Product Management Analytics: Goals, KPIs, and Metrics

Product management analytics provide a view of how users interact with your product. Collecting and analyzing this user data gives you valuable insights into building better products and achieving your business goals. In this blog, you will learn how to leverage various product management analytics metrics to grow your business.

‍

What is Product Management Analytics?

Product management analytics is a combination of product analytics and product management.

‍

While Product analytics is the process of understanding and analyzing consumer behaviors and their interactions with your products or services, Product management involves creating a strategy to drive product development, market launch, and continuous improvement.

‍

Product management analytics can monitor customer actions and help you prepare a product roadmap based on the insights generated from data analysis.

‍

Why is Product Management Analytics Important

As a product manager, product analytics will help you and your team identify the shortcomings of your product and how to improve them. It will also guide you in optimizing user experience by understanding consumer behavior.

‍

Here are some of the reasons why product management analytics is crucial:

• Direction to Product Development and Design: By tracking user events and reviews, you can understand the likes and dislikes of customers. This allows you to enhance your product development process for better customer satisfaction.
• Economical: Many organizations spend a lot of money on advertising to attract customer attention. Instead, some of your budget can be used to conduct product analysis to better understand customer expectations. This can help you optimize your marketing campaigns to target the right audience, enabling you to generate a better return on investment.  
• Strengthening Customer Relationships: Product analytics can help you build better customer relationships through retention. You can do this by actively listening to them, communicating in a personalized way based on their purchase behavior, and staying connected to them through various platforms.
• Competitive Advantage: Product management analytics helps you understand your competitors' performance. This can help you identify opportunities for yourself and stay ahead of competitors.

How to Choose Goals and KPIs for Product Management Analytics

Now that you know how beneficial product data analytics is for overall product strategy and business growth, let’s learn how to choose suitable metrics to impact business performance.

‍

Though often used interchangeably, goals and key performance indicators (KPIs) are different. They come in a hierarchy, with goals at the top. Goals are a company’s highest priority, and KPIs measure progress toward them. Once you select your goals and KPIs, you can determine the metrics that support them. Metrics act as a guide for fulfilling the goals and KPIs by breaking them into achievable components and tracking their progress. They make analytics for product managers easier.

‍

Some of the things that you can keep in mind while choosing the right product management analytics metrics are:

• Set Clear Business Goals: You should clearly define the customer and business goals you want to achieve and the specific outcomes you desire for your products.
• Ease of Use: As an analytics product manager, you should ensure that the metrics you and your team use are simple. You must consider factors such as the complexity and expertise required while selecting metrics. Analyzing a complex set of metrics can be difficult, as every team member may need more knowledge about it. This creates an imbalance, thereby reducing the team's efficiency.  
• Avoid Vanity Metrics: Vanity metrics are statistics that look great on the surface but don’t essentially translate to meaningful business results. They increase your set of KPIs and result in unnecessarily collecting and analyzing more data. It will waste your time, and you will act on irrelevant data, making wrong decisions.
• Use Quantitative and Qualitative Metrics: Quantitative indicators measure the quantity of something and allow you to collect “hard” data, such as daily active users or monthly recurring revenue. Qualitative indicators help you understand why something has happened, like why users aren’t as satisfied with the product as you expected. Combining the two types gives you a balanced view and allows you to understand your product's performance.

‍

Consider an example of a video-sharing company. The visual below gives insights into its goals, KPIs, and metrics.

‍

Sometimes, choosing a suitable set of metrics for your company can be complex. This is because no two companies are the same. Thus, no “correct” set of measurements exists for any business organization.

‍

Important Product Management Analytics Metrics

While conducting product management analytics, you must combine insights from multiple sources, ask logical questions, and perform experiments to get productive answers. This includes creating and testing hypotheses to see how everything will fit together. There are a variety of different analyses available to help you understand your metrics. Here are some of the most useful types of product management analyses:

‍

Segmentation: The segmentation metrics enable in-depth data analysis by categorizing similar characteristics that users share. This includes attributes such as behavior, signup date, or source through which they can be targeted (emails, social media, or TV commercials). For example, you can segment your customer data for an anti-ageing cosmetic based on age and gender. Segmentation will help you understand the demography of your audience and inform you what features to include to increase your product’s reach to more people. It also enables you to communicate with your customers in a personalized way and optimize your resources for practical usage.

‍

Cohort Analysis: Cohort analysis categorizes users into groups or “cohorts” based on common characteristics or behaviors. You can use it to track changes in behavior or engagement over time. Cohort analysis can be time-based, event-based, or behavior-based. You can analyze them to understand and change user events. For example, suppose your blog website has two cohorts for its readers: paid subscribers and free visitors. Your readers can access premium content only if they have paid for it. Free readers will be converted into paid subscribers only if your premium-quality content is good. Thus, cohort analysis can encourage behavior change and help you to improve the quality of your products.

‍

There are two types of cohorts: absolute and relative. Absolute cohorts track a fixed group of users, while relative cohorts track a shifting group of users.

‍

‍

Retention Analysis: Customer retention is one of the most critical metrics for any business. It indicates that your customers are satisfied and will likely remain loyal to your product. The retention analysis metrics determine the factors that lead to user churn. To improve retention rates, you can conduct in-app engagement, customer feedback, and user activities to understand and address issues. You can also choose KPIs such as customer churn rate, customer lifetime value, customer engagement score, etc., to calculate the retention rate.

‍

Funnel Analysis: The funnel analysis helps product managers understand the flow of customers on their website. The steps users take toward a desired outcome, such as signing up, checking out, or purchasing a product, are called events. Funnels measure these events to optimize the user experience and drive conversions. For example, you want the customer visiting your e-commerce website to review your products, sign up, and purchase them. These steps are called goals or micro-conversions. Funnel analysis helps you comprehend this user flow.

‍

Houseware: The Definitive Tool for Product Management Analytics

Houseware is an AI-powered product analytics software that you can use for product management analytics. It offers prominent analytics metrics such as funnel, stickiness, retention, cohort, etc.

‍

Let’s briefly look at some of these features:

‍

• Funnels: Funnels are visualizations that help you understand user events. You can use this Houseware feature to analyze the series of steps a customer performs during a website visit and the steps at which they leave your website. Usually, the funnel charts out the path of a customer’s actions. It also accepts events where users engage in other actions between the Funnel steps until they reach the final stage. Such capabilities of the Funnels feature make it effective for use in product management analytics.

• Retention: Retention measures the number of customers who return for your product or service. It offers a glimpse into how users are interacting with your product. The Retention feature considers two components to measure the retention rate. One is analyzing a critical event that shows genuine customer engagement. The second is the product usage interval, which explains how frequently users engage with the product. Houseware uses the N-day retention method to calculate retention. It is the proportion of users returning on the ‘Nth’ day after first use. You can calculate N-week and N-month similarly.

• Cohorts: Cohorts are groups of customers with common behavior characteristics. The Cohorts feature simplifies the analysis process, as you only have to analyze a specific set of users. Houseware creates cohorts by applying filters such as AND, OR, or both to facilitate product management analytics. These filters help you identify user properties (like city, region, and device type) or event behaviors (such as users who enable in-app notifications). With this knowledge, you can refine your product management analytics to understand customer’s preferences.  

Conclusion

This article provides comprehensive information on product management analytics metrics. It briefly explains the commonly used metrics and how to choose suitable ones for your company. Houseware is one of the best product management analytics tools. Its features, such as Flows, Funnels, Cohorts, Retention, and Stickiness, can enable your product manager and data analytics team to optimize product management. Book a demo to harness the benefits of Houseware today!