Crimson Hexagon Unveils First Image Analysis Beyond Logo Identification for Deepest Consumer Insight through Social Data
Crimson Hexagon , a leading provider of consumer insights from social data to inform strategic enterprise decision-making, today released its proprietary image analysis capabilities, developed in-house, to help brands and agencies unlock insights within photo data. By applying Crimson Hexagon’s analytics engine to images to recognize scenes, objects, actions, faces and logos, brands learn who, how and where consumers engage with their products. Far beyond what they can achieve with simple logo identification, brands can analyze images to tailor marketing campaigns, drive product enhancements, identify influencers and more.
Social media users share more than 3 billion images each day. When brands rely solely on textual analysis, they miss out on the full context of consumer social conversations, especially since 85 percent of images on social media lack any text reference to the brands pictured in them. As Gartner analysts Nick Ingelbrecht and Melissa Davis wrote, “The growth of all types of video/image content is driving demand for improved indexing, content analysis and search capabilities. Internet traffic activity and growth forecasts show a relentless increase in image and video content, with cameras of all types capturing and sending ever-larger volumes of high-definition video.1 ”
Crimson Hexagon’s software ingests and stores the most comprehensive image database in the market with more than 125 million images a day to train and enhance the accuracy of its machine-learning image analysis algorithm. Access to the most data together with the most advanced image analysis technologies enables Crimson Hexagon clients to analyze the top objects and scenes that appear in photos for particular conversations, as well as the evolution of image-based elements over time.
“Whatever the topic, the language around it is increasingly visual. Before Crimson Hexagon’s image analytics capabilities, we were missing the full picture around what matters, and to whom. Our campaigns, and the causes they support, are the better because of it," said Zach Zimmel, director of strategy at Grassriots.
From calculating the return on sponsorships to spotting alternative product uses to finding affinities between people, objects and scenes, Crimson Hexagon’s image analysis capabilities solve business problems across organizations. Features include image-specific filtering, data visualizations on posts containing images and a multimedia tile view display of analyzed posts.
“The future of content is visual, and brands that rely on logo recognition alone are missing an unwritten part of the conversation: the who, how and where of consumers’ engagement with their products,” said Errol Apostolopoulos, senior vice president of product at Crimson Hexagon. “As consumers, especially millennials, continue to create visual content, our system’s machine-learning-based algorithm is well-equipped to ingest, store and classify those images and videos for our clients, so they can get the clearest insights about their customers.”
Schedule a demo of Crimson Hexagon’s image analysis solution:
- Blog: http://www.crimsonhexagon.com/blog
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- Demo: http://pages.crimsonhexagon.com/image-analytics-demo.html
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- Tumblr: http://www.crimsonhexagon.tumblr.com/
About Crimson Hexagon
Crimson Hexagon is the global leader in consumer insights from social media data. Powered by patented technology and an in-house data library of more than 1 trillion posts, Crimson Hexagon's platform helps hundreds of brands and agencies answer critical business questions through the insights derived from social data. Clients include leading global organizations such as General Mills, Starbucks, Paramount Pictures, Anheuser-Busch InBev, Adidas and Twitter, and leading agencies such as TBWA, VML, BBDO, Saatchi & Saatchi, Ogilvy, Edelman and Digitas. Find us on Twitter and on Tumblr.
1 Gartner “Innovation Insight for Video/Image Analytics, 2016,” Nick Ingelbrecht and Melissa Davis, Sept. 22, 2016
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