Digital marketing channels provide great opportunities for personalized, real-time interactions with customers. These opportunities also pose a great challenge from an efficiency standpoint because marketing systems must make an extremely high number of dynamic and personalized decisions. To optimize such micro-decisions, one has to account for various signals and use advanced statistical analysis to learn patterns from historical and ongoing data.
In this talk, we will discuss automatic decision-making and AI techniques for promotion campaigns. First, we will present a methodology to develop highly automated promotion management systems. Next, we will walk through practical examples of how advanced customer and content signals can be generated using predictive models and then be used in automation of targeting, budgeting, and pricing decisions.
This talk is for Data Scientists, Product Owners, and Software Engineers involved in marketing operations or the development of marketing automation software, as well as those interested in ML-based decision automation techniques.
By watching this video, you will gain insight into:
- A methodology for AI adoption in marketing technology applications
- The architecture of software systems that can autonomously optimize and execute promotion campaigns
- Data engineering for the generation of advanced customer and content signals that help to make smarter targeting decisions
- Optimization of targeting decisions for customer acquisition, growth, and retention
- Static and dynamic optimization of budgeting decisions
- Optimization of pricing decisions and promotion parameters
#DigitalMarketing #DataScience #AI #ODSC
