Product management is an important part of the product development process. Product managers are responsible for maximizing customer value, and they need to be able to understand their customers in order to do this.
Product manager analytics helps them better understand how their products are being used so that they can make more informed decisions about future iterations and releases.
In this post, we'll go over 19 different great product manager analytics metrics and tools that you should know about if you're aiming for a position of responsibility at your company.
Let's dive in.
Table of Contents
What is product management analytics?
Product management analytics involves understanding the behavior of your customers and how they use your product. Product strategists need to have an awareness of how their user base is using their products in order to make more informed decisions about future releases, iterations, and features.
Some of the metrics they need to analyze are:
- Active users per day
- Average time spent on site per visit (minutes)
- Bounce rate (%)
- Conversion rates by source/medium (% visits converting into purchases)
Product managers will also want to study these metrics for specific marketing campaigns in order to see how effective they were.
PM analytics can help companies make better decisions about budget allocations as well as which features should be developed next based on user behavior trends.
Product manager analytics
Product manager analytics are divided into 6 different categories:
This refers to the metrics that measure engagement in the product. This includes active users per day, average time spent on site per visit (minutes), and bounce rate (% visits converting into purchases).
Product analytics helps you understand how people are using your product or service to determine what features should be developed next based on user behavior trends. These include conversion rates by source/medium (% visits converting into purchases) and which marketing campaigns were most effective at driving conversions.
Retention refers to the metrics that measure the percentage of people who return to use your product or service. This includes acquisition (signups per day) and retention rate (% visits converting into subsequent purchases).
Product analytics help you understand how engaged customers are with your product, including what features they're using most often and whether they've converted from free users to paid ones.
Activation is a measure of how many users have started using your product or service for the first time. This includes both activation rate (% visits converting into free-to-paid conversions) and conversion (signups per day).
Reach/acquisition refers to the number of people who are exposed to your product or service. This includes visitors, signups, and conversions (signups per day).
These analytics help you know how the different acquisition channels are performing and whether you need any additional channels.
Transaction/monetization refers to the number of purchases made with your product or service. This includes transactions and revenue per day.
Business-specific analytics help you track the performance of your business in relation to a specific goal. They can include conversion by product, revenue by location, and more.
These analytics will vary according to your industry and goals.
Product manager analytics metrics
Product managers will spend a lot of time focusing on metrics in order to maximize conversions. This includes the following:
1. Engagement metrics:
Average daily active users (ADAU)
This metric focuses on the number of active users on a given day. It should be tracked in order to understand your product's performance and if it is going up or down over time.
Time spent on-site or app
This metric is the amount of time an average user spends on your product or app. The key to this measurement is understanding how close a person gets to completing their goal before they leave. For example, if you are measuring TOS on a mobile phone, it would be important to know whether someone left because they couldn't find what they wanted, or because their battery died.
Pages viewed per visit
This metric is the number of pages an average user views on your site or app in a single session. It should be measured because it indicates how long someone spends browsing through content before they leave. Similarly, if you are measuring TOS on a mobile phone, this would indicate whether people are going to multiple websites and apps, or just sticking to one.
Session per user
This is the number of sessions a user has during their visit. This metric can be valuable for understanding what content people are most interested in consuming.
-Shopping cart or checkout abandonment
An important metric for e-commerce stores, shopping cart abandonment is the number of people who add an item to their cart but do not go through with a purchase. If your company has a high rate of abandoned carts, you may want to consider using discounts or incentives to lock in these potential buyers.
2. Retention metrics:
Retention or churn rate
This is the percentage of customers that continued to use your product after a designated time period. The lower this number, the better it is for your company.
For example, the churn rate on a monthly basis shows you how many people are still using the service each month in relation to those who stopped using it over the course of the month.
This is a measurement of how long your customers typically stay with your product. It's calculated by dividing the total number of days that all your users have been active on the site, including both current and non-active members, by the total number of days in one year.
The lower this percentage (i.e., more stickiness) the better your product is.
This metric is similar to the stickiness measurement, but instead of counting all members who are active on your site for a full year, it only counts those that have been active in the last N days.
3. Activation metrics:
Percentage of activated users
This is the percentage of users who have registered for your product or service and then used it at least once. It's important to measure this because it's the most basic measure of customer engagement.
Number of activations
This is the number of people who have activated your product or service. Unlike the percentage of activated users metric, this metric focuses on counting the raw number of people who have activated your product or service.
Percentage of inactive users
This is the percentage of registered users who haven't been active in a certain amount of time (say, 30 days). This can indicate that your product might need some work and needs to be made more compelling or interesting. You could also look at this as a measure of how well your product is doing because if the percentage number is low, it means that a lot of people are using your service.
Number of activation funnel steps completed by an average user
This is how many steps an average user completes in the activation funnel, which will help you determine if your funnel needs tweaking or not. Product managers will use this metric to see if users are getting lost in the funnel and need help or not.
