The concept of product analytics refers to the measurement of digital products, and refers to the process of understanding how users interact with a digital product and using this data to improve our software.
What is product analytics?
In a world where SaaS has exploded, where competition is a click of a button away, with relatively low barriers to entry, it is extremely important to properly instrument the measurement of our software. Instrumenting a digital product helps startups understand product performance and identify areas where they can improve.
We are all aware of the importance of analyzing user behavior in a SaaS, but the reality is that few teams aren´t measuring their user data correctly, and when you need to scale, that becomes a problem.
Do you know how to identify which user cohorts produce more churn?
In this post we will talk about analytics products andproduct analytics tools and how to establish a digital product analytics measurement strategy.
What is digital product analytics and why is it key to scaling a Saas?
Product analytics is the process of converting data from various data sources into insights that can be used to detect inefficiencies or improvements in our products. For example, digital product analytics can help us identify problems that may prevent user churn or achieving a goal. By incorporating analytics into our digital product measurement process, we can obtain a deeper understanding of how users interact with our Saas and make decisions not just based on intuition.
But what aspects are important to measure when implementing Saas measurement?
Steps to implement a product analytics strategy
One of the main problems in a product analytics orchestration project for a SaaS is to focus on the analytics tool, instead of the objectives we want to achieve. So, before talking about tools, let’s talk about the steps to follow.
The steps to implement digital product measurement are:
- Define our concept of active user.
- Define a product measurement plan:
- Identify user events to be measured and tag them for implementation.
- Define target metrics to analyze.
- Select the product analytics stack.
Define our concept of active user.
The number of active users is a basic metric for measuring SaaS performance. To know what an “active” user really means for your application, you have to define it by looking at the usage pattern of each user and the characteristics of your business.
In this previous article we told you how to define an active user in a SaaS.
Define product analytics measurement plan
The instrumentation strategy is the plan we have to implement analytics in our digital product. We must draw a plan to collect and store the data, define who will have access to it and design an architecture that can scale as our application grows, for this we must focus on identifying the events and identify the metrics and the stack of measurement tools.
Identifies user events to be measured
The behavior of a user within a Saas, is usually measured through the actions that the user performs in it. Each time a user performs an action we can configure a trigger for this event, so that it is recorded in the chosen target system, which can be the database itself or another service, such as, for example, segment.
There are different types of events that can be measured:
- Contact support.
- Page scroll.
- Logins and when was their last session.
- Pages visited
- Time on each page.
- Buttons or actions performed.
- Count of users for wau, mau and dau calculations.
It is important to identify these events clearly following a nomenclature that does not change, and easy to understand to differentiate one event from another. It is also important to define in which phase of the user journey it should be.
This would be an example of the nomenclature with the following fields:
|Name of the action that a user has performed
|Free-form dictionary of properties of the event, like
Here is the documentation on Segment’s event instrumentation
Product metrics for Saas
Some of the product kpi’s in a Saas are:
- DAU(Daily active users)
- WAU(Weekly active users)
- MAU(Monthly active users)
- Dau / Mau ratio
- Activation rate of users to paying customers
- MRR movements
In the post mentioned above you can find more information.
Product Analytics measurement issues
Now that you understand the basics of digital product measurement, there are a few issues to keep in mind when setting up your system.
Data privacy and security
Another issue to consider is the accuracy of the data. When collecting data, you should make sure that it is accurate and up to date, as you may corrupt your database or the service you use.
Data can be interpreted in many ways and you need to understand how it applies to your business. For example, an increase in MRR does not necessarily mean that your product is doing well, it may mean that your sales team is doing push selling things that your product is not doing and then generating more churn.
Product analytics Tools
Okay, now that we have defined the steps to define an adequate product instrumentation, it is time to choose the best tools for product analytics.
Here are some of the most commonly used product analytics tools:
- Google Tag Manager
- Analytics or Firebase
In the next post about data analysis tools we will analyze them and talk about the pros and cons of each one of them.
And if you need to instrument your digital product and define a measurement strategy: