Ever stared at a dashboard full of customer engagement metrics and thought, Does any of this really matter?
You’re not alone. It’s always good to avoid vanity metrics.
Genuine customer engagement metrics do lead to more customers and sales. If you pick the right ones. We have them all below.
Quick Overview: Customer Engagement Metrics
Customer engagement metrics quantify interactions with your brand across websites, apps, social media, email, SMS and other channels. They tell you:
- How frequently customers interact: Metrics like session frequency, likes, and follows tell you how many customers are interacting and how often they engage.
- The depth of those interactions: Metrics like session duration, feature usage, and click through rates help you determine whether customers are truly engaged or just passing through.
When customer engagement metrics are insightful
Customer engagement metrics reveal trends in behavior, such as declining session frequency or increased time spent on a feature, which signal risks and opportunities.
These metrics are also useful for testing changes — if a new onboarding flow leads to higher session frequency, it suggests improved engagement. By comparing patterns over time, businesses can refine strategies to keep customers engaged.
So what does this look like in practice?
It depends on the team using customer engagement metrics. Each one has discrete purposes, goals, and additional data that bring in to analyze engagement. Let’s take a quick look at the different metrics that matter to each team and why:
- Customer Success teams look at retention rates and session frequency, alongside support ticket activity and user feedback to assess how actively customers are using the product,and to intervene when engagement drops.
- Marketing teams keep tabs on metrics like social media engagement rate and click through rates to measure the effectiveness of campaigns, refine strategies, and target audiences more effectively.
- Product teams consider metrics like feature usage, DAU/MAU ratios, and retention rates to guide product improvements and prioritize feature development.
- Sales teams use metrics like email open rates, click-through rates, and website activity to identify leads who are showing interest and to prioritize outreach.
As insightful as these metrics can be, they don’t give any team a complete picture — there are always other metrics that need to be assessed in conjunction with engagement to ensure that teams are making sound judgments.
When customer engagement metrics are misleading
As helpful as these numbers can be, considering these metrics in isolation can obscure issues rather than clarify what’s going on.
For a marketing team, high click-through rates can be misleading if they are not leading to conversions. It’s crucial for the marketers to tie engagement to concrete sales metrics like new customers or larger average order value (AOV) in order to know what’s really contributing to company growth.
For customer success, relying too heavily on customer engagement metrics can cause the team to overlook underlying issues, such as poor product experience or unmet needs. Customers engaging frequently could still be dissatisfied — that happens all the time. A lack of qualitative data (like surveys and interviews) creates blindspots in the CS team’s analysis that make it impossible to address the root causes of why people are leaving.
How to Find And Apply 13 Customer Engagement Metrics
For each customer engagement metric listed below, you’ll find:
- A clear definition of the metric.
- A formula that explains how to calculate it correctly.
- A short guidance section that explains how to use the metric in conjunction with other data points to make smart choices that align with business goals.
After the list, I’ll run through any of the neighboring metrics and definitions referenced in the list.
1. Click Through Rate (CTR)
Definition: Measures how often users click on a specific link or ad.
CTR = (Clicks / Impressions) × 100
Guidance: A high click through rate indicates that customers are finding what they need and engaging. Depending on the link or ad, CTR can help you know if people are responding to your messaging strategy. A low CTR is a clear indicator that something is not working.
Along with CTR, you should look at the conversion rate. Are people actually taking the next step and signing up, making a purchase, or completing the action you really care about? High CTR with low conversion rate usually indicates a problem with your offer, or a mismatch between the copywriting that convinced people to click and the page they arrived at.
2. Session Frequency
Definition: Tracks how often users interact with an app, website, or platform over a period of time.
Session frequency = Total sessions / Total unique users
Guidance: If users visit often, they likely find value in your site or app. If their sessions drop, they may be losing interest. Just looking at the average session frequency obscures what’s really going on, though. Segmenting users by frequency helps you understand how power users engage compared to occasional users.
