A groundbreaking study in Marketing Science introduces the PE-Score algorithm, which uses artificial intelligence to predict sales impact from TikTok influencer ads. Developed by MIT researchers, this 'product engagement score' outperforms traditional metrics, providing brands with crucial insights into which ads are likely to convert viewers into buyers. By focusing on actual engagement rather than influencer popularity or ad budget, the algorithm enables more effective ad spending and enhances collaboration between brands and influencers. The tool's commercialization aims to reduce inefficient trial-and-error marketing practices.
We found that many popular TikTok ads fail to boost sales because influencers often prioritize their personal brand over the products they promote. To solve this, we developed the 'product engagement score,' a computer vision-powered metric far more accurate than traditional methods like video likes or influencer popularity.
This tool answers the critical question for brands: which ads will drive sales? The product engagement score predicts sales impact more effectively than video popularity, influencer status or ad budget.
By leveraging this tool, brands can determine which ads will resonate with consumers before they are launched, leading to better resource allocation and stronger return on investment.
This breakthrough is poised to reshape influencer marketing by enabling brands to optimize ad spending, improve influencer collaborations and reduce costly trial-and-error approaches.
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