In this presentation you will find information about importance of Key Performance Indicators (KPI's) for subscription-based (SaaS) Internet startups. The full list of metrics mentioned in the presentation, exact formulas, and examles you can find at http://datmachine.co/saas_metrics. If you have any questions, don't be shy to drop me a line on my email: efremov(at)datmachine.co.

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

10. Thank you!
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