How Mitzu helped Prezi to reach 100% data accuracy?
Company
Founded in 2009, Prezi offers visual communication tools that help people create engaging, dynamic presentations. Unlike traditional slide-based formats, Prezi’s zoomable canvas lets users present ideas in a more interactive, non-linear way. This approach makes it easier to explain complex topics and keep audiences engaged. With over 100 million users worldwide, Prezi is popular among businesses, educators, and students. The company is headquartered in Budapest, Hungary, and San Francisco, USA, with teams supporting users around the globe. Previously they used Indicative as an analytics tool.
Challenge
Before implementing Mitzu, the company relied on third-party tools and its own tracking system. While these tools enabled some level of self-served data access, they lacked reliability and consistency. The existing solution processed data in daily batches, leading to delayed insights and no real-time overview of product performance.
The pipeline frequently experienced synchronization issues, causing inconsistencies and confusion about the accuracy of the insights.
A major pain point was the dependence on third-party tools, which meant limited ownership of the data. If errors occurred, it was difficult to pinpoint the source. The company needed better control and aimed to double data reliability by owning the entire data process. Additionally, there was a strong push to enable self-service access to reliable data across the organization, reducing ad-hoc requests to the data team and allowing them to focus on more strategic tasks.
Solution
The company chose Mitzu for its warehouse-native analytics solution, which ensures 100% data accuracy by syncing directly with their data warehouse. This eliminated the need for third-party tools, giving the company complete control over its data. If errors occurred, they could be traced back to internal sources, doubling the overall reliability of insights. Automated SQL generation allowed teams to build and query data transparently, providing more control and eliminating the "black box" nature of previous tools.
Mitzu also stood out for its self-service BI capabilities, empowering product managers and other teams to access and analyze data independently without constant support from the data team. This significantly reduced the number of ad-hoc requests towards the data team. Additionally, Mitzu’s responsive customer support made the company feel like a part of the product’s development, with feature requests addressed promptly—something other solutions did not offer.
Results
100% accuracy and trust in reports
5x cheaper compared to third-party tools
50% reduction in data-related support tickets
Reduced reporting time from 2 days to 2 hours
Mitzu transformed our data into a reliable, transparent resource, removing the uncertainty of third-party tools. By giving us full control over our data, improving reliability, and offering faster query responses, it became an invaluable tool for our team. I highly recommend Mitzu to any team looking to generate insights for everyone, without the need for a dedicated analytics team.
- Ivan Santini, Lead Analytics Data, Prezi
How did you manage product analytics before using Mitzu?
Before Mitzu, we were using a mix of third-party tools along with our own tracking for funnel analysis. We were able to access self-serve data, but the lack of control over it was a big issue. The data often wasn’t reliable and there were syncing problems. It took too long for us to trust what we were seeing. The third-party tools were okay for basic analysis, but they were expensive and didn’t offer the level of transparency we needed.
How are you using Mitzu today?
Today, Mitzu is an integral part of our daily operations. Our data analysts spend far less time writing long queries and handling ad-hoc requests. Instead, they can now focus on more complex tasks that drive value for the business. Other teams, such as marketing, product, and sales, can now explore their own data and perform detailed analyses like A/B testing, segmentation, and user funnel analysis without waiting for us. This has significantly sped up data-driven decision-making across the company.
Product Managers (PMs) can now confidently access the data without relying on the data team, and we've reduced ad-hoc queries by at least 50%. Additionally, PMs can iterate on user funnels at least 3x faster, enabling them to identify issues and fix them in real time.
Perhaps the most important change is the control we now have over our data. If something goes wrong, we know it’s on us, not a third-party tool. This level of control has been crucial in ensuring that our data is accurate and reliable at all times.
How has Mitzu impacted your teams and decision-making process?
Mitzu has had a significant impact on both the speed and accuracy of our decision-making. It has made self-service analytics a reality across different teams, empowering product, marketing, and other departments to access and analyze data on their own. PMs now have quick access to insights and can act on them without waiting for reports. This has shortened decision-making cycles, as the team can access the information they need instantly. The data analyst team is now spending more time on complex tasks rather than routine reporting, improving overall efficiency across the company.
Who would you recommend Mitzu?
I would recommend Mitzu to product-led growth companies that need high-quality, reliable data to drive decisions. It's particularly useful for tech and SaaS businesses that need to track user interactions and make data-driven decisions at scale. If you have first-party data and need to get more value out of it, Mitzu is an excellent solution to consider.
