People think they scroll through social media freely. But tech giants constantly test them, tweaking ads and content without their awareness. A/B testing is a method where users see different ads to determine which one works best. But social media platforms complicate this process.
Facebook and Google use complex algorithms that control who sees what. This means even they struggle to understand why an ad succeeds on social media platforms.
WHY A/B TESTING IS FLAWED
True experiments require randomization. But Facebook’s algorithm selects users based on their likelihood to engage, distorting test results. Marketers assume an ad’s performance depends on its design. But algorithms decide which audience sees it, making the results misleading, especially on socialmedia.
HOW ALGORITHMS MISINTERPRET CONSUMER BEHAVIOR
Users might buy a product before seeing its ad. Platforms may wrongly credit the ad for influencing their purchase. Algorithms group users based on unseen patterns. Even tech companies struggle to explain why certain users get selected for socialmedia ads.
THE BROADER IMPACT OF ALGORITHMIC ADVERTISING
Cost-driven algorithms often exclude women from STEM ads. They are pricier to target, so they miss opportunities they might have considered. When algorithms see low engagement from certain groups, they stop showing them specific ads, reinforcing existing biases on social media.
Facebook, Instagram, and TikTok run hidden tests daily. A Facebook employee revealed users are part of about 10 experiments at any time, especially on social media.
Misinterpreting Data Can Be Costly
If an ad performs well, it may be due to the algorithm, not the content. Businesses could alienate broader audiences by over-relying on such results. Modern AI micro-targets individuals rather than groups. Even advertisers don’t fully understand how AI selects users for specific social media ads.
Understanding hidden experiments is crucial. As AI evolves, both marketers and users must stay informed about how social media shapes their online experience.
