AI/ML/Data
September 8, 2022

Founder Spotlight: Count

David Smith

About Count

Count is a collaborative data platform that breaks down silos between data teams and their stakeholders, allowing fast growing start-ups to gather data, derive insights, and solve problems faster. 

Current data tools focus on helping data analysts create insights, but they don’t support data analysts in the most important part of the process: turning those insights into outcomes. This leads to crazy workflows, endless ad hoc requests, and tons of single use dashboards and reports. This is problematic: it underutilizes data analysts’ skill set, and it stops short of the end goal - making informed data-driven decisions. This white space in the industry is what Count sees as the “last mile” of analytics. By the numbers, customers use Count more than 17 days per month on average, demonstrating the integral role it plays in their day to day.

Count goes beyond mere dashboard. They create a space where data analysts and stakeholders can discuss, explore, and present data in real-time. This reduces data analysts’ workload by up to 75% and enables organizations to bring data to the center of how they work. 

Product Launch: Count canvas!

This month, Count is launching the Count canvas, a product nine months in the making. The Count canvas redefines the way teams work, turning data analysis into a team sport.

The Count canvas combines the best features of a virtual whiteboard, SQL IDE, and data visualization tool to redefine how groups of people work with data. It is a shared workspace where data analysts and their stakeholders can collaborate, simplifying the messy nature of analysis.

Users leverage whiteboard features to review problems, discuss ideas and structure their thinking using post-it notes, shapes, and free text annotations. But the magic starts as they combine these objects with queries and charts directly from their database. Analysis often begets more analysis. Insights trigger follow-up questions. The Count canvas allows data and functional experts to iterate together to ask questions, answer those questions, and arrive at a shared understanding. 

Count canvas that enables stakeholders and data analysts to bring data and content together to solve problems.

Once the analysis is complete, users can convert their canvas into a production-ready report and present it in real-time. Reporting options are flexible to align with any use case. Users can build dashboards, notebooks, or even slide decks from the same canvas, providing new ways for data teams to work with their stakeholders.

User sign up flow report, one of many output types possible due to the flexibility of the Count canvas.

The Count canvas product launch is just the beginning. Count’s product roadmap is full of amazing features and ways to help teams collaborate with data better.  

 The Founders Behind Count

Behind the Count canvas creation are co-founders Oliver Hughes (Ollie), CEO, and Oliver Pike (Oli), CTO. “Oli and I have been friends for over 15 years. We first met at University before living together in a terrible flat in London when we first started our careers. We’ve rowed against Olympians, skied the Andes, and now support each other as we cope with the much greater (but rewarding) challenge of building a business whilst having small children.” - Ollie Hughes

Oliver Pike and Oliver Hughes rowing at University, 3rd and 4th from the right, respectively.

The Team

From the start, Ollie and Oli knew how important it was to build a successful team. When asked about recruitment, Ollie commented that the majority of their team has found them. Talk about a founder’s dream! Their members were drawn to the venture because they had directly or indirectly experienced the problem of data analysis and collaboration. This creates a unique recipe when it comes to building a solution.

 As Taylor Brownlow, Head of Product at Count said, “We’re lucky in that nearly each of us has been on the other side of this problem - working every day with data. Many of us have been data analysts ourselves and the rest have been asked to impersonate one. We know the things that didn’t work, what frustrated us and made us want to do something else. Equally, we know what makes working with data so wonderful and rewarding.”