There is more content being created an shared on a daily basis than any human team, no matter how robust, could possibly organize and manage manually. 95 million photos and videos are shared on Instagram per day. 300 hours of video are uploaded to YouTube every minute. I can't even manage all the photos I have on my phone very well - how is any business supposed to effectively manage not only the content they produce in-house but also all the user-generated content (UGC) being created and shared by consumers?
The answer is in artificial intelligence, specifically image recognition. This form of AI is being used by large social platforms to retailers in order to make managing the immense amount of visual content possible. In this post, I'll share 3 examples of how companies have implemented an AI strategy to optimize their use of visual content
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1. Staples Removes the Language Barrier
Staples Europe is the leading provider of workplace products, services, and solutions to small, mid-sized, and large businesses in Europe. Staples Europe has operations across 17 countries in Europe and provides solutions across 29 European countries – each of which has its own eCommerce website.
The company relies on SEO to surface relevant products to potential customers and stay ahead of the competition. However, with Staples Europe spanning countries that speak twelve different languages, attaching the right keyword metadata to products to improve SEO proved to not only be time-consuming but also expensive.
Staples used Clarifai’s multi-language feature, which recognizes over 11,000 different concepts in images in over twenty languages, to append the ALT tags of over 600 products to boost SEO – saving five figures worth in agency costs in the process.
2. Foap Improves Tagging Consistency
Foap is a fast-growing photograpy marketplace that receives thousands of new user-uploaded photos every day. To connect brands with the images they’re looking for, Foap had to find a way to tag all these photos and make them easily searchable consistently.
Because most of Foap’s photos come from individual photographers, the tags and metadata attached are often inconsistent. For example, an image of a dog might be tagged “dog,” or it might be tagged by the specific breed. They needed a solution that could “see” each image and apply the appropriate tags accurately and consistently.
Foap used Clarifai’s computer vision solution to scale its marketplace and improve the user experience for both buyers and sellers. When a user uploads an image to Foap, the app automatically suggests relevant tags for every image using the Clarifai API. Users still have the option to add their tags as well. That way, Foap ensures consistency across user-generated content from different creators but also allows for creativity and flexibility in the tags.
Clarifai’s tags are also baked into the Foap app’s search so that brands and photographers can find precisely what they’re looking for. Now, not only is it easier for photographers to manage their portfolios and make their offerings more attractive, it’s also easier to surface the right content to buyers so they make more purchases.
3. ButterCam Improves the User Experience
ButterCam is an app that enables users to edit their still photos with text and graphics. In the three years since ButterCam launch, the app now has 33 million users!
With the photo and video app space has growing significantly in China, the company identified an opportunity to build a single-step picture processing technique using computer vision in order to improve the user experience within the app. ButterCam already had a large volume of text templates and photo filters, so they wanted a way to simplify the steps it takes users to turn an ordinary photo into something beautiful.
The team chose Clarifai to build its single-step picture processing technique. Using Clarifai’s Organize & Curate solution to label photos, enabled on user devices by the Clarifai Mobile SDK, ButterCam automatically makes edit suggestions to users based on the image contents. With its vast catalog of text and filter templates, users no longer have to choose the best fit for their image. Instead, ButterCam does the work for them: adding the most appropriate filters, text, and stickers.
These are just a few examples of how image recognition is being put to use by brands. Unsure if your company needs to implement an AI strategy? Get the checklist below!