How 52 Entertainment Data Team Saved 60+ Hours Monthly

Company

52 Entertainment is a leading game editor with a focus on evergreen games. The company develops and operates a wide range of card games, including bridge, canasta, solitaire, spades, and others, as well as skill-based games like dominoes and Yahtzee. These games are available on both mobile and web platforms. 52 Entertainment has achieved impressive user engagement metrics, with hundreds of thousands of daily active users (DAUs) for most games and millions for some titles like bubble shooter and word search. The company operates globally, with a strong presence in Europe and its headquarters in France. Currently, the company employs around 250 people across eight game studios, divided into two business units: competition games and casual games.

Problem

Before adopting Mitzu, 52 Entertainment worked on modern data stack integration with tools like BigQuery, dbt, and Looker. While the team effectively answered marketing and monetization questions, such as predicting a campaign's return on ad spend (ROAS), they struggled with product-related analytics. The company had implemented client-side tracking using Firebase but found that Looker wasn’t suitable for product analytics tasks like cohort analysis or event funnels. As a result, the team relied heavily on notebooks and manual query building, which was time-consuming and inefficient. This lack of capability led to frustration among Product teams, who started using alternative tools independently, creating silos and complicating data alignment.

Solution

After evaluating several options, 52 Entertainment found Mitzu to be ideal for their modern data stack. Mitzu aligned perfectly with their technical setup and offered a cost-effective solution by allowing them to pay only for the interface and query builder without incurring additional data collection or storage costs. The data team quickly adopted Mitzu, and it was soon embraced by Product teams as well. To ensure widespread adoption, the company organized regular workshops and training sessions. This transition enabled faster and more efficient product analytics, with Product teams now empowered to answer their questions without relying on the data team.

Results

With complete control over the data model, the team can easily integrate and enrich data from multiple sources without reverse ETL processes. Additionally, Mitzu allows for more granular analysis of A/B tests conducted on Firebase, offering insights beyond what is available through the Firebase platform.

Saved 60+ hours/month for the Data team, freeing them to focus on high-value projects over routine reports.

100% control over the data, resulting in consistent product analytics insights

Full autonomy for Product teams to manage and analyze data independently, reducing reliance on the Data team.

2x faster integration from multiple data sources, eliminating the need for reverse ETL processes and streamlining data enrichment.

" Mitzu has been a game-changer for our product analytics at 52 Entertainment, providing deep insights that drive smarter decisions. Its easy-to-use interface and powerful features make data analysis impactful.”  – Nicolas Graziani, Data Analyst - Growth & Marketing

"Mitzu didn’t just improve our tooling—it transformed our culture around data. We’ve gone from reactive reporting to proactive exploration." - Jean-Christophe Lavocat - Head of Data & Growth

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