Customer-/user- and team-oriented whiteboards for all relevant marketing data are a real game changer. We were surprised at how easy it can be to manage large amounts of data from various databases and clouds with visual support and to create, test, and visualize data models. The integration of count into existing analysis and communication workflows is possible in a short time and generally unproblematic, provided that data is already centrally available (e.g., in Google BigQuery). Count offers very good and responsive customer support via Slack, including a large community.

I love the flexibility of Count—it has transformed the way I work with data and share insights with business users over the past two years. Previously, my workflow might have involved writing SQL queries in an IDE, exporting and analyzing the results in Excel or another tool, and then passing them along to end users for further analysis. With Count, I can now do almost everything in one place on an infinite canvas. Most importantly, it enables me to build complex models from smaller queries / data cells and visualise them step by step. The canvas approach also makes it easy to collaborate with business users, presenting and sharing data in a way that’s both clear and accessible. Their support team are always helpful - Ive suggested a few minor features and they were implemented pretty quickly!

Count has been a game-changer for our data team. Its unique blend of a data notebook and collaborative whiteboard has transformed the way we approach analysis—moving us away from static dashboards and towards deeper, more impactful problem-solving. The ability to query data in SQL, visualize results, and collaborate with stakeholders in real-time within a single workspace has streamlined our workflows and boosted team productivity. We particularly value Count’s intuitive approach to breaking down complex SQL models into connected CTE graphs with live results. This makes exploring, debugging, and iterating on data models both faster and more collaborative. Exporting work as full SQL scripts is equally smooth, keeping our work highly shareable and actionable.