Good forecast of supply and demand is crucial for advertisement inventory management in the online advertising industry. Imagine that an advertiser is planning to purchase some inventory matching the following criteria: (age > 30) and (state = California) and (web_property = yahoo_news) from Dec 1 to Dec 31, 2010. Two questions need to be answered:
There are three challenges in answering the first question. First, inventory forecasting at web-property level is very challenging. Many factors influence the future inventory, such as seasonal effects, user growth, economic environment, etc. Second, there are dozens of targeting attributes (including age and state) and the number of possible targeting criteria is in billions. Third, the response of the forecasting system must be in real time. Each inventory query should be answered within seconds even if it has never been seen before.
To address the second question above, we need to forecast advertisement demand as well, as pricing should be a function of supply and demand. Time series analysis and booking curve analysis are possible tools for demand forecasting.
Future research includes two areas: