Key Product metrics

"What gets measured gets managed" ~ Peter Drucker

Introduction

Usually I hear people talking about metrics in the context of business, but what about product metrics? In this article, we will dive into the top 10 product metrics that will help you measure the success of your product. In a meeting context, when someone says 'I think' often indicates an opinion rather than a data-backed conclusion. Data is the oil of 21st century and analytics as an internal combustion engine.So Data is a product manager's best friend i,e most valuable tool for any decision makings.

1. ARR

Definition : Annual Recurring Revenue is used to measure the recurring revenue generated by a business annually, often in subscription-based or SaaS (Software-as-a-Service) business models. It provides insight into the stability and predictability of a company's revenue stream.

Why its useful

Formula : ARR = Total Monthly Recurring Revenue (MRR) × 12

Example : Let's take Netflix as an example to calculate MRR.

Netflix Subscription Plans (Hypothetical Numbers)

Netflix offers the following subscription plans and subscribers:

1. Basic Plan: $10/month, 50 million Subscribers

2. Standard Plan: $15/month, 70 million Subscribers

3. Premium Plan: $20/month, 30 million Subscribers

Step 1: Calculate Revenue from Each Plan

Revenue from the Basic Plan : 50,000,000 × 10 = 500,000,000 $/month

Revenue from the Standard Plan: 70,000,000 × 15 = 1,050,000,000 $/month

Revenue from the Premium Plan: 30,000,000 × 20 = 600,000,000 $/month

Step 2: Total Monthly Recurring Revenue (MRR)

MRR = Basic Plan Revenue + Standard Plan Revenue + Premium Plan Revenue

MRR = 500,000,000 + 1,050,000,000 + 600,000,000

MRR = 2,150,000,000 $

Step 3: Insights

• Netflix generates $2.15 billion in MRR from its subscription-based model.

• This metric helps Netflix forecast its Annual Recurring Revenue (ARR): ARR = MRR × 12 = $2.15 billion × 12 = $25.8 billion/year.

2. CLV

Definition : Customer Lifetime Value is the total revenue or profit generated by a customer over the entire course of their relationship with your business.It helps businesses understand the long-term value of their customers and make informed decisions about customer acquisition, retention, and product strategies.

Why its useful

Formula : The formula can vary based on the business model. Here's the simplest version:

CLV = Average Purchase Value × Average Purchase Frequency × Customer Lifespan

Example : Subscription-Based Business (Netflix)

Netflix wants to acquire new customers and is considering spending more on marketing campaigns. To determine whether this investment is worthwhile, they calculate CLV.

Step 1: Calculate CLV

Assumptions:

1. Average Monthly Subscription Fee: $15
2. Average Customer Lifespan: 3 years (36 months)
3. Gross Margin: 80% (after deducting costs like licensing and operations)

Using the CLV formula:

CLV = (Average Monthly Subscription × Gross Margin × Customer Lifespan)

CLV = $15 × 80% × 36 = $432

So, the average CLV per customer is $432.

Step 2: Compare CLV to CAC

Assumptions:

1. Customer Acquisition Cost (CAC): $100 per new customer (cost of advertising, promotions, etc.)

Analysis:

• CLV ($432) > CAC ($100)

This means Netflix earns $332 of profit per customer over their lifetime. Acquiring new customers at this cost is a profitable strategy.

Step 3: Business Decision

Now, Netflix has two options for a new marketing campaign:

1. Campaign A: Costs $120 per new customer (higher CAC).
2. Campaign B: Costs $80 per new customer (lower CAC).

Which campaign should Netflix choose?

1. Campaign A’s CAC $120 is still less than CLV $432 , so it is profitable, but the profit margin is lower $432 - $120 = $312.
2. Campaign B’s CAC $80 has a higher profit margin $432 - $80 = $352`.

Netflix would likely prioritize Campaign B unless Campaign A brings in higher value customers or expands into a new market.

3. CAC

Definition : Customer Acquisition cost is the total cost spent by business on acquiring a new customer.It's a crucial metric for understanding the efficiency and profitability of customer acquisition strategies, particularly in subscription-based or SaaS businesses.

Why its useful

Formula :

CAC = Total Cost of Sales and Marketing ÷ Number of New Customers Acquired

Total Cost of Sales and Marketing: Includes marketing spend (ads, campaigns, content creation), sales team salaries, software/tools, and any other customer acquisition-related costs.

Example : Netflix wants to calculate its CAC for a month.

