# AB Testing Ads? Discover the Better Way with Multivariate Testing Over 6,000 users. July 20, 2022 Written by [Dan Pantelo](/content/authors/dan-pantelo/index.html) Average reading time: 5 minutes ## A/B testing ads isn't enough. Learn how to use multivariate testing instead to get more accurate insights and optimize your ad campaigns for success. A/B testing alone doesn’t cut it anymore when it comes to ad creative. Even though it’s automated and typically executed in-market, A/B testing delivers the shallowest level of data available. It can tell you which of two or three ads was the higher performer — but never why. There’s got to be a better way! In episode 3 of Resting Ad Face, our VP of Performance Marketing, Susan Wenograd, and I talked about: - the major downfalls of A/B testing - why brands today need a deeper level of creative insights - how a different kind of creative testing (spoiler alert: multivariate testing) can get you there Resting Ad Face, Episode 3: A/B testing ain't got nothin' on multivariate - YouTube [Watch here](https://www.youtube.com/watch?v=ZEQ-HExod-I) #### Here are some highlights: ## Better ad testing can inspire creatives to design smarter Copywriters, art directors, and designers should want to know why their ads worked or not. And while A/B testing can tell you that an ad did indeed perform well, it can’t deliver the underlying data as to what made it perform well. There’s nothing concrete for creatives to pull forward into future ad concepts. With multivariate testing, data can be used as inspiration. This removes some of the “fear of the blank page.” Creatives never really have to start from scratch because they have a deep, baseline understanding of what messaging, colors, images, etc. have worked (or not worked) before. ## Better ad testing brings creatives and marketers together A/B testing often forces creatives and marketers into silos, each side doing the work needed to get to and through the test, but never truly collaborating. Multivariate testing acts as a forcing function to bring these two sides of the house together. Because this method requires a strategy to be built around which creative assets will deliver solid results, creatives and marketers have to work in lockstep from the outset. The hypothesis begets the right creative assets, the right creative assets beget the right concepts, the right concepts beget test results, and test results become a shared data set for the entire team — powering both the next round of creative concepts and testing strategy. ## Better ad testing creates a common language for the entire team There’s often a communication barrier that comes into play when marketers try to relay which ad creative is working or not after an A/B test. A common interaction is to show the best-performing ad and ask the creative team to “do more of this.” This leaves creative teams asking, “more of what?” Multivariate testing eliminates this barrier. All creative variables are isolated, so both the media and creative teams understand which elements are boosting performance. This gives both teams a common language to work from moving forward, one built on data and specificity. For more, watch the full episode — [A/B testing ain’t got nothin’ on multivariate](https://www.youtube.com/watch?v=ZEQ-HExod-I) — or [subscribe to Resting Ad Face](https://restingadface.transistor.fm/) on your favorite podcast platform. #### Transcript **Jess:** Hey, everybody. Welcome to Resting Ad Face. I am Jess Cook. I'm the Head of Content at Marpipe. And I am responsible for all things kind of brand content and creative. And I'm here with Susan Wenograd. My work wife. **Susan:** Exactly. My day is not complete unless I hang out with Jess. I'm Susan Wenograd. I am the VP of Performance Marketing at Marpipe. So I take all of Jess's really great creative and figure out ways to promote it and amplify it. **Jess:** So today we are gonna talk a little bit about why A/B testing is no longer really the thing that's gonna get you there. **Susan:** Yeah, absolutely. So, you know, I think A/B testing has like been the traditional kind of go-to for testing ad creative for a long time. **Jess:** Even before it was automated or digital. But really today it it's just no longer enough. It's not gonna get you like that deep level of creative data that you need. Especially now that we have so many barriers to targeting in terms of privacy and, and opt outs, and iOS 14, things like that. **Susan:** So kind of the new modern richer, deeper way to test ad creative nowadays is called multivariate. It's relatively new for people in terms of using it for, for ad creative. And so we wanna talk about, you know, the differences between those two things today and why A/B testing alone is no longer enough, you know, why, what makes multivariate testing different and better. **Jess:** Multivariate testing is a testing method that measures every single element within an ad. So not only are you testing the ad itself, you're testing the elements within it, the headline, the background color, the image, the call to action, the button shape, whatever is in there, right? Whatever your heart desires to test. **Susan:** So, you know, traditionally when you'd get an ad, it's just like this one file, you know, and it's like, this is the concept, all these pieces work together. When you start thinking about it from a multivariate perspective, that's when it becomes more thinking about it as a group of elements that are working together, as opposed to one thing that just happens to have these elements in it. **Jess:** So we know what multivariate testing is. We're understanding modular design. And so now I think we can talk through the four main points of why A/B testing alone is no longer enough: 1. **A/B testing can only tell you which ad wins; multivariate testing can tell you why.** 2. **A/B testing only delivers short-term performance.** 3. **A/B testing keeps creatives and marketers in silos.** *Multivariate testing requires collaboration between teams, creating a common language to facilitate communication.* 4. **A/B testing only measures a few variants of an ad.** *Multivariate testing allows for numerous combinations, providing deeper insights.* This methodology enriches both the creative and testing processes, making it efficient for future campaigns. In short, TL;DR: A/B testing, not enough. Multivariate testing. Try it.