HelloFresh: How AI and Machine Learning are driving business

Berlin / DE. (hf) With the rise of ChatGPT, Artificial Intelligence (AI) and Machine Learning (ML) have made their way from the tech world into the mainstream. But even though the broader public seems to have just discovered AI, many companies have been working towards AI and Machine Learning solutions for quite some time as it proves to be a crucial step in building a future proof business.

HelloFresh SE is heavily investing in AI and ML for more than six years now and sees them as key components of its technology platform. The Group currently has many AI driven use cases that provide real monetary benefit and helps to become an even more efficient business. With more than 70 data scientists and machine learning engineers worldwide, HelloFresh has a team of highly skilled experts that dedicate their work to continuously training, refining and deploying machine learning tech tools. With this article the Group will give an overview on how AI and ML solutions are already making HelloFresh a more efficient business and offer an outlook on the potential generative and predictive AI entail.

Data from 12 years feed into more than 1500 models per week

Data plays a very important role in the entire meal kit production process. With more than 10,000 recipes, 12 years of customer order patterns, and menu browsing behaviors, HelloFresh has a very valuable and unique database. Since its launch in 2011, the company has grown the largest and richest customer database of taste preferences worldwide. A stable data infrastructure is the base for making use of this unique data. With seven brands across 18 markets, there is a huge amount of data being generated on a daily basis. AI and machine learning models rely on consumable data sets and a self-serving data platform which the Group’s tech team continues to evolve in order to make use of the valuable data we have.

«In the past few years, we’ve been heavily investing in building up a team of talented scientists and engineers to set up the base for the HelloFresh Machine Learning models. I’m incredibly proud of the great projects that have been launched since I joined HelloFresh almost two years ago», said Val Liborski, CTO at HelloFresh.

There are a number of AI-driven applications that HelloFresh is already actively using across marketing, operations and product teams. Most of these scaled use cases rest on predictive AI, while the Group is looking forward to unlocking the potential of generative AI models in future.

AI driven Menu: Machine Learning based product recommendations

In the long-term, Artificial Intelligence will enable a fully personalized product experience for HelloFresh customers worldwide. In the US, customers can already experience that: preselected options are now ranked in the menu by a machine learning algorithm trained on customer’s previous meal selections in order to display the most relevant products for them, first. This is the first machine learning based solution the Group has launched to individualize its customer’s menu selection.

Furthermore, AI and machine learning offer a big potential for optimizing the HelloFresh Marketing costs. One of the areas the Group is already actively using AI is customer value predictions. It enables predicting future actions of its prospective and active customers, HelloFresh can individualize marketing for different customer groups and optimize and personalized discount offers. By recommending and distributing advertising budgets across creatives, audiences, channels and markets, the Group can maximize the return of such marketing interventions and accelerate growth.

The potential of AI for the future at HelloFresh

Beyond the exciting applications the Group already has in place, HelloFresh is experimenting with many more AI and machine learning models that will make the business even more efficient and sustainable in the future. In fulfillment, the Group is currently testing a machine learning driven packaging optimization algorithm. With the help of weather forecasting and packaging material data, the algorithm recommends dynamic packaging solutions that will lead to savings on packaging material – a big opportunity for decreasing the environmental impact and costs across the value chain.

Furthermore, the Group sees a big potential for AI to improve productivity across all teams at HelloFresh. Within the tech teams, AI can make coding more productive. In the long-term, generative AI models can support the Group’s video and photo production, significantly saving costs and supporting our business at scale. Val Liborski: «Given our rich experience and the talent within our tech team, we are well equipped in unlocking the full potential of AI in the years to come» (Graphics: HelloFresh).