Average Revenue Per User (ARPU)

In the dynamic world of SaaS, data is your roadmap to clarity and confidence.

This playbook equips you with ready-to-use SQL queries for the metrics that drive growth, retention, and profitability.

No need for advanced technical skills—just adapt the table and column names to your database, and let the insights unfold.

How to Use This Playbook

1. Choose your metric.
   Find the metric that answers your most pressing questions.
2. Copy the SQL.
   Swap in your own table and column names.
3. Run it in your database tool.
   Watch as the numbers reveal your business’s story.

Industry Benchmarks & Standards

Your Data Foundation

These tables are the pillars of your SaaS analytics:

• main.saas_data_clients: The foundation of every client relationship.
  
  • client_id, client_name, created_at
• main.saas_data_customers: Every user’s journey, captured in detail.
  
  • customer_id, client_id, customer_name, signup_date, is_active
• main.saas_data_plans: Your product’s menu of options.
  
  • plan_id, client_id, plan_name, monthly_price, annual_price, is_active
• main.saas_data_subscriptions: Captures the full lifecycle: sign-ups, renewals, and cancellations.
  
  • subscription_id, client_id, customer_id, plan_id, start_date, end_date, status
• main.saas_data_payments: The flow of revenue through your business.
  
  • payment_id, client_id, customer_id, subscription_id, amount, payment_date, is_refund
• main.saas_data_events: The story of every login, upgrade, and farewell.
  
  • event_id, client_id, customer_id, event_type, event_date, is_churn
• main.saas_data_costs: The price of delivering value to your customers.
  
  • cost_id, client_id, customer_id, cost_type, cost_amount, cost_date

Average Revenue per User (ARPU)

ARPU is your guide for pricing and product strategy. The higher your ARPU, the more value your users see—and the more they’re willing to pay. Monitoring ARPU trends helps you fine-tune your pricing, identify upsell opportunities, and align your offerings with what customers truly value.

WITH
-- 1. Active users per month
"monthly_active_users_cte" AS (
  SELECT
    DATE_TRUNC('month', "event_date") AS "month",
    COUNT(DISTINCT "customer_id") AS "active_users"
  FROM "main"."saas_data_events"
  WHERE "event_type" IN ('login', 'feature_use')
  GROUP BY DATE_TRUNC('month', "event_date")
),

-- 2. Revenue per month
"monthly_revenue_cte" AS (
  SELECT
    DATE_TRUNC('month', "payment_date") AS "month",
    ROUND(SUM("amount"), 2) AS "revenue"
  FROM "main"."saas_data_payments"
  WHERE NOT "is_refund"
  GROUP BY DATE_TRUNC('month', "payment_date")
)

-- 3. Overall ARPU per month
SELECT
  "monthly_active_users_cte"."month",
  "monthly_active_users_cte"."active_users",
  "monthly_revenue_cte"."revenue",
  ROUND(
    "monthly_revenue_cte"."revenue" / NULLIF("monthly_active_users_cte"."active_users", 0),
    2
  ) AS "arpu"
FROM "monthly_active_users_cte"
JOIN "monthly_revenue_cte"
  ON "monthly_active_users_cte"."month" = "monthly_revenue_cte"."month"
ORDER BY "monthly_active_users_cte"."month"

Visualization Ideas:

• Combo Chart with Dual Axis: Compare ARPU and Active Users across plans or segments
• Dual Axis Line Chart: Watch ARPU and Active Users rise and fall across the months.
• Dual Axis Bar Chart: Compare ARPU and Active Users across plans or segments.
• Scorecard: Make your current ARPU impossible to ignore.

Implementation Checklist

1. Define your metrics and add them to a data dictionary.
2. Ensure your database schema supports the required calculations.
3. Write and test SQL queries for each metric.
4. Import results into your BI tool. Get started with DataBrain today!
5. Build and share dashboards with stakeholders.
6. Schedule regular reviews and updates.

Unlock the power of your data.
Start using this SQL Playbook today!

“In the world of SaaS, data is everyone’s responsibility. With this playbook, anyone can own their metrics and drive better outcomes.”

Now, simply run the SQL queries on your data and unlock the power of your SaaS analytics!