultaneously, giving you more insights in a single test. For example, you can test different subject lines, images, and button colors all in one go. 
2. It shows you how different parts of your email play together. You can see how different components work together, like how a funny subject line performs with serious-looking images or button colors. Who would’ve guessed?
3. It’s a time-saver if you want to give your whole email a makeover. Instead of testing one thing at a time, you can overhaul your entire email design. Let us say this again: multivariate testing can be faster than running multiple A/B tests.
4. You get to really dig into what makes your emails tick. You might discover that your readers love emojis in the subject line, but only when the email is about sales, not when it’s a newsletter.
5. It helps you make the whole email better, not just one part. You can enhance the overall email effectiveness.
6. Saves time in the long run. Sure, it might take a bit longer to set up at first, but then you’re testing multiple things at once. It’s like meal prepping for the week—more work upfront, but then you’re set for days.

Limitations of multivariate testing compared to A/B testing

But it’s not always sunshine and rainbows with multivariate testing:

1. You need a pretty big email list. It’s like trying to take a survey—the more people you ask, the more accurate your results. I learned this the hard way when I tried to run a complex test with my tiny list of 500 subscribers. The results were about as clear as mud.
2. It can get a bit complicated. Trying to figure out all the different combinations can make your head spin. I remember staring at a spreadsheet of results, feeling like I was back in high school math class.
3. It takes more time to run. You’ve got to wait for more people to open and interact with your emails. It’s like waiting for a cake to bake—you can’t rush it or you’ll end up with a gooey mess.
4. Sometimes it’s hard to figure out exactly what worked. With so many changes, it can be tricky to pinpoint the real winner. I once ran a test where everything improved, but I couldn’t tell if it was the new subject line or the flashy GIF that did the trick.
5. It’s not great for big, dramatic changes. If you want to test two completely different email designs, stick with A/B testing. I learned this when I tried to compare our old newsletter format with a brand new one using multivariate testing. Talk about confusion!
6. You need more stuff to make it work. More time, more know-how, and usually fancier software. It’s like going from cooking at home to running a restaurant kitchen.
7. If you test too many things, the results can get watered down. It’s like adding too many toppings to a pizza—at some point, you can’t taste any individual flavor anymore.
8. When you need answers fast, it’s not your best bet. I remember trying to use it for a last-minute holiday campaign. Big mistake! By the time we got results, Christmas was over and we were into the New Year.

Remember, every email list is different. What works for one might flop for another. 

Comparative Analysis: Which Testing Method Is Better for Email Marketing?

It depends on what you’re trying to do:

• You’re just starting out:

Stick with A/B testing. You’ll get the hang of testing without it being too overwhelming.

• You have a big email list and want to fine-tune things:

Give multivariate testing a shot. You can tweak different elements to make it perfect.

• You need to make a quick decision:

A/B testing is faster and easier to understand. It’s like asking a yes or no question instead of an essay question.

• You want to see how different parts of your email work together:

Multivariate testing is your friend here. We think we have already explained this part earlier.

• You’re curious about one specific change:

 Go for A/B testing. It’s like trying on just one new hat to see if you like it.

• You have a hunch that several small changes could make a big difference:

Multivariate testing can help here. It’s like adjusting the seasoning, cooking time, and temperature all at once to make the perfect dish.

Let’s look at some situations where you might use each type of testing:

A/B testing example:

Imagine you run a pet supply store. You want to send an email about a sale on dog toys. You might test two subject lines:

• A: “Fetch These Deals on Dog Toys!”
• B: “50% Off All Dog Toys—This Weekend Only!”

You send each version to half of your email list and see which one gets opened more. This is a classic A/B test.

Multivariate testing example:

Now, let’s say you want to go deeper. You might test:

• Two different subject lines.
• Two different main images (a dog playing with a toy vs. a pile of toys).
• Two different button colors for “Shop Now.”

This creates eight different combinations. You’d send each version to a portion of your list and see which combination performs best overall.

A quick comparison

Here’s a simple way to think about the two:

Feature	A/B testing	Multivariate testing
Complexity	Low	High
Data required	Less	More
Insights	Basic	Detailed
Time	Short	Long

To Sum Up

Both multivariate testing and A/B testing can help make your emails better. A/B testing is great for simple, quick tests. Multivariate testing is good when you want to try lots of ideas at once and see how they all work together.

When it comes down to multivariate testing vs. A/B testing, think of it like choosing between a Swiss Army knife and a regular knife—both are useful, but one is more complex and versatile while the other is simpler and more straightforward. The key is to keep testing and learning. And hey, sometimes the “mistakes” lead to the best discoveries!