So far, Pinterest can boast nuanced usage for specific human interests such as cooking and fashion. Twitter has become known for real-time news, while Facebook’s 2 billion monthly active user count dwarfs Pinterest’s 200 million total.Ĭlearly, the pressure is on Pinterest to establish unique ways to stand out. The rise of image search has become a strategic advantage for Pinterest, as it competes with Twitter, Facebook and Instagram for the attention of social media users. Differentiating Pinterest Through Image Search Images are shared for recommendations, so having a recommendation engine that interprets context well will be especially critical, both for image search and for software that often works alongside image sharing, such as a chatbots or apps. The refinement of image search plays into machine learning development as well. That means that dedicated image engines have become a new Holy Grail, with Pinterest and Google leading development efforts. Developing a Dedicated Image Search Engine Activities like these have unwittingly increased the number of images placed online - so much so that just by sheer volume, images have become part of the big data discussion.Īnd because pictures are increasingly being taken of products, services and micro-moments, search engines and recommendation algorithms can now take these images and correlate them to queries and requests. People are using their smartphones to create selfies and share fashions they discover. One nuance being explored more deeply these days is image search.
But as our interfaces have changed and our options for media have broadened, our needs for search capabilities have also become more nuanced. Marketers and consumers have long turned to search engines for convenience.
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