- Analytics & Modeling - Real Time Analytics
- Robots - Wheeled Robots
- Sales & Marketing
- Real-Time Location System (RTLS)
- Track & Trace of Assets
Yieldmo, a mobile-advertising marketplace, was facing a challenge in enhancing its measurement of user interactions for its ad campaigns. The company needed to capture user behavior in real time, across each ad pixel for billions of ad impressions at millisecond granularity. This was crucial for their sessionization process, which involved the collection of user interactions, known as micro-interactions, performed on Yieldmo’s ad units within a user session. The company was also planning to launch a new data platform that would provide in-depth insights into customer engagements. However, capturing hundreds of billions of micro-interactions presented a technical challenge as it would increase the number of requests coming in and require adding many more proxy servers to capture and analyze all these events. Implementing a traditional solution would be time-consuming, expensive, and require a large amount of storage and compute power.
About The Customer
Yieldmo is a mobile-advertising marketplace that delivers high-performance ad campaigns, serving billions of ad impressions to millions of unique mobile visitors each month. The company is user-centered, design-driven, and data-powered, redefining digital advertising. Yieldmo's products help marketers and publishers build deeper engagements with their customers. The company was planning to launch a new data platform that would provide in-depth insights into customer engagements, making campaigns more effective for advertisers, more profitable for publishers, and ultimately, more relevant for consumers.
Yieldmo chose Amazon Kinesis services to capture, process, and deliver its data in real time. The company's ad units on customers’ mobile web pages sent data directly to Amazon Kinesis Data Streams, which efficiently and durably captured the real-time streaming data at scale. To process the data in streams, Yieldmo employed Amazon Managed Service for Apache Flink to consolidate millisecond user interactions and define an active user session. The company used standard SQL code to compute pixel-by-pixel ad-view time and ad-view percentages, and to track how many pixels were on screen for how many seconds. Yieldmo also used Amazon Kinesis Data Firehose to deliver this data to Amazon Simple Storage Service (Amazon S3) buckets. AWS Lambda was used for final formulation of user-level engagement analytics and then to load the company’s data warehouse, where data could be served to customers.
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