Customer Engagement Analytics: How To Collect Analytics Data and Increase Customer Engagement

Customer Engagement Analytics: How To Collect Analytics Data and Increase Customer Engagement cover

Thinking of using customer engagement analytics to improve customer relationships and increase user engagement?

Customer engagement analysis helps you understand your users’ buying behavior and sentiments. It helps you anticipate customer demand and gives you a competitive advantage.

If you’re looking to create and implement highly effective customer engagement strategies, then this article is for you!

Ready to get started? Let’s go!


  1. You can track in-app interactions to understand how customers are engaging with your product.
  2. Feature tagging enables you to track feature usage and see how customers are interacting with different features.
  3. You can use heatmaps to pinpoint areas of high and low engagement.
  4. Next, make use of custom goals, aka milestones, and see how customers are progressing. You can offer to help those who aren’t progressing as planned, increasing engagement along the way.
  • To leverage the customer analytics data and improve customer engagement, you can start by segmenting customers based on engagement and sending personalized marketing messages to them.
  • Next, you can implement a loyalty program to engage loyal customers and make them power users.
  • Segmentation also allows you to identify lapsed customers, whom you can re-engage and attempt to win back.
  • Userpilot is a comprehensive product engagement tool that helps you collect customer data, track user interactions, and segment your users based on different criteria. Book a free demo to see how it can help you boost customer engagement.

What is customer engagement analytics?

Customer engagement analytics refers to measuring customer data from all interactions to evaluate customer health, identify preferences, and forecast future behavior.

What are the benefits of customer engagement analytics?

A solid customer engagement strategy can do wonders for your SaaS product. Here is how customer engagement analytics can help you create a data-driven strategy.

Understand customer interactions that impact the customer behavior

First, it allows you to visualize how customers are interacting with your product and how these interactions shape user behavior.

This helps you understand your customers on a deep level, increasing your chances of building a strong relationship with your user base.

Uncover the problems that block the customer journey

Next, with engagement analytics, you can identify problems your users face regularly.

These friction points stop them from advancing on the user journey and must be addressed to improve customer engagement and their experience.

Improve customer retention and customer loyalty

Finally, analytics can help you identify different product use cases.

This allows you to create personalized flows, which in turn improves user retention, increases loyalty, and reduces churn.

Key metrics to measure customer engagement

Here are five essential metrics that you can use to analyze your customer engagement processes.

Customer Engagement Score

The Customer Engagement Score (CES) is an essential metric that measures how engaged your current paid users and free trial prospects are.

This metric attempts to quantify user engagement and is reflected through a score based on several event values.

Customer Engagement Score.

To calculate the CES, you need to first identify what events define customer engagement for you. For example:

  • Frequency of Product Usage: How often do users open your software?
  • Key Features: What features do your customers use the most often or don’t?
  • Customer Upgrades and Renewals: How often do customers switch to the next paid tier or renew their subscriptions?
  • The Number of Support Tickets: How many tickets, within a given period, are issued by customers? Additionally, how many are solved?

The events mentioned above can vary between products and companies. They can differ in terms of importance from one SaaS company to another.

Once you’ve defined all the events, you can sum their scores to measure your customer’s overall success, health, and engagement.

Product stickiness

Product stickiness refers to users’ tendency to return to your product because they find value in it and are highly engaged by it.

Measuring this metric helps you identify scopes for providing account expansion opportunities, improving customer retention, and increasing CLV (customer lifetime value).

Product Stickiness.

The DAU to MAU ratio is one of the best ways to measure product stickiness. To calculate this for a given period, you need to find out the number of daily active users and monthly active users and then divide them as shown in the image above.

Customer lifetime value

Customer Lifetime Value (CLV or LTV) is the average amount of money your product gets from one customer over the entire duration of their relationship with you. In other words, it is an estimation of the net profit one customer can bring you in the future.

To calculate the CLV, you need to first find out the average revenue of the account(s) whose total lifetime value you’re trying to measure. Then, divide this by your existing customer churn rate.

Customer Lifetime Value.

CLV is a crucial indicator of customer engagement as it is directly connected to customer retention. Additionally, it is a predictive metric that aids in the improvement of financial decisions for your SaaS business.

Customer Satisfaction Score

The Customer Satisfaction Score (CSAT) measures how satisfied your current users are with your product and helps you understand their expectations. For example, you can use this metric to gauge customers’ satisfaction levels with your product’s features or customer service quality.

A high CSAT score shows that your efforts have exceeded user expectations, which leads to greater customer loyalty and retention and, consequently, reduced churn rates.

To calculate this, you need to first conduct a survey where you ask existing users how they feel about a certain product or feature. Here’s an example from Hubspot.

Customer Satisfaction Score.

The score is calculated by dividing the number of respondents who are highly satisfied by the total number of people who answered the survey.

Net Promoter Score

The Net Promoter Score (NPS) measures the likelihood of your users promoting your product.

