AI : Can AI Pick Your Next Winning Ad? Experiment Results Revealed
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We’ve been exploring the exciting advancements in AI-powered ad design assessment, particularly platforms that leverage data analysis to identify high-performing visuals. But how accurately do these platforms predict real-world campaign success? To answer this critical question, we conducted a small-scale experiment. The results offer valuable insights for marketers seeking to optimise their creative strategies with AI. Let’s delve into our findings.
Methodology
The experiment was structured in two phases. First, two distinct ad designs were inputted into FIMMICK CreativeMax, an AI-powered ad design assessment platform, to be evaluated across key metrics: clarity, focus, balance, and engagement.
Following the assessment, a live ad campaign featuring both designs was initiated. To maintain consistency and ensure a fair comparison, all campaign parameters, including budget allocation, bidding strategy, campaign duration, and target audience, were identical for both ad variations. Upon campaign completion, performance data for each ad was analysed and compared against the initial predictions generated by CreativeMax.
Hypothesis
We hypothesised that FIMMICK CreativeMax’s assessment of ad designs would accurately predict real-world campaign performance. Specifically, we anticipated that the design receiving a higher overall score would yield superior results, reflected in metrics such as reach and click-through rate.
Experiment
Two distinct ad designs were created to understand how AI evaluates visual elements and predicts viewer attention. Ad A featured a user engaging with a report, while Ad B emphasised the concept of AI.

Overall, FIMMICK CreativeMax favoured Ad B, awarding it higher scores for clarity and balance. For Ad A, the platform anticipated an initial focus on the woman’s face, followed by the text. In contrast, Ad B was predicted to draw initial attention to the robot’s hand before viewers scanned the remaining elements.

Result
Both ad designs were deployed in identical Facebook and Instagram campaigns, running concurrently for seven days. The results demonstrated a clear performance advantage for Ad B over Ad A:
- Reach: Ad B achieved a 17.4% higher reach than Ad A, indicating its effectiveness in connecting with a larger audience of potential customers.
- CPM: Ad B exhibited a 43.6% lower CPM than Ad A, signifying greater cost-efficiency in engaging the target audience.
- Link Click: Ad B generated a 37.5% higher click-through rate than Ad A, demonstrating its superiority in driving traffic to the intended destination.
Our experiment demonstrated that the ad design favoured by FIMMICK CreativeMax’s AI analysis (Ad B) delivered superior real-world performance. Its higher click-through rate, lower CPM, and broader reach underscore the AI’s ability to predict ad effectiveness accurately.
Explore Further: How can AI be used to improve ad design?
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Conclusion
This experiment provides compelling evidence that AI technology can effectively predict the performance of social media ad designs. This presents a significant opportunity for brands and marketers to streamline their creative processes, identify high-performing visuals, and optimise campaign efficiency. By leveraging AI-powered insights, businesses can reduce reliance on time-consuming and resource-intensive A/B testing.
It’s important to note that this was a small-scale experiment, and results may vary depending on factors such as industry, product, and target audience. Further testing and customisation are always recommended to determine the most effective strategies for individual campaigns.
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