5 popular use cases for streaming data in AdTech

Five major ways real-time data is shaping the industry

The race to compete in online ad bidding, placement, and delivery is picking up across every digital touchpoint, from display ads to mobile and in-app experiences.

In this high-stakes AdTech environment, speed and accuracy are at a premium. If you can’t deliver precise, real-time results, your customers will seek better outcomes elsewhere. Ultimately, advertising firms must be able to gather data from multiple sources to build comprehensive online profiles while navigating complex compliance needs.

In this blog, we explore five use cases where streaming data is transforming the AdTech industry and helping businesses meet these evolving demands.

#1: Real-Time Ad Bidding (RTB)

Real-time bidding (RTB) is the process by which advertising firms and agencies bid on digital ad impressions in real time, typically in the milliseconds before an ad is displayed to a user. This system requires firms to make rapid, high-stakes decisions at a massive scale in the hopes of reaching the right audience with relevant ads.

How streaming data fits

Streaming data is essential for analyzing bid requests and user behavior on the fly. In an RTB auction, a vast amount of AdTech data, such as user demographics, location, and browsing history, must be processed instantly to determine the most appropriate ad and the optimal bid amount. By continuously analyzing data as it flows in, streaming platforms can ensure that bids are placed accurately and in real time.

Streaming data benefits

Using streaming data in RTB helps agencies target audiences more precisely, increasing their return on investment (ROI). It also allows them to refine their bidding strategies based on real-time feedback, leading to more efficient ad spend and higher engagement rates.

Streaming data example

A DSP (demand-side platform) using a streaming data platform like Redpanda can process billions of bid requests per day, analyzing user behavior in real time to dynamically adjust bids and deliver relevant ads to the right users at the right time.

#2: Personalized Ad Delivery

Personalized advertising is key to driving engagement and conversions. Consumers are more likely to interact with ads that align with their interests, preferences, and browsing behavior. To serve ads that resonate, advertising firms leverage vast amounts of user data — and do so nearly instantaneously.

How streaming data fits

Streaming data enables the real-time collection and analysis of user interactions and preferences across multiple touchpoints. By continuously processing data from user actions, such as website visits, app usage, and search queries, advertising firms can deliver highly personalized ads that cater to individual preferences.

Streaming data benefits

Real-time personalization enhances the user experience by delivering more relevant ads for consumers, resulting in higher engagement. By adapting to user behavior as it happens, businesses can also tailor their messaging in the moment, improving conversion rates.

Streaming data example

A streaming platform like Redpanda allows advertising firms to personalize ads in real time, based on live data from social media interactions or product searches. For instance, if a user browses for a new smartphone, an ad network leveraging Redpanda can serve personalized ads featuring related products, discounts, or accessories almost immediately.

#3: Fraud Detection and Prevention

Ad fraud is a significant challenge in digital advertising. Click fraud, impression fraud, and bot traffic can drain advertising budgets and skew campaign metrics. Detecting and preventing fraudulent activities in real time is critical to maintaining the integrity of the campaign.

How streaming data fits

Streaming data enables real-time detection of unusual patterns and anomalies in ad interactions, such as spikes in clicks from a single IP address or bot-like behavior. By continuously analyzing data as it flows, firms can identify and mitigate fraudulent activities as they occur.

Streaming data benefits

Real-time fraud detection reduces financial losses associated with fraudulent ad interactions and ensures the accuracy of campaign performance metrics. It also helps maintain the credibility of AdTech platforms by safeguarding them against malicious actors.

Streaming data example

Using a streaming data platform like Redpanda, an ad network can monitor click patterns and detect anomalies such as repeated clicks from the same source. The system can then flag suspicious behavior for further investigation, preventing fraudulent clicks from impacting ad spend.

#4: Audience Segmentation and Insights

In AdTech, effective audience segmentation is essential for targeting ads to the right users. Traditional static segments may become outdated quickly, leading to inefficient ad spend. Dynamic audience segmentation, powered by real-time data, ensures that ads remain relevant as audiences evolve.

How streaming data fits

Streaming data enables the real-time processing of user data, allowing for the continuous creation and updating of audience segments. Firms can dynamically adjust segments based on real-time insights, such as recent purchases, browsing history, or app activity.

Streaming data benefits

By leveraging dynamic audience segmentation, firms can target ads more accurately and in a timely manner. This improves campaign performance and allocates resources more efficiently — all thanks to streaming data.

Streaming data example

An online retailer that uses Redpanda’s streaming data platform can segment users in real time based on recent browsing behavior. For example, a user who recently searched for winter coats can immediately be added to a segment that receives ads for winter apparel.

#5: Performance Monitoring and Optimization

To maximize the effectiveness of advertising campaigns, it is crucial to monitor performance metrics and optimize campaigns in real time. This includes tracking key performance indicators (KPIs) such as click-through rates (CTR), conversion rates, and ROI.

How streaming data fits

Streaming data allows businesses to continuously analyze campaign metrics and identify trends as they happen. Advertisers can use real-time insights to make immediate adjustments to their campaigns, such as reallocating ad spend to high-performing channels or tweaking ad creative based on user engagement.

Streaming data benefits

With real-time performance monitoring, advertising firms can optimize their ad spend, improve campaign effectiveness, and ensure that marketing dollars are used efficiently. Immediate insights allow for faster decision-making, resulting in better overall campaign outcomes.

Streaming data example

An e-commerce platform using Redpanda can monitor ad performance in real time, adjusting bids or creative elements on the fly based on user interactions and engagement data. If certain ads underperform, the platform can instantly reallocate resources to higher-performing ads, improving overall ROI.

Final thoughts

Streaming data is transforming the AdTech industry, enabling advertising agencies and firms to make faster, more informed decisions that lead to better targeting, reduced fraud, enhanced personalization, and improved campaign performance. As AdTech continues to evolve, the ability to process and act on real-time data will be key to maintaining a competitive edge.

With a platform like Redpanda, businesses can harness the power of streaming data to optimize their advertising strategies, reduce costs, and drive growth. Now is the time to explore how streaming data can take your AdTech strategies to the next level.

To check out tutorials for all of the examples mentioned in this post, check out the Redpanda Blog.