Assumptions:

• Marketing Spend: $500 million (e.g., digital ads, promotions, etc.)
• Sales Team Salaries: $10 million
• Software/Tools: $5 million
• New Customers Acquired: 2 million

Total Cost: $500M + $10M + $5M = $515M

CAC: $515M ÷ 2M = $257.50 per customer

Interpreting CAC:

1. Compare CAC to CLV

• From the earlier Netflix CLV example, CLV = $540.
• CLV/CAC Ratio : 540÷257.50 ≈ 2.1
• A CLV/CAC ratio of 3:1 or higher is ideal, so Netflix may need to reduce CAC or increase retention.

2. Channel-Specific CAC:

• If Netflix runs campaigns on multiple platforms, calculating CAC per channel reveals the most cost-effective ones.

Ways to Reduce CAC

1. Optimize Marketing Spend: Focus on high-ROI channels (e.g., referral programs, organic traffic).
2. Improve Conversion Rates: Streamline the onboarding and purchasing processes.
3. Retarget Existing Customers: Upsell or cross-sell to reduce reliance on acquiring new customers.
4. Leverage Partnerships: Collaborate with complementary brands to access new customers at a lower cost.

How CAC is connected to CLV

The CLV/CAC ratio is the primary metric that highlights how efficiently a business acquires customers and how profitable those customers are over time.

CLV/CAC Ratio = Customer Lifetime Value ÷ Customer Acquisition Cost

Example of CLV/CAC Connection

Scenario: A SaaS Product (e.g., Netflix)

1. CLV: $540 (calculated previously)
2. CAC: $257.50 (calculated previously)
3. CLV/CAC Ratio: 540 ÷ 257.50 ≈ 2.1

Interpretation:

• Netflix earns $2.10 for every $1 spent on acquiring a customer.
• While the ratio is decent, Netflix should aim to:
  • Increase CLV by improving retention (e.g., reducing churn or upselling).
  • Decrease CAC by optimizing marketing spend.

4. Churn rate

Definition : Churn Rate measures the percentage of customers or subscribers who stop using a product or service over a given time period. It's a critical metric for subscription-based businesses (like SaaS or streaming services) because it directly impacts revenue, growth, and profitability.

Why its useful

Formula :

Churn Rate = (Customers Lost During a Period ÷ Total Customers at the Start of the Period) × 100

Example : Netflix's Monthly Churn Rate

Assumptions:

1. Netflix starts January with 100,000 subscribers.
2. During January:
   • 5,000 subscribers cancel their subscriptions.
   • 10,000 new subscribers join.
3. Total at the end of January = 105,000.

Churn Rate Calculation:

Churn Rate = (Customers Lost ÷ Customers at Start) × 100
 = (5,000 ÷ 100,000) × 100 
 = 5%

What Does It Imply?

1. Impact on Revenue:

   • A churn rate of 5% means that the company loses 5% of its revenue (or subscription base) unless it acquires new customers or retains the existing ones.
   • Example: If each customer pays $10/month, losing 5,000 customers means losing 5,000×10=$50,000.

2. Customer Retention:

   • A churn rate of 5% means 95% of customers stay loyal during the same period.
   • Higher churn rates (e.g., 10%) could indicate issues like dissatisfaction or strong competition.

3. Customer Lifespan:

   • Churn rate is inversely related to customer lifespan.
   • For a churn rate of 5%, the average customer stays for `1 ÷ 0.05 = 20 = 20 months.

4. Sustainability:

   • If the company acquires fewer customers than it loses (e.g., gains 3,000 but loses 5,000), its user base shrinks.

A 5% churn rate may be considered good or bad depending on the industry:

• SaaS or Subscription Businesses: Aim for churn rates below 3%-5% monthly.

• Mobile Apps: Higher churn (e.g., 10%-20%) may be common due to casual usage.

• Telecom: Monthly churn below 2% is desirable.

Strategies to Reduce Churn

• Improve Customer Onboarding
• Enhance Customer Support
• Offer Loyalty Programs
• Analyze Customer Behavior
• Implement Feedback Loops

5. Retention rate

Definition : Retention Rate measures the percentage of customers who continue to use a product or service over a specific time period. It’s the opposite of churn rate and indicates customer loyalty, satisfaction, and the overall health of a business.

Why Retention Rate matters

Formula :

Example :

Example: Retention Rate for Netflix

Scenario:

1. Customers at Start of Month: 100,000
2. New Customers Acquired: 20,000
3. Customers at End of Month: 110,000

Apply the Formula

Retention Rate = (110,000-20,000)÷100,000 * 100
Retention Rate = (90,000)÷100,000 * 100
Retention Rate = 90%

What does 90% Retention Rate means

• Netflix retained 90% of its existing customers during the month.
• 10% churned, meaning they canceled their subscriptions.
• If retention remains high, it ensures steady recurring revenue and a growing customer base.

