What Is User Analytics And How To Use It To Improve SaaS Metrics?
What is user analytics, and how can it help you drive product growth?
User analytics provides actionable insights into user behavior. This allows you to see what different segments of your customers are doing in your product and why they behave that way.
With smart strategies and the right user analytics tools, you can leverage user analytics to improve SaaS metrics and unlock growth.
Let’s find out how you can do this.
- User analytics is a method of collecting and analyzing user behavior inside your website or product.
- User analytics lets you segment users based on their personas and use cases, analyze their activities, and improve product experiences for each of the groups.
- Segment analytics lets you group users based on demographics, in-app behavior, account, user attributes, and/or user sentiment.
- Funnel analytics lets you identify the users who convert at each step of the funnel and thus, find areas of high-converting traffic.
- Cohort analytics provides insights into a specific cohort’s behavior inside your product and uses the insights to reduce churn.
- User analytics help you create user journey maps so that you can improve user experience to drive activation and adoption.
- Analyzing the different cohorts or segments allows you to observe patterns to create personalized user experiences and increase user retention.
- User behavior analytics helps you flag underperforming features and modify onboarding experiences to improve feature discovery.
- Userpilot, Hotjar, and Mixpanel are the 3 leading user analytics tools out there.
What is user analytics in SaaS?
User analytics is a method of collecting and analyzing user behavior inside your website or product.
It records user activities, groups users into behavioral segments, and analyzes key SaaS metrics such as user engagement and activation.
What is the value of user analytics?
No matter how much data you collect, without user analytics it is meaningless.
51% of users won’t return to a company if they’ve had bad experiences with it. Knowing your customers is essential for developing effective marketing campaigns, improving products, and increasing engagement and retention.
Additionally, the quantitative data you collect can help you not only detect, but also predict certain trends in user behavior.
When you know how users behave, you can identify the features they are engaging with most and know what benefits they are receiving from your product.
You can even analyze user behavior to build reactive in-app experiences. You can also figure out customers’ needs proactively and improve your product or certain features accordingly.
Moreover, user behavior analysis allows you to segment users based on their user personas and use cases. This helps you learn how different user segments interact with your product so that you can build a better product for each of them.
Onboarding flows can be analyzed to discover bottlenecks, boost conversions, and identify customer churns. This further helps you improve onboarding experiences and use product marketing to boost conversion, activation, and retention.
User analytics also provide insights into how users interact with products at every stage of the user journey. In this way, you can develop a well-defined user roadmap to improve decision-making related to changes in UI/UX design, upgrades, new features, and onboarding. You can even adjust your SaaS growth metrics in real-time.
What are the different types of user analytics?
There are 3 different types of user analytics.
- Segment analytics
- Funnel analytics
- Cohort analytics
Customer segmentation is the process of dividing your users into groups based on their shared user behaviors to provide better experiences.
Segment analytics thus involves user analysis of each customer segment. You can define segments by users, survey data, usage events, and even external sources such as data from sales and marketing management systems and referral channels.
Most of the user analytics tools allow you to segment users based on the following models:
- Demographics – It includes gender, income, and age. More detailed designs include nationality, occupation, race, and even lifestyle.
- In-app behavior – This shows whether users have activated, completed a certain UX flow, performed some custom events, or interacted with a new feature.
- Account – It separates customers into new users, enterprise users, and power users.
- User attributes – It includes the plan a user is on, what language they prefer, what devices they use, and whether they registered through a company member or independently.
- User sentiment – Using the Net Promoter Score (NPS) metric, this model segments users into promoters (loyal users and advocates), passives (indifferent users), and detractors (unhappy users).
Usually, the bigger the SaaS business, the more user segments you’ll need. So, you may have to combine and match criteria from more than one model. Smaller businesses usually need 3-4 segments.
You can use the user behavior insights from segment analytics to provide tailored solutions to each segment. Plus, you can find out the segments on the verge of churn and take preventative measures.
A funnel (also known as a sales funnel or conversion funnel) is a series of steps used to map the journey of users to conversion. It could be any type of conversion, such as a purchase or signup.
Funnel analytics is the process of identifying the users who convert at each step of the funnel.
It allows you to make informed decisions to improve user experience and, thus, conversion rates. You can capitalize on your strengths by highlighting the areas with high-converting traffic.
Moreover, funnel analytics lets you run re-engagement campaigns, modify your onboarding flows, or fix bugs at any point in the user flow.
Moreover, it moves beyond improving conversion rates to helping you understand how rates differ by user behavior. Thus, you can learn what drives conversion, what causes users to churn before converting, and what optimizes funnel performance.
You can use an advanced funnel visualization tool such as Google Analytics. With this tool, you can set goals and use their Goal Flow feature to filter out the sources of converting traffic.
Cohort analytics lets you see what a cohort (sub-section of users) does inside your product. Software companies usually use cohort analytics to measure customer churn. This is why cohort analysis is also called customer churn analysis.
There are 2 most common kinds of cohort analytics:
- Acquisition cohort: where the customer segment is created based on the date they signed up.
- Behavioral cohort: where the cohort is based on user behavior while they use your product.
Based on the type you choose, cohort analytics helps you answer these questions:
- Which user segment (eg. by use case, user persona, subscription plan, etc.) churns the most?
