EP302: Confessions of A Customer Intent Expert: Lessons In Experimentation & Why Context In Data Is Everything, With FoundIt! CEO Warren Cowan

Join our LinkedIn newsletter:https://www.linkedin.com/newsletters/inside-commerce-7126171854813188096/ Podcast summary:In this podcast, Warren Cowan and James Gurd delve into the critical importance of understanding the context of data when making ecommerce decisions. They explore how misinterpreting data can lead to compromised decisions, using real-world examples like Elton John's unexpected influence on a test for Matches Fashion. The discussion highlights the necessity of scrutinising test results to ensure reliability and the dangers of relying solely on metrics like revenue per visitor, which can be easily skewed by outliers. Warren also emphasises the need for businesses to focus on customer intent and context, rather than just catalogue-driven approaches to merchandising, to enhance user experience and drive better decision-making. This episode is a must-listen for anyone looking to improve their data-driven strategies and understand the nuances of contextual data in ecommerce.Key takeaways:Understanding data context is crucial for better decision-making.Mistakes in testing can lead to valuable learning opportunities.Testing results can be skewed by outliers and external factors.Customer intent should drive the design of ecommerce platforms.The goal of focusing on customer intent is to inspire and support customers in their shopping journey.Creating a seamless shopping experience requires understanding user journeys.Retailers must adapt to changing customer behaviours and preferences.Chapters:[05:20] Warren Cowan's Journey to Founder of FoundIt![10:13] Understanding Testing and Misreading Results[15:10] Celebrity Influence on A/B Testing[19:40] The Importance of User Intent in Ecommerce[25:04] Utilising Intent Signals for Better Navigation[30:33] Creating Engaging Shopping Experiences[32:45] Capturing Behavioural Intent Signals[41:55] The Importance of Structured Product Data