Digital data reliability platform designed to monitor and offer alerts for missing or inaccurate data.
Monte Carlo is a data reliability platform that uses machine learning to automate the process of detecting issues and anomalies in databases. - Raised $135M in Series D - Top investor: Accel.
Users struggled to understand insights and customize their monitors. There was decreased user engagement, due to confusion, so users weren’t seeing the value Monte Carlo provided. Also the resource brandwidth due to helping users manually track data.
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Monte Carlo knew they needed a fresh perspective to help them tackle the challenge of summarizing complex data into digestible and actionable insight. Our streamlined processes and user-focused strategies meant we could look past the product’s complexity and apply human-centered design practices to improve the flow. With our help, Monte Carlo could create a user-friendly experience that empowered users with information and advanced options to monitor complex data more easily.
We helped Monte Carlo respond to user feedback with an optimized experience that kept customers happy and engaged.
Using a human-centric approach helped us quickly understand how to create the most effective experience for Monte Carlo’s unique user base.
Our outside perspective and expertise allowed us to identify opportunities for improvement and offer alternative solutions to create a unified product.
After implementing redesign, Monte Carlo saw an immediate improvement in user engagement
Data-backed processes and expertise helped Monte Carlo provide users with actionable insights, and a simplified customer navigation experience. With a touch of The Design Project, Monte Carlo’s incredible team developed and executed a strategy that focused on providing actionable insights that taught users how to customize their monitors.
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