Dataseat provides a privacy-ready mobile demand-side platform (DSP) that enables advertisers to manage user acquisition campaigns on iOS and Android without relying on IDFA. By utilizing custom bidding algorithms and full support for AdAttributionKit and SKAdNetwork, Dataseat enhances campaign performance while ensuring compliance with Apple’s privacy measures.
Funding
$2.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
The increasing emphasis on user privacy limits the effectiveness of traditional mobile advertising methods that rely on device identifiers like IDFA, making it difficult for advertisers to effectively target and acquire users on iOS and Android platforms. This shift requires new approaches to user acquisition that respect user privacy while still delivering strong campaign performance.
Solution
Dataseat offers a privacy-focused mobile demand-side platform (DSP) that enables advertisers to manage user acquisition campaigns in a privacy-centric environment. The platform leverages custom bidding algorithms and provides full support for Apple's AdAttributionKit (AAK) and SKAdNetwork (SKAN), allowing for effective campaign management without relying on IDFA. Dataseat's technology helps brands, apps, and games achieve programmatic success by utilizing privacy-compliant signals and contextual targeting to acquire high-value users. The platform provides full visibility of programmatic data, enabling advertisers to train their own machine learning models and maintain control over their data and bidding logic.
Target Audience
Dataseat primarily serves performance brands, agencies, and app developers in verticals such as gaming, entertainment, finance, retail, and travel, who are looking to drive user acquisition and re-engagement in a privacy-focused manner.
Features
- Full support for AdAttributionKit (AAK) and SKAdNetwork (SKAN) for privacy-first advertising
- Custom bidding algorithms powered by privacy-compliant signals
- Contextual targeting capabilities using app genre and subgenre classifications
- Retargeting solutions leveraging first-party data for audience segmentation and customization
- Machine-learning models to optimize campaign performance based on specific goals
- Real-time insights into traffic sources to identify high-value users
- Integration with major in-app exchanges for broad reach