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 marketer’s 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.