Robotics Process Automation & Intelligent Process Automation

Boost Efficiency, Unleash Data Power, and Gain a Competitive Edge


3 Days (8 hours per day)


Intermediate Level

Design and Tailor this course

As per your team needs

Edit Content

This course equips marketing analytics professionals with the knowledge and skills to automate repetitive tasks using Robotic Process Automation (RPA) and Intelligent Process Automation (IPA) technologies. By harnessing the power of automation, participants will learn to streamline workflows, improve efficiency, and gain valuable time for strategic analysis.

Course Objectives:

  • Understand the concepts and benefits of Robotic Process Automation (RPA) and Intelligent Process Automation (IPA).
  • Identify opportunities for automation within the Marketing Analytics function of a financial institution.
  • Learn the core functionalities of RPA tools commonly used in the financial industry.
  • Develop basic RPA workflows for automating repetitive marketing analytics tasks.
  • Understand how IPA integrates with RPA to enhance automation capabilities.
Edit Content

Marketing Analytics team with Data Science experience

Edit Content
  • Evolution of automation: manual processes to RPA and IPA
  • Benefits of RPA and IPA for marketing analytics teams
  • Use cases of RPA and IPA in the financial industry
  • Robotic Process Automation (RPA) definition and components
  • Attended vs. Unattended RPA
  • RPA development lifecycle
  • Benefits and limitations of RPA
  • IPA definition and core technologies (AI, Machine Learning)
  • How IPA extends RPA capabilities
  • Use cases of IPA in marketing analytics
  • Benefits and limitations of IPA
  • Overview of popular RPA tools (e.g., UiPath, Blue Prism, Automation Anywhere)
  • Key features and functionalities relevant to marketing analytics
  • Comparison of different RPA tool options
  • Techniques for process analysis and identification of repetitive tasks
  • Prioritization criteria for automation initiatives
  • Considerations for data security and compliance
  • Hands-on introduction to an RPA development platform (e.g., UiPath Studio)
  • User interface overview and navigation
  • Recording and editing basic RPA workflows
  • Design principles for building efficient and robust workflows
  • Automating data extraction and manipulation tasks (e.g., web scraping, data cleansing)
  • Integrating with marketing analytics platforms (e. g., Google Analytics)
  • Hands-on lab: Building workflows for common marketing analytics tasks
  • Testing approaches for RPA workflows
  • Best practices for deployment and managing RPA bots
  • Governance considerations for RPA in a financial institution
  • Integrating AI and Machine Learning into RPA workflows
  • Examples of using IPA in marketing analytics (e.g., customer segmentation, churn prediction)
  • Hands-on lab: Enhancing RPA workflows with basic IPA functionalities
  • Emerging trends in process automation
  • The impact of RPA and IPA on the role of marketing analysts
  • Ethical considerations for automation in marketing analytics
Edit Content
  • Solid understanding of data analysis concepts and methodologies
  • Experience working with common data analysis tools (e.g., SQL, Python)
  • Basic familiarity with marketing analytics processes in the financial industry


we'd love to have your feedback on your experience so far