From Hypergrowth to Loyalty: HelloFresh's Strategy Change

With 1.7 billion euros in revenue in the first half of 2025 and millions of meals delivered per week in 18 countries, HelloFresh has become the world's leading provider of meal kits over the last 14 years.

Today, however, the focus has shifted from rapid growth to lasting customer loyalty. Juliane Kappel, Managing Director DACH, talks about personalization through data and AI, about more than 15,000 collected recipes and about how HelloFresh understands its customers' preferences better and better. She also explains how marketing, sales and the ready-to-eat brand Factor work together to meet the growing desire for convenience.

The conversation at a glance

1. 1:45 HelloFresh from Berlin Startup to Global Meal Kit Provider
2. 7:30 Menu Planning & Technology: How Data and AI Optimize Meals
3. 13:26 Customer Experience & Personalization: Every Delivery as an Individual Experience
4. 23:40 HelloFresh's Marketing and Sales Strategies
5. 36:30 Ready-to-Eat & Convenience Products: How HelloFresh and Factor Complement Each Other
6. 40:37 HelloFresh's Future and Expansion Plans

Data and AI as drivers of value creation

HelloFresh's strategic shift shows that anyone who wants to retain customers over the long term and achieve operational excellence must consistently align their digital transformation with data and automation. HelloFresh is already using AI along the entire value chain, from efficient quantity and route planning in logistics to reducing manual effort in creating recipe cards.

Successfully implementing AI in companies and driving tech stack optimization in e-commerce requires a comprehensive approach. To create data-based customer experiences, for example to implement a tailor-made search & recommendation engine or to interlink existing systems through CRM integration, Etribes supports companies from potential analysis to scalable implementation.

As a specialized AI consultancy, Etribes sees artificial intelligence as a measurable lever for modern business models rather than an end in itself. Whether it is process automation with AI to reduce costs or the development of intelligent chatbots and AI assistants, the aim is to deliver visible business impact within a few weeks, fully integrated into existing system landscapes and enterprise-ready from the start.