Everyone knows data rules the SaaS world, and it's absurd to ignore it. Product usage analytics provides you quantitative information to identify the weak and strong aspects of your product. And it allows product teams to establish what's working and what is underperforming.
So, this guide will cover the following:
Let's get started.
Product usage is a process to analyze all the possible when-and-how of user behavior and product interaction.
It keeps track and identifies the most used features and how customers navigate the product.
After the analysis, you can pull various aspects of the user's needs and desires, such as:
Let's take an example of retention analysis—it helps to understand the interaction pattern of customers with your product, why they churn, and how you can stop it.
Let's say, during the beginning of the month, 100 people signed up for your product. But after analyzing the product usage after a certain time, you realize that 50 people have stopped using the product.
This means users are churning, and it is a sign for you to devise strategies to re-engage them.
And that's how you can stop users from leaving your platform or decreasing product usage.
It is common to divide product analysis primarily on three bases:
It mainly focuses on numbers rather than interviews and surveys to get solidified answers and build actionable product-related strategies.
Data hunting gets simple and time-saving with product analytics as it’s not subjective anymore. Because most times the customers aren’t aware of solutions either, but they will tell you their problems.
So your job is to create solutions for their problems and not the other way around.
Product usage analytics provides the complete picture of how the customer navigates through each product touchpoint.
It dives deep into real customer needs by assessing in-app behaviors and ahead of time speculations.
For instance, there are two approaches to detect: the product adoption rate and how users find the features in the product.
Whether you go with a lengthy procedure like asking your user directly through surveys or 1:1 interviews, product analysis is the last destination for authentic results and comprehensive strategies.
The only luxury you don’t have in the SaaS world is time— because it moves extremely fast. As time is limited, you have to employ it robustly. Invest in strategies that save you time and are relevant to the operations.
Execute them by utilizing your data lake without any time-consuming interactions in just a matter of minutes.
Take some time and understand the nitty-gritty of product usage analytics to enforce desired business outcomes, and start with the fundamentals of statistical analysis.
For this, you have to keep a tab on the few crucial metrics:
With the product onboarding engagement rate, you can know how many users engage with your product onboarding.
With this metric, you can keep track of three different product onboarding stages through in-app experience, which guides users through simultaneous actions.
Those three stages are:
To boost your product adoption and retention—keep a tab on each stage and integrate them with constant testing and follow-ups according to your customer experience.
It's a metric that provides an in-depth analysis of the number of users using any specific product feature.
It mainly works with the concept of the cohort when you're initially trying to crack the right code for the product usage analysis. Eventually, you can guide the customer towards any specific feature to increase its usage.
The product adoption stages are closely related to user journey stages, pointing out different paths that a user takes to reach your significant product adoption.
This metric is closely related to the identification and subsequent reach of your Aha Moment.
This metric takes the specific key features into account. For instance, if your product is a social media management tool, then key actions for it can be:
Accomplishment of key user actions is an indication of the value offered and experienced by customers - which is a start to fighting churn.
It utilizes product health to identify its pulse and correlate multiple user cohorts or behavioral user segments. It emphasizes boosting retention and eliciting more usage by deploying valuable insights. And it helps you to optimize product acquisition programs.
Before starting, make sure you collect all the crucial data necessary for the successful implementation of your plan.
Product analytics tools are the best in business to track customers' pov on your product. Choose one by aligning platform functionality with your business goals.
With Salesmachine, you can get a bird's eye view of your product usage — such as feature usage, stickiness, and other critical elements related to health and revenue.
Tracking platform implementation takes a good amount of knowledge, time, and capital.
Then the next step comes: understanding the analytical data by getting to know the gist of software's operations, report generation, and solutions output.
After executing the steps mentioned above, validate that you have factual data on your hands.
Set your goal according to your business's demands to bring out the full potential of product analytics.
Conduct meetings with employees from all teams to cover all business domains and map out diverse goals.
Discuss those goals with your team to get their input. This way, with the cooperation of all departments, you can set a realistic timeline to achieve those goals.
After setting a clear goal, it's time to formulate strategies to achieve them. Implementation of those strategies needs data to get your plan in action.
Various product analytics data is needed to achieve those goals. For example, you want to increase the product adoption rate. So you need to think about what is hindering that growth?
The point here is to find the why behind those actions instead of piling them up with solutions before understanding them.
Once you understand the core problem, you can create solutions for it easily.
Now it's time to dig into the data collected through product analytics platforms.
For example, study the customers who rate your product low. Find the common point of interest between those customers.
Track their movements on your product because it might be the case that they don't understand the niceties of your product entirely.
Make sure to keep your final goal in mind while running through all this process, as it's easy to get distracted by these metrics.
Keep sharing your progress data from among departments, and update them about the next steps, which can help them complement each other's work.
The metrics provided by these product analytics platforms mark the beginning of your plan. After that, start working on your product by making small changes.
Avoid amending all changes at once; instead, start with one or two metrics that need your immediate attention as per the goals.
Again discuss with your R&D team to make your product's functionality flawless. Follow two or three plans, choose one with maximum output, and keep working on it.
Let's wrap up things with a few key points:
The critical takeaway is to make sure your product usage analysis should be a collaborative effort of different teams and not a self-analysis from the product teams. This will open the door to various specialized ideas and will bring you qualified results to the table.
Salesmachine is a one-stop destination for all your needs that will help you increase product engagement.
With the SaaS dashboards, you get a unified view of your key product usage in real-time. Let’s face it ; static data is not actionable today. You can get an idea of the current product usage, revenue, and customer health at your fingertips.
Real-time analytics help you understand the current scenario without going back and forth to historical data.
To take this one step further, you can track account-based usage to understand the big picture. You can instantly access the product usage effectively, making it easier to use the platform and create strategies for better product engagement.