The ad & marketing tech industry requires stream processing capabilities that can handle enormous volumes of real-time data from various sources such as websites, mobile apps, social media platforms, and ad exchanges. The system must provide real-time audience segmentation, bid management for programmatic advertising, content personalization, and seamless integration with demand-side platforms (DSPs), data management platforms (DMPs), and customer data platforms (CDPs).
Implementing real-time data processing in ad & marketing tech faces several technical hurdles. These include processing ultra-high-velocity data streams from millions of user interactions and ad impressions, ensuring sub-millisecond latency for real-time bidding (RTB) in programmatic advertising, maintaining data accuracy and consistency across distributed systems, and scaling to handle traffic surges during major events or campaigns. The solution must also comply with stringent data privacy regulations (like GDPR and CCPA), handle complex data integrations from multiple sources, and provide robust security measures to protect sensitive user data.
Efficient data handlingRisingWave ingests and processes large volumes of high-velocity data from various sources such as messaging platforms and databases in real-time.
Broad connectivity It offers robust connectors for popular data systems, enabling easy data input and output.
Wide compatibility As a Postgres-compatible database, RisingWave works with many analytics tools through standard Postgres drivers.
Low latency RisingWave delivers results in milliseconds, using real-time materialized views that update continuously.
Complex transformations It efficiently performs operations like filtering, joins, and aggregates across multiple data sources.
Easy metric creation New metrics can be set up with just one or two SQL queries.
Data consistency RisingWave ensures all queries access the same version of data, guaranteeing correct and consistent results.
Simple scaling You can add new nodes as needed without system downtime.
Real-time bidding (RTB) Enabling instant auction and bidding for ad impressions in programmatic advertising.
Dynamic creative optimization (DCO) Personalizing ad content in real-time based on user data and context.
Cross-channel attribution Analyzing the impact of marketing touchpoints across various channels in real-time.
Audience segmentation Dynamically categorizing users into targetable segments based on real-time behavior and characteristics.
Fraud detection Monitoring betting activities to identify suspicious patterns and prevent fraudulent bets.
Campaign optimization Continuously adjusting campaign parameters based on real-time performance metrics.
Customer journey mapping Tracking and analyzing user interactions across touchpoints in real-time to optimize the customer experience.
Personalized content delivery Serving tailored content or offers based on real-time user behavior and preferences.
Lookalike modeling Instantly identifying and targeting users similar to high-value customers based on real-time data.
A/B testing Conducting and analyzing live experiments on ad creatives, landing pages, and marketing messages to optimize performance.
Predictive analytics Using real-time data to forecast user behavior, ad performance, and market trends.
Multi-touch attribution Assigning credit to marketing touchpoints in real-time for accurate performance measurement.
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