You Need to Know these Metrics
The life of a Product Manager is not easy, you are always tasked with keeping your users happy, stakeholders happy, management team happy, marketing and tech team happy, and CSE team happy and even after this if you have any life left you need to keep your family happy. To keep all those folks happy you always need to monitor some things from your product so you know that your product is on the right track and everything is in check.
As a Product Manager (PM), being aware of the right metrics is important for effectively measuring and tracking the progress of your product. Following are some of the metrics that a Product Manager should be aware of:
1. Key Performance Indicators (KPIs)
KPIs are high-level metrics and your product’s overall goals are tied up to them. Every product/company has their own set of KPIs which varies based on the nature of the product. Some examples of the metrics are Revenue, Customer Acquisition, Conversion Rate, Retention Rate, etc. which will be covered later in the blog.
2. Engagement Metrics
These metrics help you to understand how actively your users are interacting with your product. Some examples of these Metrics are Daily Active Users(DAU), Weekly Active Users(WAU), Monthly Active Users(MAU), time spent by the user on the app, user’s session length, etc.
Following are a few of the engagement metrics that you should be aware of,
i. Daily Active Users (DAU):
The number of unique users who visit/perform an event/actively engage with the app on a daily basis. In simple terms how many users were present on your application today, that is your app’s DAU.
ii. Weekly Active Users (WAU):
Similar to DAU and measured on a weekly basis.
iii. Monthly Active Users (MAU):
Similar to DAU and measured on a monthly basis. It gives a larger picture of user engagement with your app over a longer period.
iv. Session Length:
The average time spent by the users on your app within each app session(app launched till the time the user closes the application). Longer session lengths often indicate higher engagement but not always.
v. Screen Views per Session:
The number of screens or pages viewed by users during a single app session. The higher the screen views higher the engagement with the app’s content, as the user is exploring the application more.
vi. In-App Interactions:
The frequency of user interactions with the in-app elements, can be features, buttons or anything. More interactions mean higher user engagement.
vii. Push Notification Click-Through Rate:
The percentage of users who interact with your app’s push notifications. Using the push notification channel effectively can increase your app’s engagement drastically.
viii. User Feedback and Ratings:
Monitoring user reviews, ratings, and feedback can provide valuable insights into how engaged users are with the app and their overall satisfaction with your product.
3. Retention Metrics
Retention in simple words is nothing but how repeatedly a user is engaging with your product. Some metrics help you with measuring retention of your product such as churn rate, retention rate, etc.
i. Retention Rate:
The retention rate helps you understand the percentage of users who continue to use your app over a specific period. Retention can be calculated on a daily basis, weekly basis, monthly basis or yearly basis. A 30-day retention rate means the percentage of users who return to the app at least once within 30 days after their first interaction with the app(which can be registration, installation, or purchases).
ii. Churn Rate:
This indicates the percentage of users who stop using the app over a specific period. A high churn rate indicates that many users are leaving the app, which can/should be a cause for concern.
iii. Cohort Analysis:
These are groups of users based on a specific time frame or can be of the same behaviour, such as the month they first used the app, or first to adopt a feature. It helps track how different groups of users behave, providing insights into user retention trends and the app’s long-term performance.
iv. Returning Users vs. New Users:
This metric compares the number of returning users to new users. A balanced ratio is desirable but can vary based on the nature of the app, it indicates a healthy combination of new acquisitions and retention efforts.
v. Reactivation Rate:
Reactivation rate measures the percentage of inactive users who return to the app after a specific period. It helps you understand how effective your retention or re-engagement campaigns were.
We also have Time Between Sessions, Feature-Specific Retention, and User Engagement Over Time these are self-explanatory terms
4. Conversion Metrics
Conversion metrics help you to understand whether a user has completed an important event on your product that has now made them your customer. Metrics here can be click-through rate(CTR), sign-up rate, conversion rate, etc.
i. Click-Through Rate (CTR):
Commonly used in marketing campaigns to understand the effectiveness of the ads and ad placements. CTR is nothing but something used to measure the percentage of users who clicked on a banner ad or a button any call-to-action or even a link.
ii. Sign-Up Rate:
This helps you understand how many of your users have registered on the platform after visiting your website or after downloading the application. It helps you understand is your onboarding process is effective or not.
iii. Activation Rate:
Activation rate helps you understand whether what per cent of your users after completion of the registration has performed an action that deems them as activated users. This action can vary from app to app. For example, in the case of a movie ticket booking app, if a user registers and checks out a movie or bookmarked a movie, etc.
iv. Conversion Rate:
Conversion rate is goal or action dependent, it measures the percentage of users who have performed a key action on the platform. It can be as simple as making a purchase. In the case of our previous example of a movie ticket booking app, a converted user can be someone who books a ticket.
v. Trial-to-Paid Conversion Rate:
Percentage of users who converted to paid model that you provide from a freemium model on your app.
vi. Upgrade Rate:
This is a metric that is used by apps that provide different tiers of subscriptions/service levels. The upgrade rate helps to track the percentage of users who have upgraded to a higher tier from a lower tier.
