Traditional online display advertising is inefficient. Real-time bidding refers to the buying and selling of online ad impressions through real-time auctions that occur in the time it takes a webpage to load. With Real-Time Bidding, advertising inventory is bought and sold on a per-impression basis, via programmatic instantaneous auction, similar to financial markets. The targeting and cost efficiency opportunities presented by RTB are making it a revolutionary force in the online advertising landscape. In the same way that search engines use keywords, RTB uses behavioral and demographic data to target ads at specific audiences, producing results like never before.
Campaign automation schedule changes to optimize results, such as increasing or decreasing max cost per click based on real time conditions. Bidding Rules' purpose are to analytically optimize the programmatic buying of ad-inventory. Bidding rule algorythms help make buying and selling decisions in finite steps using the available data at the moment. Its major role is to help carry out the automation of data-driven decision making, which is one of the most challenging yet exciting problems for data scientists. Bidding rules can be based on Site, Placement, Geo-Target, Day Part, Frequency Cap, Audience-Target, etc, constantly improving with machine learning.
To reap the benefits from programmatic, advertisers have to allocate advertising budgets effectively to maximize profitability. AdTech Hub offers advertisers more control through frequency capping across inventory sources and the ability to optimize budgets across campaigns. Predictive modeling and simulations further improves results through smarter budget allocation and bidding across campaigns and networks.
Cross-device tracking consists of identifying Internet users across networks, smartphones, tablets and desktop computers.