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Oftentimes PPC ai ad services like these share the same problem. They actually really don't have a ton of data to work with. Lines, copy, photo variance, even when added together from ad spinning services don’t offer much more than statistical insights. (AI is much more data-hungry)
When they use AI, it’s to detect the text size, colors, objects, and location. It’s not to understand why worked with the brand or recipient. The result is they tell you what works with above-average ads, but not great ads. Not targeted ads, not even on-brand ads… just …ads.
This is one of the challenges with only having ppc ad campaigns as a data point. You can get a lot of clicks, but you only have a single item of content to measure them against. It leads to telling brands built-in-red like Coca-Cola to "try the color blue. It will build trust." Not going to happen, even if it would work.
It's still cool tech, but IMHO this is one of the reasons that it's smarter to anchor the analysis at the coversion, the brand, the contact, and move backward. By understanding context of the players in that conversion, you get a ton more insight into the variables, and the variables that matter. With those three you find the variables that trigger conversion increases in the double digits... which at the click level can have massive impact.
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PPC ad services often lack sufficient data, relying on statistical insights rather than understanding brand-specific effectiveness. While they can identify what works in general, they may not provide targeted or on-brand recommendations. A more effective approach is to analyze conversions and brand context to uncover key variables that significantly impact conversion rates.