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Customer Story

Professionalizing BI Processes to Improve the Customer Experience

Learn how entertainment business Pathé professionalized its BI processes, and became better at improving customer experience and predicting customer numbers
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Data Technology

Technology | Telecom | Media


Big, luxurious cinemas. That’s what Pathé envisioned 25 years ago when it first started. At present, Pathé is the largest of its kind, with 30 theatres in the Netherlands. The cinemas themselves are well-known for their extensive film presentation and complete experience. Each year 15 million visitors enjoy the latest projection techniques, comfortable seats, Pathé’s innovative food & beverage concepts.

To optimize the visitor experience and business processes
Better prediction of of visitor numbers equals a more efficient operation
Leveraging AWS data platform to make better predictions

The Challenge

Four years ago, Rick Stammes, Business Analyst at Pathé, began professionalizing the cinema’s BI. Especially on the management level, they benefited greatly from a data-driven way of working. This inspired Pathé to extend the benefits of data to other departments, such as marketing. The cinema’s ultimate goal is to optimize its visitor experience and business processes with data it collects from multiple sources, such as the website, app, and cash register systems, but also data related to the weather or major sports events that may affect the number of visitors. To centralize the data and make it available to the organization, Pathé chose to work with Xebia, who formed a team of cloud and data consultants to develop a data platform on Amazon Web Services.



"I’m curious to see what our data-driven future will look like. By using data, we now know how to stay relevant for individual visitors. I’d like to go beyond predicting theater occupancy and introduce smart applications to optimize the number of visitors. But that’s not all. Data also helps us better understand the member life cycle and retain members."
Rick Stammes Business Analyst at Pathé

The Solution

Data Platform

Bas Harenslak, Data Engineer at Xebia Data and AI, and Laurens Knoll, Cloud Engineer at Xebia, started to develop the infrastructure, the data platform, and the data processes. Bas explains: “We started from scratch with AWS. In addition to security, we paid particular attention to scalability and the greatest possible simplicity of use.” Pathé’s data is made available on the data platform via the AWS service RDS. For the notebooks and training of the models, Xebia chose to implement AWS Sagemaker, and ECS hosts the models. “Every day, we load the data of the latest movies to train the recommender. Then we deploy this model to Sagemaker again. Via the ETL pipeline, we ensure the data arrives in the right form at the right place. This is how we make data available to the rest of the organization,” Bas explains.


The new platform uses managed services from AWS for the most part. However, to control the replication of both static and streaming data from the POS systems, the Xebia engineers wrote a custom solution.

“Looking at the structure of the data platform as a cloud engineer, you get a very familiar feeling. In addition to the standard components, the way we created the connections stands out,” says Laurens. “To reduce the dependency on third parties, we wrote the coupling ourselves. We wanted to ensure that Pathé could always retrieve the data. When usage increases in the future, it will still be able to access data on demand. This gives Pathé maximum control over all its processes,” Bas adds.

Pathé’s data platform has been implemented according to the standards of the AWS Well-Architected Framework.” In this framework, security is about compliance and safe daily use. To achieve the latter, we focused on ‘keeping people away.’ Only the data engineers have access to the data, and processing is automated as much as possible,” says Bas.


“From a list of possible applications, we started with a recommender and a visitor forecast,” Rick says. The recommender was a real high potential for Pathé. “If you have seen movies one, two, three, you will probably like movie four. By comparing your viewing history with people who have a similar search or viewing history or making selections based on your favorite actors or genres, we can recommend new movies. I’ve made sure these models go to production in an automated pipeline,” Bas explains.

Another high potential was predicting the number of future visitors. Pathé was familiar with analyzing the number of visitors per theater for purchasing and planning purposes. The Xebia consultants started working with the available (historical) data to develop a model to help them do this with AWS Sagemaker. “We want to predict the number of visitors per day and theater for six weeks, for staff planning, among other things. In addition, we want to use a long-term forecast to respond to trends together with distributors,” Rick adds.

The Data Squad

An (external) Data Squad worked on Pathé’s new data goals: Bas and Laurens took responsibility for the infrastructure and bringing models to production, were joined by two other Data Scientists. Rick supported the Squad by helping them find data or write queries together, with Bas and Diederik often challenging them by asking how they could do things faster or smarter.

To achieve the goals, the Data Squad also worked very closely with the content team (film programming) and the e-commerce department, and there was a lot of testing. Pathé has 30 theaters, but also 2 million visitors in its systems. “We were already sending these movie tips by email, but we see, after a lot of testing, that the conversion rates have improved significantly by using the recommender,” adds Rik.

Finally, Pathé uses Cloud Control. “This is incredibly valuable to them because they are still building the knowledge and skills of working with the cloud. Xebia, as a partner, can supplement and guide them in building up this know-how properly and ultimately continuing to run this platform safely and securely. Pathé has a great love for movies but is just as passionate about making this platform a success,” says Laurens.

The Results

  • Using the recommender yields better results (more response, more visitors)
  • Better prediction of the number of visitors leads to more efficient operation

“Looking back, it was especially great to experience how involved everyone was. We literally saw the data and its applications come to life within the organization. For example, in the cafeteria, people would often approach us with questions and concrete ideas. We also really appreciated the ease with which we could discuss security and governance with Pathé’s compliance officer and lawyers whilst moving data from the datacenter to the public cloud.” – Laurens, Xebia.

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