In today’s mini episode, I’m going to discuss three pitfalls that many advertisers fall into and three things they need to look out for while creating and testing AI-powered creatives.
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In many of the recent accounts that I have audited, there has been an explosion in the quantity of ads tested. This is not surprising because AI has made it easy for everyone to create tens or hundreds of ads very quickly. However, quantity is not always correlated with performance. It’s important to note that simply increasing the number of creatives will not solve your performance issues.
In today’s mini episode, I’m going to discuss three pitfalls that many advertisers fall into and three things they need to look out for while creating and testing AI-powered creatives.
Number one: Garbage in, garbage out. If you’re using whatever the AI generates for your ads without considering your target audience, the kind of messaging that resonates with them, proven ad formats, or common pitfalls, you’re going to end up with poor-performing ads. This is a very common cause of poor performance.
Number two: Focusing on a local maxima. You may have ads that have performed well, and you might use AI to generate more ads similar to those. This is a common pitfall that many marketers fall into, whereas they really should be coming up with brand new ideas and concepts.
Number three: Testing isn’t cheap. Oftentimes, when an advertiser multiplies their creative output, they need larger budgets to test the additional creative output. This requires a budget, which can eat into your performance metrics massively.
These are the three reasons why your AI-generated ads might be falling flat, and these are the three things we recommend thinking about and addressing if you’re making AI-powered creatives.
BEFORE YOU GO
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