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With no in-house finance team, a new freemium offering (ClassDojo Plus) and a desire to better understand their drivers of growth, ClassDojo’s revenue team was inhibited by Google Sheet’s limitations:
With ClassDojo’s team eager to learn about their business in data driven and probabilistic ways, it became essential for them to have the ability to have a model where assumptions could be quickly changed, to add and compare scenarios effortlessly and to share relevant and real-time dashboards and models in logical ways. ClassDojo partnered with Causal to accomplish these goals in a number of ways:
With Causal, the ClassDojo team is able to effortlessly model and analyze multiple revenue lines, each having different characteristics. With each revenue model built as their own model, the team can now analyze projections at a granular and consolidated levels. These projections are then able to be layered in with dynamic scenario functionality so they can understand each case as they solidify their plans.
With connected data, easy to use formulas and automated cohort calculations, the ClassDojo team was able to finally gain confidence in their retention curves and metrics as they knew they were modelling in accurate and reliable ways.
Causal’s natural language formula syntax and easy-to-follow formulas allowed incoming data science and engineering team members to understand how each component of the revenue model works, and follow how each output traces back to their respective inputs.
With Causal’s revenue planning model humming in the background, ClassDojo can spend more time on what matters: building the best customer experience for their fast-growing community of students and their families.
With more time and fewer worries about data accuracy, they are able to free up resources to focus on product strategy and execution.
With a small team focused on cross-functional collaboration, the ability to ‘de-mystify’ the revenue model with natural syntax language and linked formulas that actually make sense have allowed the product, engineering and data team to work better together as they focus on hitting targets and building ranges of confidence within their financial models.
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