Machine Generated Content is here. It'll be cheaper, faster and better. But what's the best way to try it? Here are 8 principles to get started.

1. Tech: Find a Creative AI platform. There are a few already, but many more will emerge. Find one with a long roadmap runway, to go deep with.

  • Will it be fast, good and cheap?
  • Can you ask to see the output ads?
  • Is it optimized for the platform where you invest the most?
  • Does the team have a proven track-record building AI and ads that deliver results?

Ask tough technical questions and focus on where the roadmap is heading, not just what it can do today.

2. People: Fewer, better humans. Try to keep humans out of the loop. Don’t create a review committee to slow everything down. Empower somebody directly responsible for campaign performance with a self-serve tool. Consolidate decision making. Some of the best growth teams I’ve seen work in triads: a marketer, a designer, and an analyst. Perhaps this will collapse further to just two or even one superhuman.

3. Ad ABC’s = Attention, Benefit, CTA. Most top-performing ads broadly follow the ABC formula. And so should at least some of your MGC output ads, so that you can start your first tests with strong contenders. ABC ads grab attention in the first second, through a thumb-stopping hook message and/or visual. The more limbic the better: fear, sex, food, money triggers all stop thumb-scrollers in their feed. Then they communicate the benefit, functional and/or emotional, often with social proof testimonials or reviews. Adding an RTB (Reason to buy/believe) often helps. Finally they close with a call-to-action, often time-bound (“40% off before Memorial Day”) and a language that exactly matches the button selected for each ad. (“Shop now,” “Sign up”)

4. Volume: Aim for a strong dozen to test. Stop hunting for one sure-thing great ad. Every time I try to predict which ad will perform best, I get it wrong. Aim for a strong dozen to run in a test account, and keep the audience targeting as broad as possible, to let Facebook do the hard work getting each ad in front of the right prospects. Facebook’s Campaign Budget Optimization (CBO) might help here, especially for popular categories where a lot of previous buyer-signal exists, but it doesn’t work in all cases. You might prefer to guarantee minimum delivery against each test ad, so you don’t kill a “golden goose” ad too early. When ads are clearly working in test accounts, study the buyer profile to understand the audience, and consider promoting winning ads into scaled accounts, where they can scale up until fatigue sets in. By then, you should have iterated new strong ads to replace fading stars, possibly built from a similar DNA.

5. Variation: Optimize for meaningful difference. Being irrelevant on Facebook can be very expensive, so keep trying to use assets and language likely to be meaningful for your target audience. Use the power of variety to find and unlock new audiences. Don’t assume videos or “stills” will work better; it varies ~50/50 by brand, by level of the funnel, and by how the Facebook algorithm is behaving that week. Keep an open mind. Or better still, use a Creative AI programmed to keep its mind open.

6. Early prototyping: Crack the code, then invest. Some marketers view Creative AI as a new prototyping tool early in the creative process. Use existing assets and AI to find the language and visual hooks that connect with audiences, and then let design teams translate these into longer, more polished final films, perhaps with higher production values. For instance, incubate the ad on Facebook, and then invest behind a more traditional 30 second TV Ad to hit broader reach and frequency targets. I wonder if we’ll ever see a $5m Superbowl spot born in MGC?

7. Brand communities > brand managers. A good Creative AI tool will let you input all your logos, fonts and colors, and drop in your own assets, but brand managers are still often concerned about giving up style control to a machine. They don’t need to be. With MGC there should always be a human review before campaigns are launched, and “off-brand” ads can be rejected or edited. But the fear remains; brand managers like to manage. Yet the evidence suggests that consumers are now more attracted by brand communities, where they also have a voice. In truth, unless you are managing a brand like Apple, brands today are a lot less consistent than they think they are and have to adapt more natively, especially on social platforms. Also, brand teams are often overly fixated on storytelling. I haven’t seen that work well on short-form platforms like Facebook.

8. Production: Faster, cheaper mobile-first creative assets. As outlined, creative production costs will drop overall because it’s far simpler to collect small batches of high-quality clips and images for MGC, than to storyboard, shoot and edit scripted films. As teams learn to use AI tools, they will also rethink how they produce their assets, likely shooting a wider variety of shorter, higher-quality assets, and a mix of UGC, film, stop-motion, and even animation. In short, shoot it all, throw it into the sausage-maker, then review and edit.

Read the full post on Medium! "How to Use Creative AI to Crack Your FB Advertising"

join the waiting list