Develop deep customer understanding through advanced analytics that reveal lifetime value patterns whilst identifying opportunities for personalisation and retention improvement. Learn customer segmentation, CLV calculation, and predictive analytics implementation that enhances customer relationships whilst improving business performance. From RFM analysis to churn prediction, master customer intelligence that drives loyalty whilst increasing profitability.
The episode provides deep insights into customer behaviour patterns during seasonal periods. Matt shares research showing when customers make purchase decisions (March-May for summer), how weather affects buying patterns (17% revenue increase before heatwaves, 48% drop during), and why mobile usage intensifies seasonally. This customer intelligence allowed one team to grow 19% by understanding and planning for actual behaviour rather than assumed patterns.
Learn how to research and understand customer motivations, emotional drivers, and behaviour patterns. Laura shares practical methods for conducting customer research without massive budgets, including AI-powered questioning techniques and feedback loop strategies that reveal the emotional truth behind purchasing decisions.
Learn how to extract actionable insights from customer data, including lifetime value analysis, retention metrics, and behavioural patterns. Jo Davis reveals the Growth Model Framework that transforms overwhelming analytics into specific acquisition targets and growth strategies.
Learn how to decode customer behaviour through strategic research and questioning frameworks. Peter demonstrates how systematic customer conversations reveal pricing opportunities, journey optimisation insights, and competitive advantages that quantitative data cannot capture. Discover practical methodologies for understanding what customers truly value and how to translate those insights into measurable business growth.
Learn how to identify and understand your most valuable customers using data analysis and predictive modelling. Neil demonstrates how Google's Chief Strategist approaches customer segmentation and why focusing on your best customers drives 60-80% of revenue growth.
Learn contextual data layering techniques that identify high-conversion customer segments without personally identifiable information. Jason shares case studies showing how proper audience intelligence transforms conversion rates.
Learn Oliver's systematic approach to understanding customer data fundamentals, including how to calculate true acquisition costs, lifetime value metrics, and retention rates. Discover why 80% of founders can't answer the basic question about customer requirements and how this knowledge gap impacts growth success.
Learn Monica's systematic approach to understanding customers through the 4D Framework (Demographics, Desires, Do, Delight) and story-based questioning techniques that reveal the emotional drivers behind purchasing decisions, transforming customer relationships from transactional to genuinely connected.
This episode is centered on understanding customer lifetime value through RFM segmentation (recency, frequency, monetary value) to identify 'soulmate' customers versus 'breakups'. Valentin provides detailed methodologies for analyzing customer data, calculating CLV, and using customer intelligence to inform business decisions across acquisition, conversion, and retention.
Kristi emphasises a critical truth many eCommerce businesses miss: customers transformed during the pandemic and aren't the same people they were in 2019. Users will learn how to conduct customer research to understand lifestyle changes, why assumptions about customer needs prove dangerous, and practical methods for staying connected (Encircled maintains a Facebook community of 1,000+ customers). The episode reveals how to identify shifts in customer behaviour, purchasing patterns, and needs—from healthcare workers who never worked from home to customers who lost all routine and structure in their lives.
The conversation covers customer analytics including transaction data analysis, understanding customer behaviour patterns, lifetime value calculations, and using data to build stronger customer relationships for profitability.
Discover the sideways survey technique and other methods for understanding true customer purchasing behaviour. Learn how to map customer journeys beyond your immediate offerings to identify what customers buy before, during, and after their interaction with your business.
Learn how Skip's conversion equation uses customer psychology (urgency, desire, trust) combined with friction factors (delay, cost, effort) to predict and optimise campaign performance. Understand how to leverage customer awareness levels for better targeting.
Explore customer acquisition strategies for new eCommerce brands, including why Meta-first approaches often outperform Google-first and how to integrate customer data across channels for algorithmic training.
Master Ian's review mining techniques that transform customer feedback into positioning gold, including the cookware example that revealed the perfect headline hidden in customer reviews.
Learn how Leonardo uses customer review analysis and behavioural data to understand what actually drives purchase decisions. Discover practical techniques like using AI to analyse review patterns and identify hidden selling angles that founders often miss.
Explore advanced customer behaviour analysis that reveals business value beyond traditional metrics. Understand why seven-month return patterns indicate stronger product-market fit than subscription models, and how predictive analytics identify genuine community engagement that drives sustainable competitive advantages.
Learn how to conduct forensic analysis of customer reviews, competitor research, and market context to identify messaging themes and creative structures that resonate with your target audience.
Explore how customer ownership transforms influencer value from temporary attention to permanent business assets. Discover why databases of proven buyers in specific categories become incredibly valuable, how AI learns from network-wide transaction data to improve recommendations, and why traditional metrics like follower counts miss the fundamental shift happening in creator commerce. Learn what makes customer data a sellable business asset versus followers that can't be transferred or monetised long-term.
The conversation explores how zero-party data provides deeper customer intelligence than traditional analytics, revealing the gap between where customers are and where they want to be, enabling more effective marketing strategies.
Drew reveals how Amazon provides valuable customer intelligence through search intent data, geographic information, and conversion analytics that brands can leverage across all channels. He reframes the 'Amazon owns customer data' concern by highlighting the actionable insights available through advertising and zip code analysis.
Michael discusses using analytics to understand customer behaviour, lifetime value, and purchasing patterns. He explains how direct-to-consumer businesses can leverage customer data to make smarter decisions about product upsells and retention strategies.
Tony emphasizes the importance of analyzing customer data to identify patterns, calculate lifetime value (frequency × average order value × profitability over 3 years), and segment markets effectively. He stresses that businesses should study their customer lists and use platforms like Shopify and Google Analytics to track these metrics over time.
Matt discusses measuring customer lifetime value (CLV) and using metrics like Net Promoter Score to identify high-value customers and advocates. The episode explains how understanding which customers are most valuable allows businesses to prioritize personalized engagement for maximum ROI.
