This episode features Brad Redding, co-founder and CEO of Elevar, discussing the evolving landscape of data analytics for e-commerce, especially for DTC brands on Shopify. He emphasizes the need for goal-oriented data collection and interpretation in an era of AI automation and increased privacy restrictions like iOS 17, providing actionable advice for merchants to refine their data strategies and ensure accurate conversion tracking.
Key takeaways
Focus data collection and analysis on specific business goals to glean credible and actionable insights, moving beyond arbitrary data attribution studies.
Implement server-side conversion tracking and identify alternative user matching data to accurately track activity, especially in light of iOS 17 privacy changes.
Utilize AI by framing goal-oriented prompt questions to efficiently extract relevant insights from vast datasets, rather than using it for vague, open-ended queries.
Prioritize maintaining personal health and longevity as a founder, as this directly impacts long-term business sustainability and decision-making.
Proactively adapt to changes in data privacy regulations and platform updates (e.g., iOS 17) by adjusting tracking methods to maintain data accuracy and avoid disruptions in campaign optimization.
Chase Zieman is the Co-founder, Chief Data Officer, and General Manager of Data Products at Cart.com, an e-commerce software and service provider helping brands scale and streamline delivery processes. Chase is an expert in the data sciences industry and has experience leading high-performance teams for growth. He began his career in AI within Deloitte's counter-terrorism and fraud detection spaces before leading data science at companies, including Home Depot and Vail. In this episode... Tracking attribution helps you understand your customers' online habits and the marketing strategies influencing their purchases. While the benefits of attribution are invaluable, the model is not perfect — and it may create more questions than answers. What are the practical methods for resolving frequent attribution issues? As data analytics rapidly evolves, traditional attribution models are being discontinued. With rumors of third-party cookies dissolving, your company must adapt to these new developments to continue tracking your customers' digital behavior. Recognizing the future of data analytics, Chase Zieman found a solution that doesn't rely on third-party cookies. On this episode of the Up Arrow Podcast, William Harris welcomes Chase Zieman, Co-founder, Chief Data Officer, and General Manager of Data Products for Cart.com, to discuss how to solve issues associated with attribution tools. Chase also shares the limits placed around attribution models, how limited attribution will affect the marketing industry, the value of campaigns, and how utilizing the fourth dimension will impact our world.
What does this episode say about analytics & attribution?
Focus data collection and analysis on specific business goals to glean credible and actionable insights, moving beyond arbitrary data attribution studies.
What does this episode say about shopify & ecommerce platforms?
Implement server-side conversion tracking and identify alternative user matching data to accurately track activity, especially in light of iOS 17 privacy changes.
What does this episode say about ai & automation?
Utilize AI by framing goal-oriented prompt questions to efficiently extract relevant insights from vast datasets, rather than using it for vague, open-ended queries.
What does this episode say about founder & leadership?
Prioritize maintaining personal health and longevity as a founder, as this directly impacts long-term business sustainability and decision-making.
What does this episode say about analytics & attribution?
Proactively adapt to changes in data privacy regulations and platform updates (e.g., iOS 17) by adjusting tracking methods to maintain data accuracy and avoid disruptions in campaign optimization.
