Can AI Replace In-Person Consumer Testing of Packaging Designs?

AI technology offers a real-time alternative to traditional surveys and focus groups for package design testing and online product detail page optimization — and claims up to 90% predictive accuracy for consumer preferences.

Software analytics firm Vizit uses its “Audience Lens” technology to enable a faster, more cost-effective alternative to in-person testing of new products, services, content, and campaigns without the need for surveys or focus groups. Numerous reports cover its use in optimizing package designs and product detail pages (PDPs) for snacks, alcoholic beverages, household cleaners, and other products.

AI technology is often only as good as it’s programmed to be, right? Well as it turns out, Vizit is establishing a pretty successful track record for uncovering what will resonate with shoppers, often achieving an 85-90% predictive accuracy rate. One global snack food company even found Vizit’s Audience Lenses model to be 100% predictive of traditional research. Source: packagingdigest.com

人工智慧可以取代消費者對包裝設計的現場測試嗎？人工智慧技術為包裝設計測試和線上產品詳情頁面優化提供了傳統調查和焦點小組的即時替代方案，並聲稱對消費者偏好的預測準確率高達 90%。

軟體分析公司 Vizit 使用其「受眾鏡頭」技術，提供更快、更具成本效益的替代方案，以取代面對面測試新產品、服務、內容和活動，而無需進行調查或焦點小組。許多報告涵蓋了其在優化零食、酒精飲料、家用清潔劑和其他產品的包裝設計和產品詳情頁面 (PDP) 中的應用。

人工智慧技術的優劣往往取決於其編程，對嗎？事實證明，Vizit 在發現哪些產品能引起購物者的共鳴方面建立了相當成功的記錄，預測準確率通常達到 85-90%。一家全球零食食品公司甚至發現 Vizit 的受眾鏡頭模型可以 100% 預測傳統研究。