ClickUp Operationalizes Churn Predictions

A Data Team Designed for Impact 

You've probably seen our billboards proudly highlighting that we’re the "one app to replace them all." ClickUp is a project management software offering a suite of features like tasks, project management, time tracking, docs, chat, and whiteboards. With over 100,000 paying customers and nearly 900 employees, we've been growing rapidly. Our data team is a key ingredient in supporting that growth, with product analytics, revenue analytics, marketing analytics & data engineering, and machine learning teams, all centralized into one data team. We also have a talented analytics engineering and data engineering team that keeps our data operations running smoothly.

Identifying the Problem

In late 2022, ClickUp faced a challenge: we needed to adapt in a market that demanded efficiency over growth. We embraced this, and used data to drive decision making. We identified churn as a key focus area where we could use data to enhance our understanding and drive mitigation efforts .

Churn, or the rate at which customers stop subscribing to our service, presented a meaningful opportunity for us to improve and innovate. We needed to understand who was churning, why they were churning, and how to improve customer retention to build a more operationally efficient business.  And we needed those insights to be disseminated throughout the organization, so that various teams could make adjustments and do their part to reduce churn.  

Ad Hoc Analysis: The Starting Point

We started with ad hoc analysis to gain insights into our churn. Our dashboards and tooling were mainly tailored for executive stakeholders, so they lacked the flexibility needed for deeper analysis by various teams. Traditional BI tools fell short in providing the necessary flexibility for different teams to analyze churn according to their unique perspective. While the executive dashboards provided high-level insights, they couldn't cater to the specific needs of individual teams like marketing, lifecycle, or customer support.

Enter Hex: Operationalizing Churn Analytics

Hex allowed us to move beyond ad hoc analysis and create interactive dashboards that could be used by multiple teams across the organization. These dashboards provided the flexibility needed for teams to dive deep into the data and derive actionable insights specific to their areas of focus.  With Hex, lifecycle marketing could focus on the at-risk segment of customers to drive deeper engagement and satisfaction, and customer success could identify customers at risk of churning and take proactive measures to retain them. We also used machine learning models to predict churn and further refine our focus on high-risk segments.

Impact and the Future

By democratizing data insights and empowering teams with actionable information, we managed to save more than a million dollars in churn-related costs. We were able to build a more operationally efficient business, driving growth while maintaining profitability. And, we democratized data insights, empowering our business stakeholders to work with data so closely that they could draft their own solutions.  With the right tools and mindset, we turned our data into a strategic asset that drives revenue growth, product innovation, customer acquisition and retention.