To measure this, you must conduct a survey asking your customers a singular question, “How likely are you to recommend us to a friend or colleague on a scale from 1 to 10?”

NPS divides your respondents into three categories:

  1. Users selecting 9 or 10 are your most loyal customers. They are highly engaged customers who are advocates for your brand.
  2. Passives are users who select 7 or 8. They are neutral customers who are not harmful.
  3. Detractors are users responding with a 6 or below. They are particularly dangerous as they can ruin your brand image through negative word-of-mouth.

Using your survey and the total number of respondents, you can calculate your score by subtracting the percentage of detractors from the percentage of promoters.

Net Promoter Score.

A high NPS shows that users are very happy with your product. They are likely to suggest your product to their friends, family, or colleagues, thus directly contributing to your product’s growth.

How to collect customer engagement analytics data?

Here are four proven ways to collect accurate and relevant data for customer engagement analytics.

Track in-app interactions to understand how customers are engaging with your product

Tracking customer interactions within your product is a great way to collect data about customer engagement and find how users spend their time on your product. For example, you can see where users’ cursors are hovering or clicking the most.

Track In-app Interactions with Userpilot.

With Userpilot, you can easily track all kinds of interactions, helping you discover engagement trends and identify the most popular parts of your product that keep users engaged.

Use feature tagging and see how customers interact with different features

Feature engagement refers to observing users’ engagement and interactions with your product’s features to know which ones bring the most value to them. This insight helps you to make data-driven decisions to improve product adoption and customer experience.

Feature Tagging Userpilot.

With feature tagging, you can track which features your customers use most frequently. When you track your most and least popular features, you can make the right modifications.

For example, if 2 of your features show low usage consistently, you can take a deep dive and explore possible reasons.

If the improvements are fixable and deserve resources, you can begin designing them. Alternatively, you may want to consider removing unpopular features entirely if they are not profitable.

Use heatmaps to pinpoint areas of high and low engagement

Heatmap is a color-coded visual that helps you pinpoint areas of high and low engagement in your product.

It shows clicks, taps, and scrolls, providing a clear way to understand which specific parts of your product users interact with the most.

Heatmaps in colors.

Usually, the color of heatmaps depends on which product you use most. In the image above, the red regions describe hot areas where users are highly engaged, yellow represents medium engagement, and blue represents cold regions with the least interactions.

Set up goals and see how customers are progressing

You can create custom goals, aka milestones that users can reach and get a sense of accomplishment from.

Goal Tracking in Userpilot.

With Userpilot, you can set objectives and monitor their advancements toward them. By being able to see who becomes stuck in the middle of the goal, you also have the chance to help and re-engage them.

For example, if you see someone has stopped progressing towards the goal, this might indicate that there are friction points that block the journey. You should immediately take action and re-engage the user by showing the right experience flow at the right time.

How to leverage analytics data and improve customer engagement

Now that you know how to collect data effectively, here are four strategic ways you can use it to improve customer engagement.

Segment customers based on engagement and send personalized marketing messages

With the data you’ve collected, you are likely to see that your existing customers have varying engagement levels with your product, which can be used for customer segmentation.

Customer Segmentation with Userpilot.

With this, you can create precise segments consisting of inactive customers, regular users, and highly engaged users. You can then send them personalized messages and create custom flows relevant to their use case.

For example, you can encourage your regular users to switch to the next tier, unlock more features, and gradually become power users.

Userpilot allows you to segment customers by different attributes, such as user data, company data, user feedback, features, events, etc.

Implement a loyalty program to engage loyal customers and make them power users

Your product’s most loyal users deserve to be treated specially. You can do this through loyalty programs that award highly engaged customers. This keeps them even more engaged and motivated.

Loyalty Program created in Userpilot.

You can also nudge them to become your power users if they aren’t already. “Power users” are your most valuable users who have reached full product activation, i.e., they are subscribed at the highest possible tiers, have access to all the features, and use your product regularly.

Identify lapsed customers and try to re-engage them

Customer segmentation grants you opportunities to identify lapsed or inactive customers and re-engage them. As they are not using the app, you can send them an email in an attempt to win them back.

Here’s how Eversign sends one.

Re-engagement Email by Eversign.

Additionally, you can ask your customers what aspects of your product made them lose interest. This can be sent as a cancellation email once users have churned completely or be included in the re-engagement email.

With this insight, you can create a smarter win-back strategy to bring them back to the app.


Analyzing customer engagement involves much more than just comprehending their purchasing patterns. It takes into account a wide range of other user interactions, including social media mentions, website visits, and customer service feedback that also provide information and value to the company.

Customers who are highly engaged are more likely to upgrade your service. But for building and maintaining such loyalty, customer engagement analysis is essential.

Want to track in-app engagement, and collect customer data for customer engagement analytics? Get a Userpilot Demo and see how you can increase revenue and customer loyalty and foster stronger relationships with your users.

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