What is it
The Ad Forecaster is the next-generation forecasting engine for online advertising campaigns. It overcomes various
important limitations of existing forecast engines in ad servers, allowing you to accurately predict future ad
impressions traffic levels and campaign inventory availability using an unlimited number of targeting variables,
including geo, keywords, key-values, cookies and multiple frequency capping groups at banner, booking, line item or
campaign level.
It is operated as a Software-as-a-service, minimising integration and deployment times as well as operational
maintenance costs.
Custom-built Ad Servers and Exchanges, Sell-side platforms (SSPs) and Demand-side platforms (DSPs) are the most
common type of platforms that can take advantage of the Ad Forecaster.
The importance of ad forecasting
- The highest yielding campaigns typically require a volume guarantee.
- Agencies and Advertisers rely on commitment to deliver their budgets and goals.
- Inventory owners depend on their forecast to commit to delivering campaign volumes.
- An unreliable forecast means inventory goes unsold unnecessarily.
- Overselling and under-delivering ensures budgets will go somewhere else.
For Publishers
Premium publishers and networks are the first to suffer from unreliable forecasting as soon as they start overlaying data with their inventory, which they are compelled to do in order to increase the value of their inventory.
For Exchanges, SSPs and DSPs
The “automated channels” are already data-driven but have been focused on RTB and performance. In order to grow their service offering with guaranteed campaign delivery they require accurate and scalable forecasting engines.
For Ad Servers
Ad Server providers require a forecasting engine capable of using all the data their clients are throwing at it, or risk being replaced by another provider who does.
Why a specialised tool is a good idea
The growth of data available for campaign targeting is making traditional forecasting methods obsolete,
as spreadsheets or even standard ad server forecasting tools are no longer able to produce reliable forecasts.
The main reason is their approach: looking at aggregated counts by site, channel, packages and a limited set of
variables, instead of individual users and ad requests.
The more data overlaps, e.g. Channel News and Male Demographics, the more inaccurate these approaches become,
compounded by the increased used of 3rd-party data targeting, frequency capping and booking complexity.