Engagement scoring: Quantifying user value

You know that sinking feeling when you look at your analytics dashboard and see DAU/MAU trending down, but you have no idea why? Or worse - the metrics look fine, but customer churn is through the roof.

The truth is, traditional engagement metrics often miss what actually matters. They tell you how many people logged in, but not whether they found value, hit roadblocks, or are about to cancel. That's where engagement scoring comes in - a way to actually measure if users are getting value from your product, not just clicking around.

Understanding the importance of measuring user engagement

Let's be real: user engagement is the lifeblood of any SaaS business. It directly impacts how long customers stick around and how much they're worth to your business. But here's the thing - most companies are terrible at measuring it.

Sure, you can track daily active users divided by monthly active users. But what does that really tell you? A user who logs in every day to export a single report isn't engaged - they're trapped. Real engagement means users are finding value, exploring features, and integrating your product into their workflows.

This is where engagement scoring models shine. Instead of looking at surface-level metrics, they dig into the behaviors that actually matter for your specific product. Think of it as the difference between counting how many times someone visits a gym versus tracking if they're actually getting stronger.

The team at Lenny's Newsletter found something fascinating: focusing on optimizing existing features drives more growth than constantly shipping new ones. They developed the ARIA framework to systematically improve engagement:

• Analyze which features actually move the needle

• Reduce friction in the user experience

• Introduce features at the right moment

• Assist users when they get stuck

Another powerful approach? Content-driven growth strategies. Companies like HubSpot and Intercom didn't just build great products - they created valuable content that attracted their ideal users. But fair warning: this isn't a quick win. It takes years to pay off, which is why most companies give up too soon.

Quantifying user engagement: scoring models and key metrics

So how do you actually build an engagement score? There are two main approaches that work well.

Customer Engagement Score (CES) tracks how often users perform key activities and weights them by importance. Picture this: completing onboarding might be worth 10 points, while daily logins are worth 1. The Reddit SaaS community has found this particularly effective for identifying users about to churn - their scores start dropping weeks before they actually cancel.

Product Engagement Score (PES) takes a broader view. It combines three critical factors:

• Adoption (are people using core features?)

• Stickiness (do they come back?)

• Growth (are they expanding usage?)

Here's what most people miss: the specific metrics don't matter as much as consistency. Pick measurements that reflect how YOUR users get value. For a project management tool, that might be tasks completed. For an analytics platform like Statsig, it could be experiments launched or feature flags deployed.

The key metrics to track will vary, but typically include:

• Feature adoption rates (which features hook users?)

• Session duration and depth (are they exploring or bouncing?)

• Time to value (how quickly do new users hit "aha" moments?)

• Activation rate (what percentage reach that first success milestone?)

One thing that's crystal clear from analyzing product usage patterns: you need to look beyond averages. Your power users might be thrilled while 80% of signups never activate. Segmenting by engagement level reveals these hidden patterns.

Implementing engagement scoring in your product

Alright, let's get practical. How do you actually build this in your product?

First, define what engagement means for YOUR users. This isn't about copying what worked for Slack or Notion. Sit down with your team and ask: what behaviors indicate a user is getting value? When someone becomes a power user, what did they do differently?

Start simple. Pick 3-5 key events that matter:

• Core feature usage (the thing that delivers your main value prop)

• Repeat visits within a time window

• Depth of usage (how many features they explore)

• Collaboration indicators (inviting team members, sharing work)

Now comes the tricky part - weighting these events. Not all actions are created equal. Opening the app daily means nothing if users never complete meaningful work. This is where tools like Statsig's analytics platform help - they let you experiment with different weightings and see which best predict long-term retention.

The ARIA framework from Lenny's Newsletter is gold here. Start by analyzing which features your most successful users love. Then ruthlessly reduce friction - every extra click is a chance for users to give up. Time your feature introductions carefully (nobody needs to see every feature on day one). And please, actually help when users get stuck instead of hiding behind a chatbot.

Here's what trips up most teams: they set up engagement scoring once and forget about it. User behavior evolves. New features ship. Competitors change the game. Your engagement model needs regular tune-ups, just like any other part of your product.

Leveraging engagement scores for strategic growth

Now for the fun part - using these scores to actually grow your business.

Segmentation is your secret weapon. Break users into groups based on their engagement scores:

• Champions (top 20%): These folks love you. Time for upsells and case studies.

• Regular users (middle 60%): Focus on deepening their usage.

• At-risk users (bottom 20%): Intervention time before they churn.

Each segment needs different treatment. Your champions might be ready for annual plans or add-ons. At-risk users need proactive outreach - maybe they're stuck, or maybe your product isn't the right fit. Either way, you'll learn something valuable.

The Reddit SaaS community discovered something powerful: engagement scores predict churn weeks in advance. When someone's score drops 30% month-over-month, they're probably shopping for alternatives. That's your cue to reach out with helpful resources, not desperate discount offers.

Use engagement data to guide product development. Which features correlate with high engagement? Double down on those. Which features do engaged users ignore? Maybe they're not as important as you thought. This data-driven approach beats endless debates in product meetings.

Onboarding deserves special attention. Track engagement scores during users' first week - you'll quickly spot where people get stuck. As Lenny's data shows, reducing early friction and showing value faster dramatically improves long-term engagement. Small tweaks here compound over time.

Finally, let engagement scores inform your content strategy. What topics resonate with highly engaged users? What questions do struggling users ask? Create content that addresses these needs, and you'll attract more of your ideal customers while helping existing ones succeed.

Closing thoughts

Building effective engagement scoring isn't about perfect formulas or complex algorithms. It's about understanding what makes your users successful and measuring whether they're getting there.

Start simple. Pick a few key behaviors, track them consistently, and use the insights to help more users succeed. Whether you're using basic analytics or a platform like Statsig, the principles remain the same: measure what matters, act on what you learn, and keep iterating.

Want to dig deeper? Check out:

• Lenny's guide to the ARIA framework for optimizing features

• Community discussions on engagement scoring from SaaS operators

• Practical examples of usage analytics in action

Hope you find this useful! Remember - the best engagement model is the one you actually use. Start somewhere, learn as you go, and your users (and metrics) will thank you.