PepsiCo Pulls Accessible, Actionable Insights From AI
Total Retail Talks · with Michael Cleavinger · September 13, 2022 · 19 min
Summary
This episode features Michael Cleavinger, Global Commercial Data Science Lead at PepsiCo, who shares how the multinational giant leverages AI and advanced data strategies to extract accessible and actionable insights from both customer and product data. He discusses PepsiCo's unique data collection processes, how they model data across regions using 'digital twin cities' for global insights, and advises other retailers on developing robust data strategies and continuously evaluating data quality. This is a must-listen for ecommerce operators keen on refining their data strategy and utilizing AI for impactful business decisions.
Key takeaways
Implement a robust data strategy that prioritizes both customer and product data, defining clear collection and utilization processes.
Leverage AI and machine learning to analyze data and uncover accessible and actionable insights that directly inform business decisions across departments.
Explore 'digital twin cities' or similar modeling concepts to gain global insights and understand market variations effectively.
Establish a continuous process for evaluating the quality of your data to ensure accuracy and reliability of insights.
Foster cross-departmental collaboration to ensure data science insights are shared and integrated into decision-making processes across the organization.
Themes
ai & automationanalytics & attributionfounder & leadership
In episode 366 of Total Retail Talks, Michael Cleavinger, global commercial data science lead at PepsiCo, discusses the organization's data strategy for both customer and product data, and its unique data collection process. He shares examples of how PepsiCo is leveraging data to inform decision making, as well as how his data science team shares information with other departments across the organization.
Implement a robust data strategy that prioritizes both customer and product data, defining clear collection and utilization processes.
What does this episode say about analytics & attribution?
Leverage AI and machine learning to analyze data and uncover accessible and actionable insights that directly inform business decisions across departments.
What does this episode say about founder & leadership?
Explore 'digital twin cities' or similar modeling concepts to gain global insights and understand market variations effectively.
What does this episode say about ai & automation?
Establish a continuous process for evaluating the quality of your data to ensure accuracy and reliability of insights.
What does this episode say about ai & automation?
Foster cross-departmental collaboration to ensure data science insights are shared and integrated into decision-making processes across the organization.
