Easy A/B Testing Tips for Top-of-Funnel Leads

When you first introduce yourself to potential customers, aka top-of-funnel leads, you don’t know much about them except for the small amount of interest they expressed to end up on your mailing list.

How do you know which CTA button color they will respond to best? What subject line will get them to open your email in the first place?

Top-of-funnel leads are a blank slate for testing. Here, you can experiment to figure out what your leads like and what they don’t, before they end up too deep in the funnel.

What interesting is that, more often than not, top-of-funnel engagement data and A/B testing leads to more questions than answers. It’s more like asking questions to learn what other questions you can ask. In today’s post, we not only go into what questions you can ask using A/B testing, but also how to turn those questions into experiments you can act upon.

Break It Up

First, take your email and separate it into elements. This is a critical step.

Each and every element of an email required a design decision. When you made the email initially, you may have used a template and didn’t decide on each and every one of the elements.

But each element that isn’t optimized is one that could make or break the success of your emails.

Here are some elements to look at:

  • Subject line
  • Titles
  • Body copy
  • Logos
  • CTA
  • Images (or lack thereof)
  • Background color

Questions to Ask

For each element of an email, it is imperative to figure out why or why not that element specifically is effective. Look for weaknesses in these areas:


Does each element make sense? This can be everything from the from name to a visual element.

Why is this graphic here? Does your copy read without confusion?

Pick apart your content. Send it to someone else – someone who has never even seen your emails before, preferably.

The less familiar you are the better. Have them critique the elements. Their fresh perspective will make it easier to identify potential points of friction.


Does this element add to your email? What does it add? What is its purpose? Would it go better somewhere else?

Examine your email and take away any graphic that might not actively contribute to the purpose of your email.

The same goes for any sort of copy. Each and every word must contribute something.

If it doesn’t, lose it. It doesn’t matter how clever you think it is or how nice you think it looks. Emails are about engaging, precise communication.

Don’t waste your leads’ time.

Value Proposition

Make sure that if you ask for a form of value from your customer, you have something to give in exchange.

Why should they give you anything? This value can come in many forms, from a free ebook to a discount on your offering.


This isn’t mandatory, but urgency is an effective way to ensure a customer makes a choice. Without urgency, they might believe that they have all the time in the world.

Urgency can take the form of a discount (value proposition) that expires. Or that there is a limited amount of an offering.

Be careful with urgency though, it can backfire if the urgency isn’t real. You will have betrayed the trust of your lead, something that isn’t easy to get back.

Create Hypotheses

For each weakness that you identify, create a hypothesis as to what would fix that.

For example, if you notice your CTA isn’t compelling, create a hypothesis that reads.

"We will see an increase in click-throughs if the button color is changed from blue to red."

From there, create two separate emails, with one button the original color and another that is red. Test these one a small group of top-of-funnel leads.

Rinse and repeat. As you run more and more tests, you will gain more answers to your questions and reveal additional points to test.

Keep this up and you should see your email engagement numbers soar and revenue along with it.


Let us know what you think:

  • What are your favorite A/B tests to run at the top of the funnel?
  • How do you implement them?
  • What was the most surprising change you made using A/B testing?



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