It’s also important to look at session frequency within the context of other metrics, like session duration, conversion rates, or data from customer support. For example, if an e-commerce site sees users returning often but not completing purchases, then something is off. Looking at engagement without conversions would obscure the problem.
3. Session Duration
Definition: Session time tracks how long users stay on a website or app before leaving.
Average Session Duration = Total Time Spent on Site / Total Sessions
Guidance: Longer session durations suggest that users are more engaged with the content or feature, spending more time exploring. Comparing session duration across different blog posts, for example, can help you figure out what topics or formats are most engaging for your audience.
Looking at conversion rates alongside session duration ensures that the additional time spent on a website is leading to productive business outcomes. It could just be that people are confused, or having more difficulty navigating the site.
It’s similar with apps — if users are spending more time in the app without progressing through workflows or achieving goals, it may point to usability issues or a lack of clear direction.
4. Social media engagement rate
Definition: Tracks user interactions on social media platforms, such as: likes, shares, comments, followers, and so on. You can certainly drill down into any of those specific metrics, but the standard way to look at social media metrics is with engagement rate.
Engagement rate = (Total interactions / Total impressions or followers) × 100
Guidance: Engagement rate is a useful way to figure out whether customers are engaging more often or more meaningfully, or whether you are growing surface-level engagement with a wider audience.
It’s up to you what counts as a “meaningful” interaction on a social media platform. Many brands count comments and shares as more meaningful than likes or raw follower counts. Tracking changes in engagement rate along with CTR and conversion rates can help you understand whether or not driving social shares is productive for your company.
It’s also true that a sudden spike in engagement rate could indicate controversy rather than success. Engagement bait content can certainly boost impressions and shares, but does it lead to actual value? And low engagement doesn’t always mean failure, especially if you are trying to appeal to niche audiences
5. Bounce rate
Definition: Bounce rate measures the percentage of visitors who leave a website without interacting further.
Bounce Rate = (Single-page Visits / Total Visits) × 100
Guidance: A high bounce rate indicates weak engagement. If users land on your page and immediately leave, then most likely the content didn’t meet their expectations or failed to capture their attention.
There isn’t an ideal bounce rate that holds true across industries, so you’ll have to figure out what the natural rate is for your site. Once you have a baseline, changes in the bounce rate can help you spot issues and opportunities. Spikes in the bounce rate, for example, indicate something’s broken or not resonating, causing people to disengage.
6. Feature usage
Definition: Feature usage tracks how often users interact with a specific function of a product, like a search bar or chat bot.
Feature Usage Rate = (Number of Users Who Use a Feature / Total Active Users) × 100
Guidance: Higher usage of features often indicates strong customer interest and satisfaction, while low usage may signal the need for improvement or more user education.
On its own, high feature usage rates may not reflect value or enjoyment for customers — it might be that they use it out of habit or have limited options. Similarly, low feature usage doesn’t always imply that a feature isn’t useful.
Getting survey data or other types of qualitative feedback adds context to feature usage, which can help teams understand whether engagement is really driven by satisfaction or confusion. You could also look at success/completion rates to get a better sense of whether users are achieving their goals with the feature, which may yield insights into its usability and value.
7. Pages per session (Session depth)
Definition: Pages per session measures the average number of pages a user visits during a single session before exiting.
Pages Per Session = Total Page Views / Total Sessions
Guidance: Higher values suggest users are exploring multiple pages, while lower values indicate poor engagement and potentially irrelevant content.
But context matters when it comes to session depth — if users are clicking excessively due to poor navigation, it may signal a usability issue. Pairing this metric with bounce rate, session duration, and conversion rate provides a fuller picture of user behavior.
For example, if your conversion rate is going up and the session depth is going down, it might signal that you are presenting people with exactly what they want — in this case the low pages per session metric indicates that your offer is appealing to visitors and aligned with their expectations coming from search, social, or paid ads.
8. Conversion Rate
Definition: Percentage of visitors who complete a desired action, such as signing up or making a purchase.
