StackAdapt Launches Forecasting

StackAdapt, a programmatic advertising company, today  launched Forecasting as part of its StackAdapt Planner. Forecasting helps media buyers plan and execute campaigns.

Forecasting allows advertisers to see the estimated audience size, unique users, and daily impressions they could reach with their allotted budgets by inputting the target geography, audience demographics, and inventory. They can then see the cost-per-thousand and estimated number of unique users that the campaign can generate based on the parameters.

Built on artificial intelligence, Forecasting leverages programmatic tech to provide data-driven insights to anticipate campaign performance prior to launch, identify potential drop-offs in audience, and recommend adjustments that will improve results.

"Our clients wanted a planning feature that provided more insight into their campaigns' spending potential and scalability as well as helped them identify and reach the right audience in their target demographic. Enter Forecasting in StackAdapt. With this new tool, we provide deep insights into your campaign before you even spend a dime," said Vijay Sridharan, director of product at StackAdapt, in a statement.

"Forecasting in StackAdapt is the answer to a programmatic predicament we all have: how can I predict campaign performance? I absolutely love that it takes campaign goals into account in the final forecast because I know the platform actually considers my campaigns' nuances. The feature is very straight orward, easy to navigate, and helps to clearly identify what parameters might restrict campaign performance and scale before launch, which is a huge benefit," said Cash Meyerhoffer, associate director of digital media at ThomasARTS, in a statement.

Related Articles

StackAdapt Expands into Outdoor Advertising

StackAdapt is offering digital out-of-home advertising through partner Vistar Media.

StackAdapt Integrates with Oracle Moat

StackAdapt's Oracle Moat integration allows retail and CPG companies to access real-time attribution and measurement metrics