For the past ten years, we’ve been really focused on finding the right audience when it comes to getting new users for mobile apps. We’ve tried to be super specific about who we’re targeting, looking at things like demographics, what people are interested in, and how they behave. The idea was that if we could just reach the perfect person, they would definitely download our app or make a purchase.
However, it seems we overlooked a vital part – the creative aspect.
You can show your ideal customer the perfect ad, but if it’s not personalized, they’ll just keep scrolling. The issue is that trying to customize each ad by hand is a sure way to get overwhelmed. Creating a unique version of your ad for every group of people is just too time-consuming and costly, and it slows down your ability to come up with new ideas.
This is the personalization paradox: we have the data to speak to specific personas, but we lack the production capacity to actually build the assets. Fortunately, the integration of generative AI is finally bridging that gap.
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Moving Beyond the “Generic Average”
For years, our teams at UA had to play it safe and target the middle ground. We’d create one or two big assets that were supposed to appeal to everyone, but they ended up not really resonating with anyone. The problem was, we were focused on getting our message out to as many people as possible, rather than making sure it actually meant something to the people who saw it. We were prioritizing reach over relevance, and it wasn’t working.
With modern automation, we can stop producing for the average and start producing for the segment.
Imagine you’re promoting a productivity app. Instead of one video, you can now generate three variations in the time it used to take to produce one:
- The Student Persona: A script focused on exam season and deadline management.
- The Professional Persona: A narrative highlighting deep work and meeting scheduling.
- The Parent Persona: A variation centered on balancing household chaos and personal goals.
Each variation uses the same core value proposition, but the hook and the narrative are tailored to the specific pain point of that segment. This isn’t just “more content”—it’s relevance at scale.
The Balancing Act
The problem with automation is that it can go too far if nobody’s watching. When you automate how you personalize things, you might lose the tone and feel of your brand, or even worse, end up with content that doesn’t flow well and feels all over the place.
Making things personal really works when it feels like you’re having a real conversation, not just mixing and matching from a database. The key is to keep the main message of what you’re selling consistent, while using artificial intelligence to change up the outside stuff – like the hook that grabs people’s attention, the character telling the story, or the specific situation. There are tools like apptovid.com that let teams do just that: take one link from the App Store or Google Play and create lots of different versions that try out different approaches for different groups of people. This way, you can see what works best for each group and make your message feel more personal and relevant to them.
Creative as a Variable
To win in today’s feed-driven economy, you have to stop treating your video ads as fixed objects. Start treating them as variables in an equation.
If you aren’t personalizing your creative for different segments, you are effectively paying a premium for clicks that never happen. By leveraging automation, you can finally align your creative output with your targeting precision.
The future of User Experience (UA) isn’t just about understanding your audience better, it’s about creating content that resonates with each individual. If you’re still using the same old approach, where one piece of content is supposed to work for everyone, you’re missing out on a huge opportunity to improve your workflow. It’s time to move away from broadcasting your message to the masses and start having personalized conversations with each user, even if it’s on a large scale. This means using data and insights to create unique experiences that speak directly to each person, rather than relying on a one-size-fits-all approach. By doing so, you can build stronger connections with your users and drive more meaningful engagement.