Conversion Rate = (Conversions / Total Visitors) × 100
Guidance: High conversion rates are a really healthy signal that you are attracting and engaging your target audience effectively. Low conversion rates are almost never good.
This is not always a customer engagement metric. When you are talking about conversions as purchases, you cross a boundary into sales/revenue metrics. That said, conversion rate is extremely useful for validating movement you see in the engagement data.
But earlier in the customer journey, when conversions are clicking on lead magnets, subscribing to newsletters, registering for webinars, or booking a product demo — these are clear signs that customers are engaging. Sign ups and completed forms are much more concrete customer engagement metrics than lower-effort interactions on social media.
9. Churn rate
Definition: Churn rate tracks the percentage of customers who stop using a service over a specific period.
Churn Rate = (Customers lost during period / Total customers at the start of period) × 100
Why It Matters: A high churn rate often reflects dissatisfaction and underlying issues with the site or product. Essentially, it’s a direct measure of the percentage of customers who stopped engaging altogether.
Looking at customer lifetime value (CLV) can help you understand the impact of churn on revenue. Segmenting users by CLV can also shed light on whether you are losing high-value users or those who are less likely to drive business growth.
Since retaining existing customers is generally more cost-effective than acquiring new ones, reducing churn is key for long-term business growth. By identifying patterns of disengagement and understanding why customers leave, companies can make strategic improvements to keep customers loyal and engaged.
10. Referral rate
Definition: Referral rate measures how many new customers are acquired through word-of-mouth or referral programs.
Referral rate = (Referred customers / Total new customers) × 100
Guidance: A strong referral rate indicates that existing customers find value in the product and are willing to advocate for it. It means customers are actively recommending your brand to others, and should build on any positive momentum.
Encouraging referrals through incentives can lower customer acquisition costs while strengthening brand credibility. Dropbox is a classic case study of hypergrowth through referrals, using the incentive of getting more free storage for referring new customers.
Just keep in mind that if you offer incentives for referrals, it’s important to track both the conversion rate of referred customers and the cost per acquisition (CPA). These metrics help you assess whether your referral program is driving real business growth, and ensures that the cost of incentivizing these referrals remains financially sensible.
11. DAU/MAU ratio
Definition: Daily Active Users (DAU) and Monthly Active Users (MAU) measure engagement by tracking how many unique users interact with a product within a given timeframe.
- DAU: Number of unique users active in a day.
- MAU: Number of unique users active in a month.
Engagement Ratio = DAU / MAU
Guidance: High DAU/MAU ratios indicate strong user retention and habitual engagement — key factors for business growth, especially for apps and SaaS products. A low ratio suggests users aren’t consistently finding value, which may require better onboarding or product improvements.
Some companies track Weekly Active Users (WAU) in order to get more granular data about changes in user activity.
When analyzing DAU/MAU ratios, consider metrics like feature usage, session frequency, and click-through rate, because they provide insights into how actively users interact with your product.
You should also segment active users to surface engagement patterns across different user groups (e.g. demographics or cohorts). This way, you can tailor the strategies you use to appeal to each segment and keep them engaged.
12. Re-Engagement rate
Definition: Re-engagement rate measures the percentage of previously inactive users who return after receiving targeted re-engagement efforts, like emails, push notifications, or special promotions.
Re-Engagement Rate = (Re-engaged Users / Total Inactive Users Targeted) × 100
Guidance: A high re-engagement rate indicates that outreach efforts are successfully bringing users back, reducing churn, and increasing CLV. If the re-engagement rate is low, it could mean that the messaging is off, incentives aren’t compelling, or the timing of the offer needs to be adjusted.
It’s hard to offer a useful benchmark for re-engagement rates, but you can find a baseline over time to assess whether your efforts are making a positive impact.
13. Customer Effort Score (CES)
Definition: CES measures how easy or difficult it is for customers to complete a task, such as resolving an issue or making a purchase. Customers rate the ease of their experience, typically on a 1-7 scale, with 1 being the most effort needed and 7 being the least.
