Wojciech Polak

RTB House – a tech company specializing in sophisticated retargeting scenarios and operating worldwide – has appointed two new Country Managers in Western Europe. The move is expected to strengthen its position in Spain, Portugal and Benelux as a leading retargeting service provider. As Country Managers, Monica Ibarbia will coordinate operations in Spain and Portugal, while Cyril Westerhof manages activities in Benelux (Belgium, the Netherlands, and Luxembourg).

RTB House, a global company providing state-of-the-art retargeting technology, introduces new features to recommendations for targeted ads. The solution leverages deep learning (currently the most promising subfield of artificial intelligence-oriented research), in display advertising to achieve more accurate product recommendations, making personalized retargeting up to 50% more efficient.

RTB House, a global company providing state-of-the-art retargeting technology for leading advertisers worldwide, is unveiling new market presence in the Asia-Pacific (APAC) region as it enters Australia and New Zealand. This market sector will be led by Steve McMahon, joining RTB House as Country Director.

Users are more likely to click on banner ads and buy a promoted product on weekdays, with the highest conversions on Tuesdays and Wednesdays. The results come from an aggregated data analysis of campaigns carried out by RTB House, a global company providing state-of-the-art retargeting technology, across more than 40 markets. The largest sales peaks were seen between 2-4 PM and 8-11 PM.

RTB House, a global company providing state-of-the-art retargeting technology for top advertisers worldwide, adds India to an ever-growing presence in Asia-Pacific (APAC) markets. Country Manager Kshitiz Randhir Shori will lead regional operations.

RTB House, a global company providing state-of-the-art retargeting technology for top advertisers worldwide, presents a new upgrade to its recommendation mechanism using a combination of deep learning and computer vision. The new method enables ultra-precise predictions of possible user’s buying needs, leading to product recommendations up to 41% more efficient than previously.