Bid forecasting in Real-Time Bidding (RTB) is a predictive process that aims to estimate the probabilistic distribution density with respect to the market price given an ad auction information. This information is typically represented by a high-dimensional feature vector.
The goal of bid forecasting is to provide advertisers with insights into the potential outcomes of their bids, helping them make more informed decisions about their bidding strategies. It can help predict the likelihood of winning an auction at various bid prices, which can be crucial for optimizing ad spend and maximizing return on investment.
It’s important to note that bid forecasting is a complex process that involves analyzing historical data, understanding market trends, and applying sophisticated machine learning algorithms. It’s a key component of programmatic advertising and plays a vital role in the RTB ecosystem.