Pinterest pilots a new AI feature that converts product catalogs into interactive, shoppable collages to help advertisers boost visual engagement
This week, Pinterest disclosed that it is experimenting with “auto-collages,” an AI feature that enables advertisers to convert their product catalogs into shoppable collages promptly.
The new feature is intended to simplify the process of advertisers reaching consumers while also conserving time and creative resources, according to Pinterest.
The company observes that collages are among the most popular and engaging content categories among Gen Z users, with tens of millions of collages created on the platform. Pinterest discovered that users saved auto-collages at twice the rate of conventional product Pins during its initial testing.
Auto-collages combine product images into shoppable visual content determined by user engagement, ensemble ideas, similar products, and user saves.
For example, the feature may organize clothing that constitutes a fashionable ensemble by extant styles. Alternatively, it may generate a new collage comparable to extant collages that have garnered substantial user engagement.
Additionally, the feature has the potential to combine similar products and compile them into a collage. In another scenario, auto-collages may produce a collage containing products identical to those that users have saved on their boards.
In an announcement, Julie Towns, Pinterest Vice President for Product Marketing and Operations, stated, “Auto-collage was born out of the Pinterest Ads Labs program that launched last year, where we innovate new generative AI products that help brands stay ahead of the curve.”
“The auto-collages tool is a revolutionary advancement that utilizes artificial intelligence to provide brands with the ability to instantly transform their product catalog into innovative content that resonates with Gen Z and beyond.”
Pinterest has also disclosed that it will be revising its “Trends” utility to assist advertisers in gaining a more comprehensive understanding of and predicting the following items that users intend to purchase. The updated tool will capitalize on users’ preferences regarding saving, curating, and purchasing.
