KPIs for Product Management: Identifying and tracking Key Performance Indicators
Key Performance Indicators (KPIs) for Product Management are specific metrics used to evaluate the success and progress of a product in various aspects. These KPIs help product managers to make informed decisions, track the performance of their product, and align their strategies with the overall business goals. Identifying and tracking the right KPIs is crucial for effective product management. Here are some common KPIs used in product management (Let's consider the example of our journal app and I've shown formulaes related to it.)
Customer Satisfaction (CSAT):
Explanation:
CSAT measures how satisfied customers are with your product. This is usually obtained through surveys asking customers to rate their satisfaction.
Formula:
(Number of satisfied customers / Total survey respondents) × 100.
Example:
After introducing a new feature in your journal app, like mood tracking, you survey users. If 80 out of 100 respondents say they're satisfied, your CSAT is (80/100) × 100 = 80%.
Net Promoter Score (NPS):
Explanation:
A metric that gauges customer loyalty by asking how likely customers are to recommend your product to others.
Formula:
(% of Promoters - % of Detractors) × 100.
Example:
If 50% of your app users are promoters (score 9-10) and 10% are detractors (score 0-6), NPS is (50% - 10%) × 100 = 40.
Churn Rate:
Explanation:
The percentage of customers who stop using your product over a given period. A lower churn rate indicates higher customer retention.
Formula:
(Number of customers at start of period - Number of customers at end of period) / Number of customers at start of period.
Example:
If you started the month with 1000 users and lost 50, churn rate is (1000-950) / 1000 = 5%.
Monthly Active Users (MAU) / Daily Active Users (DAU):
Explanation:
MAU and DAU measure the number of unique users who engage with your app on a daily or monthly basis.
Formula:
Count unique users daily or monthly.
Example:
If 5000 users open your journal app at least once in a month, your MAU is 5000.
Customer Acquisition Cost (CAC):
Explanation:
The total cost of acquiring a new customer, including marketing and sales expenses. It's crucial for understanding the profitability of acquiring new customers.
Formula:
Total Sales and Marketing costs / Number of new customers acquired.
Example:
If you spend $5000 on marketing in a month and acquire 1000 new users, CAC is $5000 / 1000 = $5 per user.
Lifetime Value (LTV):
Explanation:
Estimates the total revenue a business can expect from a single customer throughout their relationship with the product.
Formula:
Average revenue per user (ARPU) × Average customer lifespan.
Example:
If users spend $10 on average and stay for 12 months, LTV is $10 × 12 = $120.
Revenue Growth Rate:
Explanation:
Measures the rate at which the product's revenue is growing, an essential indicator of market acceptance and business scalability.
Formula:
(Current Period Revenue - Previous Period Revenue) / Previous Period Revenue × 100.
Example:
If last month's revenue was $10,000 and this month's is $12,000, growth rate is ($12,000 - $10,000) / $10,000 × 100 = 20%.
Conversion Rate:
Explanation:
The percentage of users who take a desired action (e.g., making a purchase, signing up for a trial). This indicates the effectiveness of the product in motivating user action.
Formula:
(Number of conversions / Total number of visitors) × 100.
Example:
If 500 out of 10,000 visitors subscribe to a premium feature, the conversion rate is (500/10,000) × 100 = 5%.
Time to Market:
Explanation:
The duration it takes to develop a product and bring it to market. Shorter times can be a competitive advantage.
Formula:
Date of release - Date of project start.
Example:
If you started developing a backup feature on January 1 and released it on March 1, the time to market is 2 months.
Feature Usage:
Explanation:
Tracks how often specific features of the product are used, indicating what's valuable to users.
Formula:
Number of times a feature is used / Total number of sessions.
Example:
If the mood tracking feature is used 1000 times in 5000 sessions, its usage rate is 1000/5000 = 20%.
Product Quality Metrics:
Explanation:
These could include the number of bugs or defects reported, downtime, and other quality-related metrics.
Formula:
Total number of reported issues / Total number of sessions.
Example:
If users report 50 bugs over 10,000 sessions, the bug rate is 50/10,000 = 0.5%.
Engagement Metrics:
Explanation:
This includes various metrics that measure how users interact with the product, such as session duration, pages visited, and user actions.
Formula:
Total duration of all sessions / Number of sessions.
Example:
If users spend 5000 hours in 2000 sessions, average session duration is 5000/2000 = 2.5 hours.
