Our online and offline sales data were showing if a consumer bought a ticket just few days before the flight, the average basket value was higher. Further, thanks to social listening, we also knew that users might have a negative perception towards a brand when they see an ad that becomes irrelevant to them after a certain time. So, we knew that if we could have target users who were searching for a flight within few days we would increase our average transaction value and total revenue. In addition, by not showing an ad for a flight that a consumer was no longer interested in, we would save our marketing budget. By increasing revenue and decreasing budget, we would increase the ROI. In order do such targeting we’ve needed a reporting system that dynamically update user segments according to time between a flight search and the demanded departure date. Yet, there was no such reporting so we’ve developed our own. We’ve created many segments according to days to travel and 140 destinations. We’ve tailored both our search and display ads accordingly and adjusted our bidding strategies for these segments. We’ve achieved 3.5x higher ROI, 64% higher conversion rates and 58% CPA.