This project represents "phase 2" of the overall Astrofluenced growth strategy, which we detail in our scaling AI brand case study. We began experimenting with new technology right as Adobe Express updated into a more powerful tool for creating content on the fly, introducing generative capabilities. However, its winning benefit was its surplus of quality stock images and, more importantly, video clips that made storytelling on platforms like Instagram more accessible than ever.
We created two series meant to showcase the personality of various signs in relatable situations: "Falling in Love" and "Just Fired". In retrospect, it probably should have been "Just Laid-off" as it would have gotten more engagement. People share as a way to identify and brand themselves, and it's much more common for people to talk about being laid off than getting fired, which remains rather taboo and not something people outright share, no pun intended.
These kinds of after-thoughts are what make creating viral social media content possible. When you're starting a brand and finding your audience, unless you're going to go super lowest common denominator and you don't have much pre-planned messaging to stick to, you're just going to have to experiment. But the key to experimentation isn't just the analytics - it's actually scheduling time every other day to review posts. Do a 'step-back' and write candid thoughts on each post - why it did well and why it didn't. This was where strategists spent a lot of their time back when I was creating viral content regularly for PETA, as detailed in our viral campaign strategy breakdown.
The reason step-backs and experimenting and analytics are so important is that you are very frequently surprised. Our next batch is a great example of that. These videos are beyond simple - something that takes seconds to put together compared to the story-telling images above. Where the above might get a few hundred views, these simpler versions got thousands of views every time.
The reasoning, discovered in doing step-backs, was often obvious - these videos were mesmerizing and fun to watch. For where our audience was, for where our TikTok viewers' heads were at, this was the preferred content. It's honestly a great example of marketing today in general: If you want success, you have to follow the data. I've consulted with more than a few growing brands that, these days, you just don't get to always decide what your brand is about if you're looking for success. You follow the numbers. You have a little freedom - once you learn what works you get to build around that. But too often brands - especially large companies - stick to only posting their messaging.
Because you can't argue with something that takes 1/10th as long to make AND reaches 10X the number of people. You need that - lots of that - on your page. Then intermix your messaging where you can. It's the marketing funnel at its core. It's also where automation started to become an obvious go-to. Imagine, the video that was taking 1/10th as long to make to reach 10X people, you can now make in 1/100th the time. That's a lot of crazy, exponential math I can't even wrap my head around.
Once we discovered the style that performed best, we eventually found ways to work more of our messaging in, all while using an API service and images with copy already prepared by AI generative automations that filled up the database that fed the API service that edited together our videos in the cloud. Imagine getting videos that reach 10X at 100 times as fast, just sent to your Dropbox via a Webhook. Once you have the automations set up, you produce content without ever leaving your database - Notion was our go-to.
Strategic content targeting adjacent interests:
This project fundamentally changed our understanding of modern content strategy. While traditional thinking often emphasizes complex, highly produced content, our data revealed that simpler, more hypnotic content could achieve dramatically better results with far less effort. This insight, combined with our automated production pipeline, allowed us to scale our content operation exponentially while maintaining quality and engagement.
The true innovation wasn't just in the automation technology - it was in recognizing that perfect efficiency isn't always about creating the most polished content, but about finding the sweet spot between what resonates with your audience and what can be produced efficiently at scale. By letting data guide our creative direction and building systems to automate production, we transformed a traditional content operation into a highly efficient, API-driven production engine that could adapt and scale with our growing audience. This approach proved that with the right combination of data analysis, automation technology, and strategic thinking, it's possible to achieve exponential growth in content reach while dramatically reducing production overhead.
The key is being willing to let go of preconceptions about what content "should" be and instead focus on what actually drives engagement and can be scaled effectively.