RTB House Unveils Deep Learning Backed Digital Marketing Technology for Brands Globally

November 17, 2017 12:11 PM AEDT | By NewsVoir
 RTB House Unveils Deep Learning Backed Digital Marketing Technology for Brands Globally
Image source: Kalkine Media
  • New technology to drive 100% of RTB House Campaigns & allows for ultra precise estimation for CTR

  • This is the first of its kind technology in the nascent Indian digital advertising market

RTB House, a global company providing state-of-the-art retargeting technology for top advertisers worldwide, has recently implemented new algorithms for ultra-precise estimation of CTR. The new technology allows for better prediction of potential clicks on ads, which ultimately yields better ROI for customers. This development makes RTB House one of the first retargeters so extensively using deep learning - the most promising subfield of AI research.

Increasing click-through rates (CTRs) effortlessly is every digital marketers dream. CTRs, or the ratio of clicks on a banner against the total number of impressions, is one of the most common metrics of a successful advertising campaign. By using technology that can predict users behaviors based on previous activities and recommend the best product offer for them, brands can increase CTR metrics and reaching their most valuable potential customers with the same budgets than previously allocated.

By using deep learning technology, processing models inspired by the biological neurons in our brains, RTB House makes it possible to get more reliable, richer, machine-interpretable user profiling of customer's buying potential, without any human expertise.

Recently implemented algorithm allows to predict user clicks on ads more accurately, boosting the total number of clicks by 16.5% within the same budget limitations.

CTR estimation marks is the fourth major implementation of deep learning methods at RTB House. Due to the cutting edge approach, conversion rate and conversion value algorithms are able to increase overall performance from retargeting activities up to 29%. Moreover, deep learning-based recommendations, increase product selection efficiency by up to 41%, compared to campaigns that did not utilize the same methods.

Bartłomiej Romański, Chief Technology Officer RTB House, emphasizes that the changes in the company's algorithms makes its retargeting technology supported by deep learning on every level of advertising process. "We've been working on these innovations for a year and a half, gradually extending upgrades to our solution. It has brought us to the point where we can say that 100% of our algorithms are based on deep learning components, bringing advertisers globally a new wave of efficiency to their online activities. We're taking a note from other industries, like travel, where a long list of metrics are taken into consideration and user purchasing patterns are dynamic and difficult to predict. In such cases, algorithms powered by deep learning can better react to user needs. It's a vast improvement over other methods typically used in retargeting." Romański summarizes.

RTB House is one of few companies in the world that managed to develop and implement its own technology for purchasing advertisements in the RTB model, or real-time bidding - a solution in which buyers participate in real-time advertising space auctions. In India especially where digital advertising spends remain low at only 14% of the total advertising spend, RTB House sees a great opportunity with advertisers and brands for its technology. The company operates worldwide and runs more than 1,000 unique campaigns for global brands in more than 40 markets across Europe, Latin America, Asia and Pacific, Middle East and Africa.

The company's findings in the field of artificial intelligence were lately presented during the 2017 International Joint Conference on Neural Networks in Anchorage, the 33rd International Conference on Machine Learning (ICML 2016) in New York City and the 31st AAAI Conference on Artificial Intelligence (AAAI 2017) in San Francisco.

Notes to editors

RTB House is a global company that provides state-of-the-art retargeting technology for top brands worldwide. With its proprietary ad buying engine, powered by deep learning algorithms, RTB House helps advertisers multiply sales to reach their short, mid and long-term goals.

Founded in 2012, RTB House serves over 1,000 campaigns across more than 40 markets of Europe, the Middle East, Africa, Asia, Pacific and Latin America. The team consists of over 200 professionals and growing.

Learn more at www.rtbhouse.com.


Disclaimer

The content, including but not limited to any articles, news, quotes, information, data, text, reports, ratings, opinions, images, photos, graphics, graphs, charts, animations and video (Content) is a service of Kalkine Media Pty Ltd (“Kalkine Media, we or us”), ACN 629 651 672 and is available for personal and non-commercial use only. The principal purpose of the Content is to educate and inform. The Content does not contain or imply any recommendation or opinion intended to influence your financial decisions and must not be relied upon by you as such. Some of the Content on this website may be sponsored/non-sponsored, as applicable, but is NOT a solicitation or recommendation to buy, sell or hold the stocks of the company(s) or engage in any investment activity under discussion. Kalkine Media is neither licensed nor qualified to provide investment advice through this platform. Users should make their own enquiries about any investments and Kalkine Media strongly suggests the users to seek advice from a financial adviser, stockbroker or other professional (including taxation and legal advice), as necessary.
The content published on Kalkine Media also includes feeds sourced from third-party providers. Kalkine does not assert any ownership rights over the content provided by these third-party sources. The inclusion of such feeds on the Website is for informational purposes only. Kalkine does not guarantee the accuracy, completeness, or reliability of the content obtained from third-party feeds. Furthermore, Kalkine Media shall not be held liable for any errors, omissions, or inaccuracies in the content obtained from third-party feeds, nor for any damages or losses arising from the use of such content.
Kalkine Media hereby disclaims any and all the liabilities to any user for any direct, indirect, implied, punitive, special, incidental or other consequential damages arising from any use of the Content on this website, which is provided without warranties. The views expressed in the Content by the guests, if any, are their own and do not necessarily represent the views or opinions of Kalkine Media. Some of the images/music that may be used on this website are copyrighted to their respective owner(s). Kalkine Media does not claim ownership of any of the pictures displayed/music used on this website unless stated otherwise. The images/music that may be used on this website are taken from various sources on the internet, including paid subscriptions or are believed to be in public domain. We have made reasonable efforts to accredit the source wherever it was indicated as or found to be necessary.
This disclaimer is subject to change without notice. Users are advised to review this disclaimer periodically for any updates or modifications.

AU_advertise

Advertise your brand on Kalkine Media

Sponsored Articles


Investing Ideas

Previous Next
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.