Retention Strategies

To increase retention rate, companies can:

• Improve Onboarding: Ensure new customers experience value quickly.
• Engage with Personalization: Offer recommendations based on user behavior (e.g., Netflix suggests shows based on past viewing).
• Provide Exceptional Support: Quickly address issues to keep customers satisfied.
• Introduce Loyalty Rewards: Offer discounts or perks for long-term customers.
• Monitor Engagement: Identify and re-engage inactive customers with reminders or offers.

6. BDFU framework

BDFU is used in multiple contexts depending on the industry, framework, or company focus. There are 2 variations based on the context

6.1 Breadth, Depth, Frequency, Usage

Context: This version is used in engagement and feature adoption analysis, helping teams evaluate the extent and intensity of product usage.

Key Goal: Measure how users interact with the product in terms of the variety of features (breadth), how deeply they engage with specific features (depth), how often they use the product (frequency), and overall engagement (usage).

Hence here BDFU is broader and focuses on overall engagement trends.

6.2 Breakage, Dormancy, Failure, Usage

Context: This version is commonly used in retention and user lifecycle analysis, particularly in SaaS or subscription businesses. It focuses on identifying points where users drop off or fail to engage.

Key Goal: Understand where users struggle or disengage (breakage, dormancy, failure) and drive them toward active engagement (usage).

Thus,this version focuses on user retention and lifecycle bottlenecks.

7. Feature Adoption & Retention rate

Definition : Feature adoption measures how well a specific feature in a product is being discovered, used, and integrated into users' regular workflows. It evaluates whether users are realizing the intended value of the feature.

Why its useful

Formula : Adoption Rate is the percentage of users who start using a specific feature out of the total user base.

Adoption Rate = (Number of Users Who Used the Feature ÷ Total Users) × 100

Example : In a trading app like Zerodha, if 1,000 out of 10,000 users use a new charting tool, the adoption rate is

= 1,000÷10,000×100
= 10%

Similarly Drop-Off Rate = (Users Who Abandon the Feature ÷ Total Users Who Tried the Feature) × 100

Retention Metric measures how well a product or feature keeps users engaged and coming back over time. It’s critical for long-term growth and customer loyalty.

Formula :

Retention rate = (UsersatEnofPeriod - NewUsers) ÷ UsersatStartofPeriod * 100

Example : In Zerodha, if 10,000 users started using a feature in January and 8,000 continue in February (with 1,000 new users joining in February) ,then Retention rate is

Retention rate = (UsersatEnofPeriod - NewUsers) ÷ UsersatStartofPeriod * 100
= (8,000 - 1,000) ÷ 10,000 * 100
= 7000 ÷ 10,000 * 100
= 0.7 *100
= 70.0

Hence the retention rate is 70% .

Relationship Between Feature Adoption and Retention

• Adoption Drives Retention:

  • If users adopt a feature and find value, they’re more likely to stay engaged and loyal to the product.
  • Example: In a SaaS product, if users adopt an advanced reporting tool, it enhances their workflow, increasing their likelihood to retain.

• Retention Provides Feedback on Adoption:

  • High retention of users who adopt a feature indicates success.
  • Low retention signals the feature might not be delivering sufficient value.

8. Product stickiness

Definition : Product stickiness refers to how well a product retains users by becoming an integral part of their daily routines or workflows. A "sticky" product is one that users rely on frequently, find value in, and are unlikely to abandon. High product stickiness typically leads to increased retention rates, engagement, and customer lifetime value (CLV).

Why its useful

Formula :

  Stickiness Ratio = Daily Active Users (DAU) ÷ Monthly Active Users (MAU)

Example :If Netflix has 10M DAU and 50M MAU ,then

Stickiness Ratio =DAU/MAU
 = (10M ÷ 50M) × 100 
 = 20%

Ideal Benchmark: 20%-30% is considered good for most products; higher ratios indicate greater stickiness.

A high retention rate is a sign of stickiness, as users continue returning to the product over time.

Case Study: Lets study an example of great stickiness product Zerodha, India’s leading stockbroking platform, is an excellent example of a sticky product in the financial and investment sector.

1. Breadth of Offerings

• What It Means: Zerodha offers a wide range of features like equity trading, mutual funds, options, futures, and even goal-based investing through their platform Coin.
• Why It's Sticky:
  • Users can fulfill multiple financial needs (trading, investing, goal planning) on a single platform.
  • This reduces the need to switch to competitors or use multiple apps.
• Example: A trader uses Zerodha's Kite for intraday trading, while also using Coin for SIPs in mutual funds.

