Cloud Expense Software Churn Data

Columns

• Cliente: The unique identifier or name for each customer. There are 330 distinct customer entries, all valid.
• Estado Cliente: Indicates the current subscription status of a customer, categorised as 'Active' if they are currently paying for the service, or 'Churned' if they have ceased their subscription. Approximately 71% of entries are 'Active', while 29% are 'Churned'. There are 2 unique values, and all 330 entries are valid.
• Mes Registro: The date, formatted as month/year, when a user initially subscribed to the service. The registration dates span from January 2019 to December 2020. All 330 entries are valid, with a minimum date of 1 Jan 2019 and a maximum of 1 Dec 2020.
• Mes de Abandono (Churn): The date, formatted as month/year, when a user cancelled their service. This column is populated for customers who have churned, covering dates from March 2019 to December 2020. It has missing values for customers who are still active; 99 (30%) entries are valid, while 231 (70%) are missing. The minimum churn date is 1 Mar 2019 and the maximum is 1 Dec 2020.
• 1/2019 to 12/2020 (24 columns): These columns represent individual months from January 2019 through to December 2020. A value of '1' indicates that the customer paid for the service in that specific month, while an empty cell signifies non-payment. For example, '1/2019' has 11 valid entries, '2/2019' has 24, and '12/2020' has 233 valid entries, each representing customers who paid in that month.

Distribution

Usage

• Conducting in-depth cohort analysis to monitor customer retention trends over time.
• Calculating monthly and quarterly customer retention and churn rates.
• Identifying specific months or quarters where customer loss was most pronounced.
• Assessing Product-Market Fit (PMF) by observing user stickiness and sustained engagement.
• Supporting strategic business discussions on resource allocation, such as balancing investment between marketing for user acquisition and enhancing product features.
• Developing skills in data organisation, manipulation, and analysis using spreadsheet tools, including pivot tables, VLOOKUP, and Query functions.
• Informing decisions on whether to scale a business or prioritise product improvements.

Coverage

License

Who Can Use It

• Junior Data Analysts: To gain practical experience in customer behaviour analysis, cohort studies, and business metric reporting, and to present data-driven recommendations.
• Product Managers/Directors: To evaluate product stickiness, understand user journeys, and inform product development roadmaps, especially concerning PMF.
• Finance Directors: For budgeting, investment planning, and understanding revenue stability linked to customer retention.
• Marketing Directors: To justify marketing spend by correlating acquisition efforts with long-term retention outcomes and to strategise on scaling user acquisition.
• User Experience (UX) Design Directors: To identify points of friction leading to churn and pinpoint areas for user experience improvement.
• CEOs and Business Leaders: For strategic planning, assessing business health, and making critical decisions on scaling operations or reallocating resources, particularly regarding investment in growth versus product enhancement.
• Students and Educators: As a real-world case study for learning data analytics, SaaS metrics, and the concept of Product-Market Fit, including data organisation, manipulation, and filtering with queries.

Dataset Name Suggestions

• SaaS Customer Retention Analysis 2019-2020
• Cloud Expense Software Churn Data
• Product-Market Fit Cohort Study
• Monthly SaaS Customer Engagement Metrics
• Startup Retention Analytics

Attributes