There are a few other metrics such as Form Completion Rates, Lead Customer Conversion Rates, and In-App Purchases.
5. Customer Satisfaction Metrics
The success of your product totally depends on your customer’s satisfaction. We have metrics that help a Product Owner to understand customers’ sentiments for the product, these include Net Promoter Score(NPS), App Store or Play Store ratings, customer feedback scores, etc.
i. Customer Satisfaction Score (CSAT):
CSAT is rather a simple metric that usually asks customers to rate their satisfaction on a scale (e.g., 1–5 or 1–10) with a specific product. The average score then represents the overall satisfaction level w.r.t the product.
ii. Net Promoter Score (NPS):
NPS measures customer loyalty and the chances of users recommending or referring a product or service to their friends or colleagues. It asks users to rate the likelihood of recommending on a scale of 0 to 10. Based on their responses, customers are categorized into Promoters (scores 9–10), Neutrals (scores 7–8), and Skeptics (scores 0–6). The NPS is then calculated as the percentage of Promoters minus the percentage of Detractors.
iii. Customer Effort Score (CES):
It usually asks customers to rate the level of effort required to accomplish a task or perform an action. Lower the CES scores better the customer experience.
Other ways to track customer satisfaction metrics are Time Taken to Resolve Customer Complaints, Online Reviews and Ratings.
6. Acquisition Metrics
Acquisition means your product acquiring users through various sources. Users can land on your product via organic search, paid advertising, social media, etc.
i. Cost per Acquisition (CPA):
CPA measures the average cost of acquiring a new customer through marketing campaigns. It is calculated by dividing the total cost of acquisition (e.g., advertising costs, sales team expenses) by the number of new customers acquired from that specific campaign.
ii. Customer Acquisition Cost (CAC):
CAC is similar to CPA but includes all costs related to acquiring a new customer. It helps you understand the overall amount required/spent to gain new customers.
iii. Return on Advertising Spend (ROAS):
ROAS determines the revenue generated by users acquired from a specific advertising campaign or channel compared to the cost of that campaign.
iv. Return on Investment (ROI):
ROI measures the returns generated from an investment, such as a marketing campaign. For acquisition efforts, it indicates the revenue generated compared to the investment done to acquire new customers.
7. Funnel Metrics
A complete product irrespective of its nature is divided into funnels. Funnels are nothing but different stages of the product. These metrics help you understand the user drop-offs at each stage of the product flow.
i. User Funnel Conversion Rate:
The rate at which users complete a set of desired actions or tasks within the app, such as sign-ups, purchases, etc.
ii. Funnel Drop-Off Rates:
These metrics track the percentage of potential users or existing users that drop out of the funnel at various stages, indicating potential areas of concern or improvement.
8. Revenue Metrics
Revenue as the name suggests means the metrics related to your product’s income. Some examples of revenue metrics are Average Revenue Per User(ARPU), Average Revenue Per Paid User(ARPPU), Customer Life Time Value(CLTV), Cost Per Acquisition(CPA), etc.
i. Revenue:
The total amount of money generated during a specific period. It shows how well the business is doing.
ii. Gross Revenue:
The total revenue generated before deducting any expenses or costs associated with the product.
iii. Net Revenue:
Commonly known as revenue after deductions, it is the revenue remaining after subtracting discounts, spends, and other expenses from the gross revenue.
iv. Average Revenue Per User (ARPU):
The average revenue generated per user. It helps understand the revenue generation from individual users.
v. Average Transaction Value (ATV):
The average value of each transaction made during a specific period.
v. Customer Lifetime Value (CLV):
CLV represents the revenue generated by a customer over their entire time on the product.
vii. Monthly Recurring Revenue (MRR):
The recurring revenue generated from a product on a monthly basis.
viii. Annual Recurring Revenue (ARR):
Similar to MRR, it calculates the recurring revenue generated from a product on an annual basis.
ix. Upsell and Cross-sell Revenue:
Extra income from selling upgraded products (upsell) or related products (cross-sell) to current customers.
9. Abandonment Rate
Users at various stages of the application might abandon specific processes, tasks or events. One common example is cart abandonment in e-commerce.
Cart Abandonment Rate:
This is a metric highly used by the e-commerce platform. This metric helps you to understand and track the percentage of users who dropped in between the completion of the full journey or action. When it comes to e-commerce it can be used to understand, users who add items to their cart but do not complete the purchase
10. Error and Bugs
As name errors and bugs are issues that are faced by the users which leads to bad experiences and eventually lead to user drop-offs. These metrics help you understand the stability and performance of the product, this can be the number of bugs, avg. response time, error rates, etc.
i. Bug Count:
The total number of identified and recorded bugs in the product. Tracking the bug count helps in understanding the scope of issues that need to be addressed.
ii. Bug Open/Closed Ratio:
The ratio of open bugs to closed bugs.
iii. Bug Fix Rate:
The rate at which bugs are fixed. It measures the efficiency of the development and quality assurance teams.
iv. Mean Time to Detect (MTTD):
The average time taken to detect a bug from the minute it was introduced into the system.
v. Mean Time to Repair (MTTR):
The average time taken to fix and resolve a reported bug.