2. Depth of Engagement

• What It Means: Zerodha deeply engages users with its intuitive and efficient trading tools like Kite and Console for advanced analytics.
• Why It's Sticky:
  • Kite provides advanced charting tools and real-time data, making it indispensable for active traders.
  • The Console dashboard gives a deep breakdown of portfolio performance, P&L reports, and tax reports.
• Example: A trader who starts using Kite for its superior charting tools is likely to stick because of its smooth UX and comprehensive features.

3. Frequency of Usage

• What It Means: Zerodha caters to traders and investors, ensuring frequent engagement.
• Why It's Sticky:
  • Daily Traders: Intraday traders use the platform multiple times a day for placing trades and analyzing market movements.
  • Long-Term Investors: SIP reminders and market updates encourage periodic interactions.
• Example: A day trader logs into Kite every morning to analyze charts and place trades, while an investor checks their SIP performance monthly through Coin.

4. Usage and Value Delivery

• What It Means: Zerodha consistently delivers value by offering low-cost services, educational resources, and seamless technology.
• Why It's Sticky:
  • Low brokerage fees make it cost-effective for traders and investors.
  • Educational initiatives like Varsity help users learn about stock markets and investing, increasing their trust and reliance on Zerodha.
• Example: A first-time investor learns the basics of stock markets through Varsity, opens a Zerodha account, and sticks with the platform due to its low fees and value-added tools.

Why Zerodha is a Sticky Product

1. Low Brokerage and Transparent Pricing

   • Fixed brokerage of ₹20 per trade makes Zerodha an affordable choice for both small and large investors.
   • Transparency in pricing builds user trust, reducing the likelihood of churn.

2. User-Centric Technology

   • Kite's sleek, user-friendly design ensures ease of use, even for first-time investors.
   • Tools like Streak (for algo trading) and Sensibull (for options trading) cater to advanced users.

3. Personalization

   • Zerodha's platform provides personalized insights through Console, including P&L summaries, tax reports, and market notifications.

4. Community and Education

   • Educational content through Varsity and engagement via community forums like TradingQnA helps users feel supported and part of a larger ecosystem.

5. Habit-Forming Features

   • Regular notifications for SIPs, stock updates, and trade alerts encourage frequent usage.
   • Investors and traders become reliant on the platform for their day-to-day financial activities.

9. NPS

Definition : Net Promoter Scoreis a widely used metric to measure customer loyalty and satisfaction by assessing how likely users are to recommend a product or service to others. It provides insights into customer sentiment and helps businesses identify promoters, detractors, and opportunities for improvement.

Why should Team track NPS

Formula :

NPS = % Promoters − % Detractors

Scoring Categories:

• Promoters (9–10): Loyal customers who actively recommend the product and drive growth.
• Passives (7–8): Satisfied but unenthusiastic customers who may switch to competitors.
• Detractors (0–6): Unhappy customers who are unlikely to recommend the product and may discourage others.

NPS ranges from -10 to +10.

Example : NPS in Practice

Problem: Spotify wanted to understand how satisfied its users were and identify areas to improve.

Approach:

1. Sent an NPS survey to users asking: “How likely are you to recommend Spotify to a friend?”

2. Collected feedback, segmenting users into promoters, passives, and detractors.

3. Insights:

   • Promoters loved personalized playlists like “Discover Weekly.”
   • Detractors cited app crashes and missing features like lyrics.

4. Actions:

   • Improved app stability and introduced real-time lyrics.
   • Rewarded promoters with early access to new features.

Result: NPS score improved over time, correlating with increased user retention and growth.

10. Mission Metric

Definition : Customer Mission Metric is a metric that tracks how effectively a product helps customers achieve their core objectives or "mission" when using the product.

Unlike traditional business metrics (e.g., revenue or churn), this focuses specifically on measuring the success rate of the customer’s intended goal.It’s a customer-centric KPI that evaluates how well the product aligns with and delivers on customer needs and expectations.

Why its matters

Examples of Customer Mission Metrics

1. Zerodha (Trading App)

   • Metric: Percentage of users who successfully execute trades without errors or drop-offs.
   • Customer Mission: Enabling seamless and informed stock trading.

2. Uber (Ride-Hailing App)

   • Metric: Percentage of rides completed without delays or cancellations.
   • Customer Mission: Ensuring users get to their destinations quickly and reliably.

