KPI analytics for saas startups
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The document outlines the importance of KPIs for SaaS startups, focusing on monitoring business performance, developing strategies, and managing implementation plans. It details metrics for customer acquisition, retention, and churn, along with guidelines on setting target values and performing data analysis. Additionally, it provides resources for data storage and tools for analyzing KPIs effectively.
KPI analytics for saas startups
- 1. KPI analytics for SaaS startupsMETRICS: THE WHY, WHAT AND HOW
- 2. Why Do You Need KPI's Monitor the business performance Develop successful strategies Control the implementation of plans
- 3. Performance Management Lifecycle 1. Decide what to measure 2. Select relevant metrics 3. Set target values for selected metrics 4. Create and implement an action plan 5. Analyze results by comparing real and target values
- 4. What to measure: SaaS Customer Lifecycle Acquisition • Traffic • Conversion • Costs Retention • Number of customers • Structure of customer base • Upgrades and Downgrades Churn • Total number of lost customers • Lost revenue
- 5. Acquisition: Metrics Traffic Number of new visitors and growth rate Bounce rate New visitors by countries Conversion Conversion from visitor to trial plan Conversion from visitor to non-trial plans Costs Customer Acquisition Cost (CAC) = Marketing costs / Number of new customers CAC by channels Time to recover = CAC / ARPA
- 6. Retention: Metrics Total number of customers and growth rate Revenue and growth rate Structure of customer base Number of new customers and average revenue from new customers Number of customers by plans Average revenue per account (ARPA) = Revenue / Number of customers Number of upgrades and downgrades Customer lifetime value (CLV) = ARPA / Churn rate
- 7. Churn: metrics Number of lost customers and growth rate Lost revenue Churn rate = Number of lost customers / Customers at the beginning of the period Net customers = Number of new customers - Number of lost customers
- 8. Target values should be: Realistic Time-framed Accessible for team members
- 9. How to analyze data? Where to find data? Web analytics tools (Google analytics, Mixpanel etc.) Your payment gateway ( Stripe, Braintee, Recurly, Chargify etc.) Where to store data? Spreadsheet applications ( Excel, Gdrive etc.) Business analytics tools ( Datmachine.co, Baremetrics etc.) How to analyze data? KPI dashboards Time series analysis Drilldown analysis Multidimensional analysis
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