Storyblocks Harnesses AI to Surface Fresher, More Relevant Content

Stock media leader answers customer demand with AI-driven innovations to improve creative workflows

Storyblocks, an unlimited, subscription-based stock media platform with video creation and workflow functionality, has unveiled new search enhancements powered by AI. These improvements aim to deliver an elevated user experience and streamlined creative workflows for Storyblocks’ customers.

  • Learn more about Storyblocks’ AI-enhanced search experience at

In the recently released 10th Annual Survey of Creative Pros, Leslie Hughes, founder of iSPY Technologies and president of the Digital Media Licensing Association, said, “This year’s survey confirmed what creators truly value when licensing stock media – high content quality and relevance. However, finding the perfect assets through search remains their biggest hurdle. Encouragingly, many creators are optimistic that AI can lend a hand in streamlining asset discovery going forward.”

“Our team has relied on Storyblocks for several years now to create video content at a rapid pace,” said Nolan Nichols, manager of video production at the U.S. Travel Association. “We’re excited that Storyblocks is leveraging AI more to help customers like us find the content we need even quicker than before. We’re a lean team and are always looking for ways to work smarter, faster, and more efficiently, so I’ve been actively looking for ways that AI can help us do that at every step of the creative process.”

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Cutting-edge data, AI and machine learning technologies drive Storyblocks’ platform. The company uses advanced AI models to deliver the most relevant content to its users. However, Storyblocks is not just about technological prowess; it is equally committed to curating a diverse and representative library that meets changing customer demands.

Recent improvements include:

  • Delivering faster, more relevant and more representative results in search queries
    • Storyblocks prioritizes fresher content in its search results through a proprietary algorithm that evaluates the performance of new content every four hours. Early testing indicates that including recently uploaded content can boost download rates by up to 60% compared to searches without this prioritization.
    • Storyblocks employs an in-house machine learning model based on the BERT framework, allowing the platform to rapidly analyze how users engage with content and refine search result rankings in near real-time.
    • Storyblocks aims to provide representative search results. On average, 24% of videos on the first page feature Black, Indigenous, or People of Color (BIPOC) models. This aligns with the company’s goal of proactively surfacing the quarter of its library content featuring models from underrepresented backgrounds.
    • Furthermore, Storyblocks stands out in the stock media industry by routinely pulling underperforming assets to maintain a top-tier library quality. Despite expanding its collection by 40% in 2023, the company prioritized removing nearly 200,000 assets, ensuring customers can discover relevant content more efficiently.
  • Identifying compelling thumbnails for video content 
    • First impressions are critical in a medium like video, particularly for content creators juggling multiple projects. This reality prompted Storyblocks to use AI technology to identify the most pertinent thumbnail in video search results. Recent Storyblocks A/B testing revealed that videos showcasing AI-curated thumbnails experienced heightened engagement levels, suggesting these visuals better aligned with users’ interests.
  • Providing insightful and accurate content suggestions 
    • Storyblocks employs OpenAI’s large language model to enhance search capabilities, delivering comprehensive results that transcend users’ initial queries. This innovative approach aims to return relevant content even for specific or flawed search parameters. In addition, by harnessing the power of metadata enhancements and Storyblocks’ computer vision technology, the company can aggregate pertinent search results, recommend alternative scenes and surface additional clips featuring specific individuals.
  • Making cross-asset recommendations 
    • Since 2022, Storyblocks has leveraged user behavior data to suggest complementary pairings between different types of creative assets, such as videos, images and audio tracks. Through its computer vision technology, the platform can analyze music tracks by rendering songs as spectrograms in order to identify and recommend tracks that are significantly similar.

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Today’s announcement of Storyblocks’ search enhancements complements its ongoing commitment to collaborating with artists on new collections and commissioning content to address emerging gaps identified through search data analysis. These improvements not only facilitate the discovery of Storyblocks’ ever-expanding library but also increase the likelihood of users downloading both existing and newly added content.

“At Storyblocks, we’re harnessing the power of AI to revolutionize the way creators discover and use content,” said Lucy Huang, senior vice president of product and engineering at Storyblocks. “By delivering faster, more relevant and more representative search results, we’re not just streamlining creative workflows – we’re empowering our global community of artists and customers to create inclusive and impactful work. Our commitment to curating a diverse and top-quality library, combined with cutting-edge technology, sets us apart in the stock media industry.”

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