Product metrics are data about how customers and users interact with digital applications and products and how they interact with the business. Product metrics are used by product teams, marketing teams, customer success teams, and analytics teams to determine the success of products and websites. Product metrics are data analyses that benefit companies to assess product progress and learn how customers involve with the product. Standard metrics such as termination rates and conversion rates are reflected in product strategy and help different stakeholders in the company understand the product’s value.
Product metrics vary significantly from product to industry. However, a standard metric can be used for almost all products choosing the right metric for key performance indicators. It is a significant part of the product improvement process. Many experts recommend tracking metrics at the time of product or feature launch.
Product metrics are often classified into different groups. It is an efficient way to estimate how a product works from various aspects. Classifying Product Metrics One valuable and straightforward way to classify product metrics is to separate them into two groups: business metrics and action metrics.
Why are product metrics important?
There are several essential reasons why product metrics are essential.
Lead to better product decisions
By determining the right metrics to monitor and analyze, the company can make more intelligent decisions throughout the product development process.
These metrics, sometimes referred to as Key Performance Indicators (KPIs), provide quantitative evidence of which aspects of the product or customer experience resonate with the customer and which are not.
Using product metrics makes it easier to get executive approval:
The second reason to use product metrics is to provide executive employees with objective support for their proposed plans as product managers present product roadmaps. Management wants to see evidence that if they approve the proposed product, the company will get a positive return on investment.
Product Usage Metrics
- The number of Days Active Users:
- Number of customers using the product on a daily or monthly basis
- Feature usage:
- The number or part of clients practicing a specific feature or feature set
- Length of the session:
- The amount of time customers spends using the product in one session.
- Several sessions per user:
The rate of sessions per client during a specific period
How does the product analysis tool work?
Product analysis tools capture data by tracking user behavior within products and websites. From this data, the product team can use a variety of analytical methods to extract insights. Here is a general example of how product analysis tools work.
- Attribution analysis:
Analyze customer touchpoints (demos, sales talks, website visits) leading to purchases.
- Churn analysis:
Investigate customer loss rates to understand the causes of customer separation.
- A cohort analysis:
To measure long-term behavior patterns by dividing users into related groups and cohorts.
- Conversion analysis:
Determine if the customer has completed the desired conversion action (e.g., sign up for a trial) and discover where the customer leaves.
- Funnel analysis:
Map a customer’s journey through different stages to reach a goal. It allows the Product Manager to understand the points of friction and separation.
- Retention analysis:
Understand factors that drive customer continuity (reverse of cancelation analysis).
Group users based on demographics, behaviors, personas to reveal deeper insights.
Sometimes, the only feedback on product issues is these metrics. The user may not request help from customer support. The company will also not be able to contact the sales representative to complain. Users may stop using certain aspects of the product, but they will not contact the company to tell them why. If this situation continues, the cancelation rate will increase, and the product’s reputation will drop.