Agreement Integrates VideoAmp’s Proprietary User Graph and Cross Screen DSP with Grapeshot’s Live Audience Pre-Bid Keyword-Driven Targeting Solution
SANTA MONICA, CA – VideoAmp, The Total Video platform for the TV and Video ecosystem, and Grapeshot, the technology company that deploys machine learning to unlock value from data, announced they have integrated Grapeshot’s Live Audience pre-bid keyword targeting solution with VideoAmp’s proprietary user graph. Under the terms of the partnership, programmatic buyers can find live audience segments across desktop, mobile, and TV, with the ability to leverage custom audience definitions and social media trends all at scale with brand safety protection.
“At VideoAmp, we seek partners who bring immediate value to our clients. We are excited by Grapeshot’s proven ability to deliver increased conversion with the scale required to support our client’s broad audience reach needs,” said Nick Chakalos, EVP Global Business Development, VideoAmp.
VideoAmp unites traditional TV planning with digital data and supports traditional and advanced measurement currencies. Their user graph, which covers more than 170M individuals, makes it simple for media buyers to optimize TV and digital campaigns at scale by leveraging precise targeting across screens in a single platform. VideoAmp’s platform connects households and devices to viewing behavior enabling advertisers to plan, buy, optimize, and measure the success of de-duplicated and precisely targeted campaigns that reach broadcast TV, VOD, OTT, desktop, and mobile audiences.
Grapeshot uses adaptive machine learning algorithms to organize large amounts of data into useful, shareable actions. This partnership will power pre-bid targeting on VideoAmp’s DSP, with Grapeshot signal analyzing pages and giving segment level responses on mobile and desktop inventory. This gives VideoAmp the ability to execute qualified reach and scale cross platform. Additionally, the cross device signal from Grapeshot will power digital consumption insights for cross device users.
“Grapeshot is excited to align ourselves with VideoAmp’s innovative approach to data activation. In addition to offering Grapeshot’s full suite of pre-bid targeting solutions, VideoAmp will incorporate Grapeshot analysis of digital content consumption to help power their proprietary device graph. Understanding content consumption patterns across devices will give VideoAmp a unique approach to data-driven TV buying,” said Ryan McBride, VP, Platform Partnerships, Grapeshot.
VideoAmp is the world’s first Total Video Platform to enable advertisers and media owners to transact seamlessly across devices. Our software and data solution enables advertisers to plan, buy, and measure the success of de-duplicated and precisely targeted campaigns that reach broadcast TV, VOD, OTT, desktop, and mobile audiences. Founded in 2014, VideoAmp is headquartered in Los Angeles, with offices in New York, San Francisco, Chicago, and the Netherlands. VideoAmp is backed by European TV giant RTL Group and six other top venture capital firms. For more information, visit www.videoamp.com or follow us on Twitter, Facebook, and LinkedIn.
Grapeshot is a global privately-owned technology company that deploys machine learning to unlock value from data. Grapeshot uses a page crawling algorithm, to profile data on behalf of marketers and developers, as well as agencies and publishers. Grapeshot’s core WordRank™ technology offers a fully customizable, transparent and scalable solution, giving clients simple, integrated control. Grapeshot is integrated with all major programmatic trading marketplaces including AppNexus, MediaMath, Turn, The Trade Desk, AdForm, iPinYou and AOL. The core technology is also available through an API. Grapeshot operates at scale, processing large amounts of data efficiently. Grapeshot receives requests for 7T classifications per month, 3.5m QPS, recognizing 100+ languages and deploying segments in 33. Grapeshot has offices in Cambridge, London, New York, Chicago, San Francisco, Singapore and Sydney.