4. Reach/Acquisition metrics:
This is how many paid subscribers you have. This number will help you determine the viability of your business and whether or not this product should stay on the market. If this is low, then it might be time to overhaul your pricing plan or a new strategy in general
3-month active users
This is how many active users you have for a three-month period. This number will help you determine whether the product or service is worth keeping on the market
You may also want to consider other metrics such as bounce rate, time spent per session, and page views in order to get a more accurate picture of your audience's behavior during the 3-month period.
Page or ad impressions
Page or ad impressions are how many times your page was seen by a visitor. This metric in particular is important because it can help you determine your advertising and marketing strategy. For instance, if this number is low then a new ad campaign might be necessary in order to increase the number of page or ad impressions.
Monthly recurring revenue (MRR)
Monthly recurring revenue (MRR) is the amount of money that you receive from customers on a monthly basis. Measuring this metric is important because it tells you how much revenue your business has the potential to generate.
Average revenue per daily active user (ARPDAU)
The average revenue per daily active user (ARPDAU) is the amount of money that a company earns from its users on a monthly basis. This metric can help you to determine how much your business has the potential to generate in terms of revenue.
Average return on ad spend (ROAS)
The average return on ad spend (ROAS) is the amount of money that a company earns from its advertising expenses. This metric can tell you how much your business has the potential to earn as far as ROI goes.
Customer lifetime value (CLV)
The customer lifetime value (CLV) is the total amount of money that a company would generate from one of their customers over the course of their relationship with them.
This metric can help product managers to determine the potential for growth.
Ad click-through rate (CTR)
The ad click-through rate (CTR) is the number of times that an advertisement was clicked on. This metric can help to determine how successful a particular advertising campaign has been and what areas might need improvement.
Cost per acquisition (CPA)
The cost per acquisition (CPA) is the amount of money a company spends on advertising to acquire one customer. This metric can help product managers determine how much they are spending in order to get new customers.
How can product analytics help a company?
The analytics can help a company to determine whether or not they are meeting the requirements of customers, and how much time is being spent on developing features. Product managers will need to have basic PM skills to see what needs improving in their products by using these metrics for analysis.
Also, some of the metrics can be used to measure customer satisfaction. For example, a product manager will know how many customers are frustrated if they see that their app crashes too often and needs improvements in this area.
All these metrics allow for managers to make decisions on which features need improvement, what type of advertisements should be run through different channels, or even whether or not customers are satisfied with the quality of a product.
Naturally, PMs need to meet some PM education requirements In order to understand and be able to analyze all the metrics effectively, PMs usually enroll in a PM bootcamp or take a product management certification course.
Product analytics metrics help the following people plan effective strategies:
The Product Manager:
Product managers can monitor what the customer likes through metrics like NPS or Net Promoter Score. They will also be able to see what needs improving in their product by using these analytics for analysis. Product managers would want to know if customers are frustrated with a certain feature of the products and plan necessary improvements in that area.
Developers and UX Designers:
Product analytics can help developers and UX designers understand what the customer likes or doesn't like about a product. They may be able to identify issues with certain features in order to make improvements or optimize them for customers more effectively.
Marketers can use product analytics to identify opportunities and changes in the market. Product managers are able to see if a campaign has been successful or not by using metrics like conversion rate, traffic sources, bounce rates, etc.
Product insights can help research teams understand how customers feel about their products. This is especially true for innovation teams. They may be able to identify new opportunities or problems with a product by using metrics like customer satisfaction, purchases per visitor, etc.
Investors are also interested in knowing how customers feel about their products and can use insights from Product Management for things like branding campaigns that require additional funding.
Product analytics will ultimately benefit end-users because all the information collected will be used by the product management team, the engineering team, the senior product manager, and other team members to craft a new product that meets customer experience expectations.
3 Best product analytics tools
Project managers will use many functionalities of business analytics platforms designed to obtain accurate data analytics metrics. These tools will give PMs the results of different digital product strategies and if metrics are meeting the product roadmap goals. The following SaaS companies offer these tools:
Amplitude is software that offers easy-to-use analytics and ensures teams work together. It also resolves one of the most prevalent challenges for product teams: data governance, security, and compliance.
The development team at Mixpanel is driven by knowledge of the importance of great products. The software allows its users to analyze top traffic flows, funnel data, and create customer cohorts among other analytical features.
Mixpanel not only offers a simple data model and APIs to load your own data but easy insights as well.
Google Analytics is the most widely used website analysis service. It helps webmasters and product managers to measure traffic, identify visitor behavior patterns on their site, and improve conversion rates.
Product managers will use Google Analytics in many ways, for instance, to see how many visitors came from organic search and what keywords they used or to measure the success of a new campaign.
Why is Product analytics important?
Product analytics is important because it will give you a better understanding of your customers and what they're looking for and if your product vision aligns with it.
The product manager job isn't just to build the best possible product; it's also to understand how their target audience uses the products that are available, so they can make strategic decisions about new features or updates.
Product managers will use analytics to measure traffic, identify visitor behavior patterns on their site, and improve conversion rates.
Product managers will also need some basic knowledge of statistics in order to analyze the data they collect from Google Analytics or other tools.