Spent $4,372 on FB ads so you don't have to

Welcome to the first part of CXL Growth Notes. Our goal is to create actionable content that will allow you to learn along and apply the lessons in your next growth project. 

In this case study, I'll walk you through our initial hypothesis, results, experiment setup and framework, and then show you the actual campaign (targeting, creative, performance).

Once done reading, let's discuss the experiment here.

Hypothesis: it's possible to deliver content in-feed via Facebook Ads as a brand awareness play while also getting email signups, all at a low cost ($2 per email signup).

Results:

• 338,753 people saw these ads, with CPM of $3.89
• 1,592 email signups with the average cost per email signup of $2.75
• 0.4 ROAS (this was a surprise)

The unexpected purchases that this campaign triggered brought down the cost per email signup to $1.65 and CPM to $2.33, making this experiment a success.

Experiment setup:

• 4 targeting variations (newsletter subscriber lookalikes, agencies, B2B SaaS, digital marketing interests)
• 4 creative variations (see below)
• ...giving us a total of 16 variations (4x4)

Experimentation framework:

• at the end, declare 2 targeting winners and 2 losers (ad set level)
• within the 2 targeting winners, declare 2 creative winners (campaign level)
• turn off the losers, start optimizing the winners
• replace the losers with new targeting/creative bets (innovate)
• make these decisions based on cost per email signup, but keep an eye on CPM and ROAS

This is what it looks like. You can get your copy here.

TL;DR: optimize the winners, innovate when replacing the losers.

Here are the 4 creatives we used:

With this setup, we were able to maximize our learning by understanding:

• which creative works best
• which targeting works best
• but also which creative works best with each targeting

The first loser was clear almost immediately. Agency targeting had significantly higher cost per email signup than others. We've turned it off quickly, but we'll experiment with different targeting setup around this audience later.

We also ran a retargeting campaign, but quickly turned it off too. Its cost per email signup was actually higher than prospecting campaigns, and unless we're getting email signups through retargeting for 10-20% cost of the prospecting campaigns, I'd rather show our ads to new audiences.

The second loser we declared was B2B targeting. Its cost per email signup was $3.21, also significantly higher than the winners. Here's the data we made these decisions on.

*We haven't declared creative winners/losers yet. Targeting proved to be a place where the biggest differences in performance happened, so we'll run another round of tests and then pick winners. So far, black-background and Peep's LI screenshot ads are top performers.

Comment section also went crazy. In my media buying experience (some $3M in ad spend), that's almost always a good sign, no matter how bad some of the comments are. Check some of them below.

Good, bad, ugly, we got it all here. Here's the ad link if you've got some popcornHere's the ad link if you've got some popcorn.

Important notes:

• Building an email list for CXL isn't a lead nurture play. Some of you will surely become customers, but our main goal is to simply use it as a content distribution channel, given the content delivered is really useful to you, the marketer. We'll know that once you've read this email.
• This type of campaign won't work unless we keep refreshing our creatives, due to inevitable diminishing returns. That's exactly what we'll be doing regularly. So, more case studies that we'll send to you.
• This experiment is not the most scientific one you've seen. Making big bets by testing significantly different approaches will help us learn more and achieve bigger wins than A/B testing that headline. This means some of our decisions won't be just based on performance, but gut feeling too. Marketing is both art and science, and we too often focus just on the science.

Learnings:

• The offer is the most important campaign element. This one worked because most marketing advice is given without first-hand testing it first. We did the opposite - everything we preach, we have and we will test ourselves first.
• You communicate the offer through copy. Your offer doesn't matter if the copy fails to deliver the message.
• The hook is the most important element in your copy.
• The biggest insights come from qualitative data. I've read every comment on these ads, replied to most, even posted these ads on LinkedIn twice and got even more insights (also exposure and signups) there. Don't just check the dashboard, talk to people.
• Don't spend money on paid media until you've got a high converting landing page. We did it here on purpose in order to understand the current conversion rate (that page hasn't received much traffic previous to this campaign, so sample size wouldn't have been big enough). What we could've done is A/B test it while running this traffic to it, but decided to do it step by step. Next case study will cover the landing page A/B test we just started running.

What did you think? If you have any questions, suggestions or future experiment requests, let’s chat on this LinkedIn post.

In the next experiment, we'll try to reduce cost per email signup to $1 by redoing our newsletter signup page, making it match the intent of the people landing on it (expecting growth case studies).

See ya soon.

First time here? You can get these biweekly by subscribing here.

Ognjen Bošković
Demand Gen at CXL

Let's connect on LinkedIn.

Our address: 901 S Mo Pac Expy, Suite 150, Barton Oaks Plaza One, Austin TX 78746

Manage your communication preferences