3. Amazon (E-Commerce)

   • Metric: Percentage of orders delivered on time and in good condition.
   • Customer Mission: Helping users receive desired products quickly and conveniently.

How to Measure Customer Mission Metrics

1. Understand the Customer Journey:

   • Map the steps users take to achieve their goals.
   • Identify points where success or failure occurs.

2. Define Success Criteria:

   • Success should be measurable.
   • Example: For a project management tool, success could be completing a task or achieving a project milestone.

3. Collect Data:

   • Use analytics, surveys, and feedback to track outcomes.
   • Example: Ask users if they successfully achieved their goals after using the product.

4. Analyze Success and Failure Rates:

   • Identify the percentage of users achieving their goals.
   • Analyze failure points to make improvements.

11. North Star Metric

Definition :The North Star Metric is a single, overarching metric that represents the core value your product delivers to users and aligns your team around a shared goal.

It focuses on the desired customer outcome rather than business outcomes like revenue or profit, driving long-term growth and user satisfaction.

Why its matters

Examples of North Star Metrics by Industry

1. Streaming Platforms (e.g., Netflix, Spotify)

• NSM: Hours of content consumed per user per week.
• Why: Reflects user engagement and satisfaction with the content library.

2. E-Commerce Platforms (e.g., Amazon)

• NSM: Number of purchases per active customer per month.
• Why: Indicates customer satisfaction, repeat usage, and convenience.

3. SaaS Tools (e.g., Slack, Notion)

• NSM: Number of messages sent per user per day (Slack).
• Why: Shows how integral the tool is to users' workflows.

4. Fintech Apps (e.g., Zerodha, Robinhood)

• NSM: Number of trades executed per user per month.
• Why: Tracks how often users achieve their trading goals through the platform.

5. Fitness Apps (e.g., Strava, Fitbit)

• NSM: Number of active days logged per user per month.
• Why: Encourages users to stay consistent with fitness goals.

Real time example of how Zerodha, or a similar trading platform, can define and use a North Star Metric (NSM) to align its teams, measure success, and drive growth:

Step 1: Identify the Core Value Proposition

What does Zerodha deliver to its users?

• Zerodha helps users make informed trades and invest seamlessly in stocks, mutual funds, and other financial instruments.
• The core value is enabling users to successfully participate in financial markets and grow their wealth.

Step 2: Define Zerodha's North Star Metric

Potential NSM:

• "Number of Successful Trades Executed Per User Per Month"
• Why?
• It reflects user engagement (active trading).
• It aligns with the business goal of increasing trading volumes, which directly impacts Zerodha's brokerage revenue.
• Successful trades indicate that users find the platform reliable, efficient, and valuable.

Step 3: Break Down the NSM into Contributing Metrics

The NSM can be supported by secondary metrics that track different parts of the user journey

1. User Onboarding Metrics:

• Metric: Percentage of new users completing account setup (e.g., KYC completion).
• Why It Matters: Ensures more users are onboarded and ready to trade.

2. Feature Adoption Metrics:

• Metric: Percentage of users using advanced tools like charting, Basket Orders, or Streak (algo trading).
• Why It Matters: Users adopting these tools are more likely to execute trades.

3. Retention Metrics:

• Metric: Monthly Active Traders (MAT).
• Why It Matters: Higher retention shows that users consistently engage with the platform.

4. Transaction Success Rate:

• Metric: Percentage of trades executed without errors.
• Why It Matters: A seamless trading experience builds trust and loyalty.

5. Revenue Metrics:

• Metric: Average brokerage earned per user per month.
• Why It Matters: Higher trading activity aligns with Zerodha's revenue growth.

Step 4: How to Use the North Star Metric

1. Align Teams Around the NSM:

   • Product Team:
     • Focus on improving tools (e.g., charting, data analytics) that help users trade confidently.
   • Marketing Team:
     • Target campaigns to attract active traders who align with the NSM.
   • Engineering Team:
     • Optimize system performance to ensure trade execution is fast and error-free.

2. Analyze User Behavior:

   • Identify user segments:
     • High-value traders: Focus on advanced tools.
     • Infrequent users: Encourage engagement through education or reminders.
   • Use behavioral data to see why some users aren't trading.

3. Improve Key Features to Drive the NSM:

   • Simplify onboarding to reduce friction for new users.
   • Provide better educational resources (e.g., Varsity or webinars) to help users make informed trades.
   • Add personalization, like recommending stocks or funds based on user preferences.

4. Track and Iterate:

   • Regularly monitor the NSM and contributing metrics.
   • Use A/B testing to validate changes that impact the NSM (e.g., introducing new trading features or simplifying workflows).