- How long can you retain an average customer and at what point do they leave your product?
You need a cohort table, like the one shown below, to perform cohort analytics.
The rows (from top to bottom) segment cohorts based on their signup dates, specifically by months. The columns (from left to right) indicate how long has passed since a customer subscribed.
Each cell in the table gives the percentage of customers who churned within a particular month of subscribing.
Knowing when users leave and how the churn rate varies depending on when a new cohort signs up, you can check whether your marketing and product strategies are effective.
Also, you will be able to see if any changes you make to new user onboarding eventually affect your first-month retention rate. You can even see if changes to your product, UX, or marketing strategy have any effect, positive or negative, on your product.
How to use user analytics to improve SaaS metrics?
Analyzing user data helps you know how much users engage with your product and how it affects retention, customer lifetime value, revenue, and other vital outcomes.
Therefore, user analytics is the key to improving SaaS metrics and driving product growth. And here’s how you can achieve that.
Use user analytics data to map out user journeys
The main purpose of the user journey is to help convert users into paying customers and adopt your product completely.
You create a user journey map to visualize this user journey. You can use insights from user analytics to create a user journey map and find the right metrics to track.
What’s more, you can map out multiple user journeys through user segmentation based on different personas. This will help you find areas of poor user experience.
If you quickly address issues with user experience, you can keep your users engaged and help them understand the value of your product.
Thus, your users can quickly reach their Aha! moment (realize the value of your product) and activate (actually get the value).
Therefore, a user journey map helps boost customer acquisition, retention, and your company’s revenue.
Use insights from analytics to create personalized user experiences
Analyzing the different cohorts or segments helps you observe patterns to create personalized user experiences.
With segmentation, such as in the example below, you can even discover highly disengaged users and build personalized onboarding experiences for them to prevent churn.
Your user onboarding should take place in the context of what users are currently doing or not doing within your product.
Personalized, contextual onboarding based on users’ goals, role, persona, and use case makes the user experience more engaging, relevant, and thus, effective.
Furthermore, in today’s SaaS world, self-serve onboarding is crucial for providing a positive user experience. It should be accessible to users 24/7 to help them solve repetitive issues by themselves without waiting for human agents.
In-app resource centers let users search all your onboarding and help documents by keyword, which greatly improves the onboarding experience.
Use user analytics to identify features that aren’t working properly
User behavior analytics will help you flag the features that aren’t functioning well.
Before a user can complain or churn, you can proactively understand their needs by keeping track of trends and activities. It can help you guide your product marketing and value proposition if, for example, a certain feature is used more frequently than others.
If your users aren’t adopting a specific feature, especially after requesting it, it can mean that your secondary onboarding is falling short. It can also indicate that the feature isn’t in an intuitive location inside your product.
Improved secondary onboarding can help users discover more features and thus, drive more and more value. It makes it easier to gain more power users and brand advocates.
3 best tools to track user analytics
The right user analytics tool for you depends on your product and business goals, among other factors.
You should consider certain criteria before choosing a user analytics tool.
- What it measures
- How it gathers and measures data
- Whether it measures unidentifiable or identifiable data (email, unique ID, etc.)
- The type of analytics it performs
- Whether it tracks in-app or website user activity
- Whether it fits in with your current technology and tech stack
Let’s look at the top 3 user analytics platforms you can use to track user behavior.
#1 – Userpilot
Userpilot enables you to monitor user behavior based on predefined goals. This makes it flexible to choose what aspects of product usage to concentrate on, thus making it a lot easier for you to track and interpret user data.
Userpilot’s analytics is built on what users do inside your product.
It’s based on feature tags that lets you ‘tag’ features on the front end of the web app. It’s also based on custom events created by the software developers.
What’s unique about Userpilot is that it offers proactive onboarding. It helps you take charge of a user’s journey, proactively understand their needs, and direct them towards particular features/experiences.
#2 – Hotjar
Hotjar is a behavioral analytics tool that comes with session recordings and heat mapping features.
You can record the browser actions of your customers while they visit your site and gain valuable insight into their behavior. You can even revisit those recordings multiple times to get a more in-depth user analysis.
In addition, you can find areas of friction in the user adoption journey. So, you can take prompt actions to reduce your Time to Value, improve user experience, and boost your retention rates.
Piecing together the insights enables you to map out the entire user lifecycle effectively – from being a mere visitor to becoming a power user.
#3 – Mixpanel
Mixpanel is a very advanced analytics solution that lets you track and gather user data in real-time.
With Mixpanel, you can track the interaction of every user segment with your product. You can even predict user activity to decrease churn proactively.
However, the platform doesn’t perform account-level tracking unless you can add all of your customers into one segment.
Mixpanel may be the most suitable option for you if you’re a large business with an in-house analytics team. Being a highly technical tool makes it possible to conduct complex analytics using large data pools.
Wrapping it up
You can’t get away from user analytics if you want to achieve product growth. It opens up a world full of actionable insights into user behavior.
In turn, you can use these insights to improve your marketing and growth strategies, and therefore your SaaS metrics such as activation and retention.
Want to get valuable insights into your user analytics? Get a Userpilot demo and see how you can achieve it easily.