Futuristic catalog for GoodWine, the market leader in alcohol and healthy products
GoodWine is the largest importer and distributor of alcohol and healthy products in Ukraine.
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The model helps Edenred build long-term relationships and retain valuable contracts
About the project
The company now identifies high-risk customers in a timely manner.
Edenred is not just a fintech company, but a global leader in payment solutions for businesses. For many years, the company has been changing the approach to corporate life for millions of people. The brand's mission is to help improve team performance and take care of employees. Edenred's digital platforms cover more than 60 million users in 45 countries. They also bring together a network of more than 2 million partners, creating an ecosystem. Well-known products such as Ticket Restaurant and Edenred make employees' daily lives easier and business processes more transparent.
Client Challenges and Needs:
The client requested to reduce the outflow of corporate clients and increase the retention rate of B2B contracts. Edenred has a huge customer base, but the lack of a solution for early detection of risky users prevented it from taking proactive action.
The main challenges facing the IWIC team were:
- the need to build a predictive mechanism that would analyze data and generate clear signals;
- the lack of a tool to identify high-risk customers at an early stage;
- the need to automate decision-making processes;
- the importance of retaining valuable long-term contracts.
The customer’s main goal was to transform data analytics into a customer retention system that would work quickly and efficiently.
How we solved the client's problem
Thanks to the model we created, Edenred can respond to risks before they start to affect the business
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Predicting user churn minimizes losses and helps manage B2B contracts effectively.
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Our approach:
Our work with Edenred began with a deep dive into the business context. Together with their team, we conducted a series of strategic workshops. This allowed us to identify key hypotheses, set goals, and agree on the main steps. After that, our specialists developed a model that would work for real business tasks. We implemented a flexible data pipeline. Compliance with GDPR requirements became an important part of the project. We ensured the anonymization of customer data so that its processing outside the EU jurisdiction would be safe and legal.
Work results:
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Working on the Edenred project was challenging but interesting at the same time. The churn prediction model we created was seamlessly integrated into the company’s internal processes and began to respond quickly to risk signals.
Our main results:
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- the accuracy of forecasts has increased thanks to adapted business metrics and relevant functions;
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- high-risk customers are identified at an early stage, allowing for timely intervention;
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- full GDPR compliance ensures secure data processing and adherence to international standards.
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Our work provided the client not only with an analytical tool, but also with a key element of their business development and customer retention strategy.
Project details
Key facts about the project
5 months
Project duration
Medium
Project size:
Project complexity
Completed
Project status:
Our team:
Project manager
Вusiness analyst
Data engineer
2 Data Science engineer
Data Analyst
DevOps
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