Episode 18 - Boost Profits, Cut Churn & Maximize Growth

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🤖 This weeks collection of AI Stories

• My good friend Kofi Annan has created a brilliant playbook on how to read your customers minds with AI, get access here

• A few weeks ago, I published this post covering some brilliant ChatGPT prompts for problem-solving. I hope you find them as useful as I have.

• Here’s an article on the best AI tools for customer retention

📰 Summary of the Previous 5 Episodes

Episode 13 - How Improving Retention 5-10% Can Double Profits

In this episode, we explored how a 5-10% improvement in retention can lead to a doubling of profits. By reducing churn, companies can lower acquisition costs, improve customer lifetime value, and enhance upsell opportunities. The key lies in focusing on critical moments of truth, such as the first 90 days or the cancel journey, and using data-driven insights to optimise customer experiences. Even minor improvements to retention at these key moments can significantly impact profitability.

Episode 14 - When to Double Down on Customer Retention

This episode explores when to shift focus from acquisition to retention. While acquisition is crucial at launch, developing a retention plan from day one is essential. Once you validate product-market fit, reallocating resources toward customer retention can dramatically impact long-term growth. Investing in high-value customers through optimised retention strategies becomes vital as your market penetration increases.

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Episode 15 - Why Customer Data Is the Key to Retention-Led Growth

In this episode, we explore how customer data is crucial for optimising moments of truth to enhance retention and reduce churn. Leveraging data allows you to understand customer needs, behaviours, and pain points, whether during onboarding, service issues, or the cancel journey. Brands like The Financial Times, Netflix, Starbucks, and Apple exemplify how data-driven insights can enhance personalised experiences, build loyalty, and drive value.  

Episode 16 - How To Prioritise Your Data Science Efforts

In this episode, we dive into how to prioritise data science efforts, emphasising the importance of mastering descriptive analytics before jumping to predictive models. Some basic but high-value descriptive analytics techniques are covered, including revenue deciles, cohort movement through time and cohort decomposition.

Episode 17 - Leveraging Customer Data to Identify & Act on Drivers of Churn

By transforming data into actionable insights, brands can better understand customer needs and develop retention-focused experiences at critical moments of truth. In this episode, we outline the step-by-step process for analysing churn events, identifying key customer cohorts, and uncovering the deeper reasons behind churn. Armed with these insights, you can adjust experiences to address specific churn triggers and improve retention.

Until next week,

Tom

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