Iterate AI
Dec 18, 2024
Every decision in product management needs to be supported by numbers and insights– be it a product's features or user experience, or growth strategies
This is where product management metrics come into play.
Metrics are an objective way to assess the performance of a product and features. So when PMs back their suggestions and decisions with metrics, it is not considered biased.
In this blog, we'll explore important metrics used in product management today. Let's dive in!
Product Adoption Rate
What it is:
It measures how quickly new users are adopting a product after the launch. It helps you understand the initial product-market fit and growth potential. You can also check adoption rate for features as well (more on this under Feature Usage Rate)
How to calculate product adoption rate:
Product Adoption Rate = New Users/Total Target Market × 100
Example of product adoption rate:
Let’s say 10,000 users download your product. However, only 1000 users completed onboarding and did the first task (which you consider a parameter for adoption). Then this is the calculation:
1000 / 10000 x 100 =10%
Read: Adoption rate - an in-depth guide for PMs
Customer Retention Rate
What it is:
Retention Rate (also called as stickiness of the product) measures how well a product keeps its users over time. It tells you how many users continue using the product after their first experience which in turn evaluates user satisfaction of your product.
How to calculate customer retention rate:
Retention Rate = Customers at the End of Period / Customers at the Start of Period×100
Example of customer retention rate:
If you start with 500 users in January and end the month with 450, your retention rate is:
450/500 × 100 = 90%
High retention rates means users are finding long-term utility and it also reduces customer acquisition costs over time.
Churn Rate
What it is:
Churn Rate measures the percentage of customers who stop using your product over a certain period. It's the opposite of retention rate and is used to check if users are disengaging from your product after using it.
How to calculate churn rate:
Churn Rate = Customers Lost/ Customers at the Start of Period × 100
Example of churn rate:
If you have 1,000 customers at the start of the month and 50 customers cancel their subscriptions, your churn rate is:
50/1000 × 100 = 5%
The churn can occur because of poor user experience, customer support just because there are better competitors or the trend died. Identifying the reason and reducing it makes sustainable growth possible.
Net Promoter Score (NPS)
What it is:
NPS measures customer loyalty by asking a simple question: "How likely are you to recommend our product to a friend or colleague?" The scale is 1 to 10 and your final score ranges from -100 to +100. Your final score is based on the percentage of promoters (score 9-10) and detractors (score 0-6).
How to calculate NPS:
NPS = Percentage of Promoters − Percentage of Detractors
Example of NPS:
If 60% of your users are promoters, 10% are detractors, the NPS would be:
60% − 10% = 50
A high NPS indicates that users are likely to advocate for your product, which can lead to organic growth. This also reduced the customer acquisition cost eventually.
Customer Lifetime Value (CLV)
What it is:
CLV predicts the total revenue a business can expect from a customer over their entire relationship with the product. It helps PMs understand the long-term value of retaining customers and investing in customer satisfaction.
How to calculate customer lifetime value:
CLV = Average Revenue per Customer × Average Customer Lifespan
Example of customer lifetime value:
If the average revenue per customer is $100 per month, and the average customer lifespan is 12 months, the CLV is:
100 × 12 = $1,200
Why it matters:
CLV is crucial for budgeting, as it helps you understand the return on investment for customer acquisition efforts. By maximizing CLV, you can focus on strategies that enhance customer satisfaction and retention.
Active Users (DAU/MAU)
What it is:
This metric measures the number of unique users who engage with the product on a daily (DAU) or monthly (MAU) basis. You can use MAU (Monthly Active Users) and DAU(Daily active users) to track engagement and understand user behavior on a regular basis to find patterns.
DAU = Number of unique users on a given day
MAU = Number of unique users over a month
Example of DAU and MAU ratio:
If your app has 5,000 unique daily users and 20,000 unique monthly users, the DAU/MAU ratio would be:
5,000 / 20,000 = 0.25
A higher DAU/MAU ratio indicates a highly engaged user base, while a low ratio suggests users might not be returning frequently enough. This helps you figure out how to make your product more engaging.
Feature Usage Rate
What it is:
Feature Usage Rate tracks how frequently specific features of a product are used by customers. It helps you evaluate the success of new features and whether users are deriving value from them.
How to calculate feature usage rate:
Feature Usage Rate = Users Using Feature / Total Users × 100
Example feature usage rate:
If 500 out of 1,000 users are actively using a new feature in your app, the feature usage rate would be:
5001,000 × 100 = 50%
A low feature usage can mean it is hard to discover, not useful, or poorly designed, etc. You can also calculate feature adoption by your existing users. To calculate divide users using the feature / total users exposed to the feature x 100
Time to Market
What it is:
Time to Market (TTM) refers to the time it takes for a product or feature to go from the concept phase to being available to customers. It's a critical metric for assessing how quickly a team can execute and deliver value.
How to calculate time to market:
Time to Market = Launch Date − Start Date
Example of time to market:
If you start developing a new feature on January 1st and release it on March 1st, the time to market is:
60 days
Reducing time to market means how quickly your company can cater to customer needs and market changes. It also accelerates learning and iteration cycles giving you an edge over your competitors.
Conversion Rate
What it is:
Conversion Rate tracks how effectively a product or feature converts users into paying customers or users who take a desired action. You have to have a specific action (e.g., signing up, making a purchase) that is considered as conversion to calculate.
How to calculate conversion rates:
Conversion Rate = Converted Users / Total Users × 100
Example of conversion rate:
If 200 out of 1,000 trial users convert to paying customers, the conversion rate would be:
200 / 1000 × 100 = 20%
Conversion rate optimization is very critical because when you can’t convert users to customers you are losing on the effort made to bring in the users. These users, if they are in need of the solution, will become customers of your competitors.
Low conversion can also indicate the users’ intent or need is not matched or met which means you have to work on your marketing strategy to bring the right ICP into product.
Bounce Rate
What it is:
Bounce Rate measures the percentage of visitors who leave your site or app after viewing only one page. It's a useful metric for evaluating how engaging your content or product is.
How to calculate bounce rate of a product:
Bounce Rate = Single Page Sessions / Total Sessions × 100
Example of bounce rate in a product:
If your app had 1,000 sessions in a month and 400 were single-page visits, the bounce rate would be:
400 / 1000×100 = 40%
A high bounce rate on a particular page can indicate the landing page isn't delivering the user's needs or the experience is confusing.
Set up product management metrics with Iterate AI
As a product manager, you should be on top of your metrics game. It is one of the biggest product manager responsibilities.
So why wait for your developer to code when you can do it yourself with Iterate AI? All you need to do is choose events to track, label them. Iterate AI generates the code for your dev to check before you implement it yourself.
Schedule a demo to learn how Iterate AI reduces PMs dependency on developers.