CES = Sum of effort ratings / Total responses
Guide: The standard benchmark for CES scores is between 5.5 and 6. Anything in that range or above means it’s easy for customers to interact with a brand.
A low CES score suggests that customers are struggling, which leads to frustration, churn, and negative reviews. Treat it as an opportunity to run usability testing, figure out where users are running into issues, and fix those revenue leaks.
Analyzing customer engagement metrics in context
In this section, I wanted to cover the key metrics from revenue, sales, and customer support that I referenced while talking about how to analyze customer engagement metrics. Bringing this data is valuable because you can better understand the root causes of engagement and where it is having an actual impact on business goals.
If you want to know what the engagement numbers really mean, look at:
- Retention rate: Measures the percentage of customers who continue engaging over time. A high retention rate validates your engagement strategy, whereas a low retention rate signals a problem even when engagement looks healthy on the surface.
- Cost per acquisition (CPA): Measures the cost associated with acquiring a specific action, such as a lead or a sale. It provides insight into how well engagement strategies convert prospects into paying customers.
- Customer acquisition cost (CAC): Measures the total cost of acquiring a new customer, including all marketing and sales expenses. CAC helps businesses assess whether their engagement strategies are cost-effective in the long run.
- Customer Satisfaction Score (CSAT): Measures how satisfied customers are with a product, service, or interaction. It provides immediate feedback on specific customer experiences and can help identify strengths and weaknesses in engagement
- Net Promoter Score (NPS): Assesses customer loyalty by asking customers how likely they are to recommend a brand to a friend or colleague. A high NPS suggests strong word-of-mouth marketing and a solid customer base, whereas a low NPS indicates dissatisfaction and potential churn.
- Customer Lifetime Value (CLV): Estimates the total revenue a business can expect from a single customer over their entire relationship. The real benefit of looking at CLV comes with segmentation. Identifying your high-CLV segments and prioritizing engagement with them is valuable, whereas low-CLV buyers need to be reached with less expensive, lower-touch methods.
Along with those metrics, you also want to segment your engagement data to surface patterns in how specific groups interact with your brand. Here are some of the best factors to bring into your analysis:
- Customer demographics: Age, location, job title, and other demographic traits provide valuable context for understanding engagement behaviors across different user segments.
- Customer psychographics: Factors like customer interests, values, lifestyle, and motivations offer deeper insights into user behavior. Understanding psychographics helps tailor content and messaging to resonate with different customer segments on a more personal level, driving better engagement.
- Traffic Sources: Shows where users are coming from — organic search, social media, paid ads, etc. — which can help you find engagement patterns, decide which channels are worth focusing on.
- Devices and Browsers: Shows how engagement varies between mobile and desktop users, which is critical for finding accessibility issues or where your site falls short of basic UX benchmarks.
- Time of Day/Week Activity: Reveals when users are most active, providing insights into peak engagement times. This helps in planning content delivery, marketing outreach, and feature updates for maximum reach and impact.
How to track customer engagement metrics
Customer engagement data lives in a few different places and tracking it usually involves a combination of platforms and tools.
Web analytics platforms (e.g. Google Analytics) track user actions, page views, and feature usage, providing businesses with data on how users interact with their websites and apps. Similarly, in-app analytics tools (e.g. Firebase), offer detailed data on feature engagement within mobile apps or SaaS products, helping companies understand user activity and refine their products
Social media management platforms (e.g. Hootsuite) track likes, shares, comments across various channels and social networks, revealing how engaged customers are with the brand. Email marketing services (e.g. Mailchimp) calculate metrics like open rates and CTR, helping companies see the effectiveness of individual campaigns.
Companies may also use customer relationship management (CRM) software (e.g. HubSpot) to consolidate these various data sources and track other forms of customer engagement, such as phone calls, meetings, support tickets, and purchase history.
