SaaS Analytics

More than just reporting: How to extract (and use) actionable insights from SaaS analytics

SaaS companies are a lot like a restaurant: they’re in business to make money. But unlike restaurants, SaaS companies have to have multiple streams of data that can help them understand what’s working and what isn’t. They need to get this information – because making the right decisions about their business is critical for long-term success!

Leverage SaaS analytics reports to understand the health of your SaaS company.

Now that you know the importance of SaaS analytics reporting and how to use it, let’s look at how you can leverage these reports to understand the health of your SaaS company.

  • First and foremost, track key metrics that matter for business growth and profitability (e.g., revenue growth). These will give you a good idea about where your company is going next in terms of its business model or product offering. For example: If revenue growth has been flat over time but customer acquisition costs have been dropping steadily since last year’s quarter (which could mean lower overall operating costs), then it might be time for some strategic rethinking!
  • “How do we optimize our top-line performance? What are our customers saying about us?”

These questions are important because it helps you understand what’s working and what’s not. If your churn rate is higher than expected, then you should look into why customers are leaving (e.g., poor onboarding experience) and how to fix it as soon as possible.

Always look for trends and changes that might affect your business.

It’s important to keep an eye out for trends and changes that might affect your business. You should look at certain metrics during respective periods, such as:

  • The number of active users who are paying customers. If a metric has been increasing or decreasing over time, there could be a problem with the product that you need to address.
  • The number of users who have been active in the past three months as compared to those who were active during the same period last year (or last month). This will help you determine whether any particular user type is dropping off faster than they used before—and why!
  • The difference between actual customer value versus what was expected is based on historical data from similar companies who have been using this tool (or similar tools) for longer periods.*

Use specific timeframes to find key levers of change or improvement.

One of the most powerful ways to extract meaningful insights from your SaaS analytics is to use specific timeframes. It’s important to think about what you are looking for, and how long it will take to find those insights.

For example, if you want to see if there are any patterns in your data over time (and why), then look at the last 12 months (or even longer). If this pattern doesn’t seem like it would apply today, then maybe a shorter timeframe would be more appropriate.

You could also look at data over a specific time—for example: “In October 2014 I saw that my customer churn rate was higher than usual.” In this case, we’re not interested in comparing this month with other months; instead, we’re focused on seeing if there’s something about October 2014 that makes it different from other recent months when customers left prematurely or didn’t renew as part of their contract renewal process (which could also indicate an issue with product quality).

Look at overall trends, but focus on specific values and indicators within them.

When you’re looking at your SaaS analytics data, it can be tempting to focus on the overall trends and patterns. You might see an increase in signups or an increase in revenue. But these numbers don’t tell you much about what’s happening with your customers—they are only general indicators of success.

Instead, use specific values and indicators within these larger trends as a way to get more specific information about what’s going on with your users. For example:

  • If you have a dashboard showing all of your metrics for each user segment (e.g., “hiring managers”), look for any differences between groups that make sense based on their goals; maybe one group is signing up more frequently than another. That would indicate something might be happening within this group that isn’t normal behavior but could still mean something meaningful if investigated further down into more granular metrics like churn rate over time etc…

Focus on certain metrics during periods defined by milestones.

To set yourself up for success, it’s important to have a goal before you start. The more specific your goal is, the better. For example: “I want 100% of my users to be paying customers within 6 months” or “I need 50% of my leads converted into sales.”

As you’re setting these goals and preparing for them, keep in mind that they’re not meant to be rigidly adhered to by others—they should only serve as guidelines for your actions. If someone else has a different definition of success than yours does, let them know about how their expectations differ from yours without getting defensive about it or attacking their values or methods (e.g., “I think we should focus on signups first before focusing on revenue generation”).

Use “top of funnel” dashboards to see how well your customers are buying.

Top-of-funnel dashboards are an important part of your SaaS analytics data. They show you how well your customers are buying and can help you understand customer behavior, which will lead to improvements in user experience.

Top-of-funnel dashboards are typically available after a customer has filled out the form for the first time or at another point in the funnel before they buy something from you. They should contain information about:

  • The type of product (e.g., software) that users have purchased
  • How many times each product has been purchased by different groups of people, such as men vs women; young vs old; etc.; and
  • The average dollar value spent per person who made a purchase

Determine what your top customers want through quantitative and qualitative research.

Quantitative and qualitative research are two different types of data collection methods. Qualitative research involves conversations with customers to determine their needs, wants, and preferences. For example, you might ask them if they would be interested in another feature or service that helps them do something more efficiently.

Quantitative research involves gathering information about the size of your user base and how many people use a specific feature or function on your website. This is important because it allows you to see how many users are using certain tools while also highlighting areas where there could be improvements made based on results from this type of research (such as adding new features).

The more data you have, the better when it comes to extracting actionable insights.

The more data you have, the better when it comes to extracting actionable insights from SaaS analytics.

  • More data is always better for any number of reasons: the more information you have about your users, the better your predictions will be; if there’s a problem with one customer’s experience and they complain about it online—or worse yet in person—then maybe that means something is wrong with their product or service as well; etcetera.
  • A more accurate analysis leads to better results and ultimately higher conversion rates (the number of people who sign up for your service).

For any SaaS company to be successful, they need to have analytics set up in their system. It’s not just about knowing what customers are doing or how often they’re using your service—it’s about knowing why they do those things and whether or not it’s good for them. 

Being able to analyze your SaaS data in detail helps you make smarter business decisions.

Analyzing your SaaS data in detail helps you make smarter business decisions. You can use data to predict future outcomes, improve product design and marketing strategy, and even improve sales performance. When it comes to analyzing your SaaS analytics, there are many ways that you can do this.

The key to analyzing your SaaS analytics is to start by reviewing the data in the most basic way possible. This will help you understand what’s happening and give you ideas on how to improve performance.

With Radix you can track & analyze these SaaS Finance Metrics and more:

  1. Monthly Recurring Revenue (MRR
  2. The average revenue per user (ARPU)
  3. Customer churn rate
  4.  (CLV) Customer lifetime value
  5. Customer retention rate
  6. Activation rate
  7. Expansion MRR
  8. 150+ KPIs

Sign Up Here!

(Not Credit Card Required)

SaaS analytics



We hope this article has given you some insight into how to analyze your SaaS data in detail. The more data you have, the better when it comes to extracting actionable insights. And once you have an understanding of your business and its customers, you can use that information to make smart decisions that will help drive growth for your company as well as improve customer satisfaction levels. Everyone within a company must understand what they need from their analytics reports because without them, then there would be no way for anyone outside of the organization (or even within it) to know what data is telling them about their business

Free Trial 2

Luis Cordero Schiffmann
Luis Cordero Schiffmann
Digital Marketing Strategist & Web3 Passionate MBA with expertise in Science, Technology, and Innovation. I'm a big fan of the crypto revolution, the internet and business.