A big data platform to be developed to collect, manage and analyze massive volumes of data from various advertising channels. It contains following modules: 1. Unified data repository for data storage and management; 2. Data query & presentation for performance evaluation reports and optimization strategy management; 3. Advanced data analytics using statistic/machine learning/deep learning technologies for target audience identification, fraud/anomaly detection; 4. Integration test and customer site deployment; 5. Documentation (design, API, user manual). Contract service deliverables for customer 1: 6. Data collector to get information from various advertising channels, including Google search/display network, Google video, Google shopping; 7. Software for data aggregation, consolidation and transformation; 8. Software for target audience identification; 9. Software for fraud detection.
AsiaPac Net Media Limited (Contract Service) [Sponsor]
AsiaPac Net Media Limited (Technology Licensing) [Sponsor]
Silverhorn Investment Advisors Limited [Sponsor]
As digital platforms are increasingly incorporated into marketing plans and everyday life, and as people use digital devices instead of visiting physical shops, digital marketing campaigns are becoming more prevalent and efficient. Though a lot of data has been generated by users in digital marketing, it is still quite challenging to make use of the data to identify their loyal customers and deliver a personalized communication which is highly relevant to customers' desire in order to empower the brand.
The objective of this project is to develop a big data analytics platform for digital market advertisers to manage and analyze massive volumes of data from various advertising channels, including campaign performance data, user tracking data, and other supporting data, and then harness valuable insights from the data to create a viable set of predictive stratagems.
We will also develop AI (Artificial Intelligence) powered advanced analytics tools to create “smart ads" that targets right audiences and detects advertising fraud to optimize the market campaign performance. Deep learning approaches will be applied to solve the core issues including audience segmentation and fraud placement/traffic patterns.