Marketing intelligence (MI) combines marketing and customer analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations make better data-driven decisions. Using MI, organizations can optimize their marketing and customer performance by maintaining a competitive advantage and achieving organizational goals and objectives. Building on the data and marketing analytics concepts and frameworks from the first three courses, participants in this course will focus on continuous improvement opportunities to optimize marketing and customer initiatives. This will require looking at an organization’s entire data ecosystem – internally and externally.
This elective course is recommended after taking the first three required courses in the Associate Certificate in Data and Marketing Analytics program.
Curriculum topics include:
- Marketing intelligence concepts, challenges, and considerations
- Experimentation and A/B Testing
- Conversion Rate Optimization
- Marketing attribution models
- Role and differences between artificial intelligence, machine learning, and deep learning
- Predictive and prescriptive analytics
- Governance and agile organizational practices
Upon completion of the course, participants will be able to:
- Describe the key challenges and considerations in compiling and analyzing marketing intelligence (MI) data
- Optimize marketing activities to better achieve organizational objectives
- Evaluate and improve marketing and customer performance
- Understand how artificial intelligence, machine learning, and deep learning can be applied to marketing
- Adapt to organizational change and sustain a data-driven culture
Curriculum is subject to change.