• The Power Of Earned Media In Social Images

    12.04.2015 News

    Brands are spending large amounts of money on sponsorships, in particular in sports, which are seen as a unique way of engaging emotionally with fans. Ideally the brand will be featured prominently in an image of a star player scoring a key goal for the home side and reap the benefits of being connected to a moment of collective glory. Anecdotally brands get “a lot” of exposure for their sponsorships of teams and athletes via images shared on social media, but up till now, no one has been able to quantify this valuable audience.
    Luckily for brands, the convergence of existing computer vision technology and the recent advances in machine learning are changing the game. Large-scale analysis of social media images to identify brand logos and gather useful information about audience and engagement is now emerging as a credible approach to earned media measurement, especially for sport sponsorship. It is now possible to look inside the image to detect faces, objects and brand logos at a scale, speed and accuracy that was impossible a few years ago. These new approaches reveal huge audiences and high levels of engagement that were previously invisible.
    The new services available from companies like Kuznech, combined with inexpensive cloud computing puts brand-spotting within reach for brand managers. Kuznech can do brand, logo, face recognition on images, as well as on videos.
    Widespread adoption of these new technologies will change the way earned media is measured. Brands will have new ways to measure the ROI of their sponsorship dollars and engage directly with the audience that is already emotionally connected to their brand. Brands, agencies, teams and events that grasp these tools now will lead in the future.

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  • Kuznech Mobile Recognition Debut: Parts Town Launches App Upgrade With PartsMATCH™

    02.04.2015 News

    Parts Town, a market leader in restaurant equipment parts distribution, launched their latest innovation: the entirely redone Parts Town app with revolutionary PartsMATCH parts identification technology and a dramatically improved in-app shopping experience.




    PartsMATCH 1.0 utilizes cutting edge image recognition algorithms to compare customer-submitted pictures of a part against hundreds of thousands of PartSPIN images to find a match. While the technology is in its infancy and still evolving, Parts Town is committed to pushing the envelope with unique customer solutions.
    The image recognition engine was developed by Kuznech Inc, a company that creates object recognition technologies for m-commerce. “Image recognition is being used in fields like national security, social networking, and retail. As we’ve done with other industry innovations such as PartSPIN, we applied an external technology to solve a parts-related problem”, said Mike O’Shea, Parts Town’s Director of Ecommerce. “This feature, developed by Kuznech, reinforces our commitment to drive the industry forward, and we will continue to refine and improve it over the coming months”.
    PartsMATCH Assistant applies a human touch to the same parts identification challenge. Customers can submit parts identification requests right from the app, including pictures of the part, then receive push notifications direct to their device as soon as a PartsMATCH specialist has located their matching part. “At Parts Town we are committed to helping each of our customers find the right OEM part for their equipment. Pictures are often extremely helpful in the parts identification process, and PartsMATCH Assistant combines great technology and great people to get answers to customers faster than ever before”, said Steve Snower, President of Parts Town.
    Significant shopping and speed improvements were also incorporated into the new app. “Technicians and operators need access to parts technology on the go now more than ever, and the all-new Parts Town app is an indispensable tool for our increasingly mobile customers”, added Snower. Initially on iOS only, an Android version will be available soon.

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