SaaS Metrics That Matter: A PM’s Guide to Data-Driven Decisions

Why Most Startups Fail (And What Metrics Have to Do With It)

You can spend months building something you’re proud of, only to realise no one really needed it. That’s the reality in most startup failures.

It’s not because the team didn’t work hard, but they targeted the wrong things. More often than not, they were tracking the wrong metrics.

Numbers like total sign-ups or page views might look impressive in a report, but they don’t show whether people care about what you’ve built. More importantly, they don’t tell you if the business is sustainable.

As a product manager, data shapes your decisions. But not all data is useful. The real advantage comes from knowing which metrics reflect actual progress.

What You’ll Get From This Guide

This guide focuses on the numbers that matter. They show whether your product is working and if it’s worth continuing to invest in.

You’ll learn:

• The essential metrics every product team should track

• What these numbers reveal about user behaviour and product fit

• How teams at Slack and Amazon used this metrics to guide their growth

• The most common mistakes, including chasing after metrics that lack substance or drawing the wrong conclusions from early signals

Whether you're launching your first version or growing something that already exists, the same risk applies.

It doesn’t matter how clever your product is or how much effort you’ve put in. If you’re tracking the wrong things, you’ll make decisions that pull you further from what your users needs. You might think you’re making progress when you’re in the wrong direction.

The Metrics That Actually Matter for Your SaaS Product

Something I realised early in my product journey, and the hard way, is that not all metrics are equal. Some drive progress while others just look good but offer little value.

The key difference comes down to vanity metrics versus actionable metrics. Spotting this early can save you from chasing the wrong numbers.

The Seduction of Vanity Metrics

We’ve all been tempted by vanity metrics. The big, impressive numbers that look great in reports but do little to improve the product. It’s like counting gym memberships instead of tracking who’s actually working out.

The Vanity Metric Trap

It’s easy to chase the wrong milestones:

• "10,000 sign-ups!" But how many are actually active?

• "1 million page views!" Are users engaging with what they see?

• "50,000 downloads!" Do they keep using the product after the first day?

These numbers give the illusion of growth. They offer a dopamine hit, not a sign of lasting success. That spike feels great until you realise most users never came back after their first visit.

The Power of Actionable Metrics

Actionable metrics help you understand what’s working and what to improve. Here’s why they matter:

1. They guide your next step (if activation is low; you know it's time to fix your onboarding).

2. They tie back to business goals like retention or revenue.

3. They reflect real user behaviour, not just potential interest.

Take the activation rate. It measures how many users reach the "aha moment" with your product.

Slack used this to track how many teams sent 2,000 messages. That became their benchmark for activation and a powerful predictor of long-term retention.

Other SaaS teams have done similar things, zeroing in on the actions that matter for their product's success:

• Trello: Users who created at least one board in their first week were more likely to stay.

• Dropbox: Saving one file early on signalled long-term use.

• Zoom: Hosting a meeting in the first week predicted repeat usage.

Each team focused on real user behaviour to define early success and shaped onboarding to drive it.

How Your Key Metrics Should Evolve With Your Business

One of the biggest mistakes teams make is using the same metrics from launch all the way through to scale. As your product grows, your metrics need to evolve too.

Stage 1: Finding Product-Market Fit (0-1k users)

When you're just starting out, your entire focus should answer one burning question:

Are we solving a real problem for real people?

At this stage, you should:

• Track engagement depth over user count (10 passionate users beat 1,000 passive signups)

• Measure frequency of use - are people coming back without being pushed?

• Collect feedback like your life depends on it (why they stay, why they leave)

As the Lean Startup teaches us, this is your validation phase. I've seen too many teams waste months trying to scale before proving anyone wants their product.

Stage 2: Growth (1,000–10,000+ users)

Once you've nailed product-market fit, the next question is:

Can this grow into a healthy business?

That means shifting your focus to a few key metrics that show whether your growth can last.

Here's what to watch:

1. Churn Rate: How many customers leave each month. If 5 out of 100 users leave, that's 5% churn. High churn means you're constantly replacing users just to stay level.

2. Customer Acquisition Cost (CAC): How much it costs to acquire one customer. Spend £10,000 and gain 100 customers, and your CAC is £100.

3. Lifetime Value (LTV): How much revenue a customer brings over time. If someone pays £50 per month and stays for 10 months, LTV is £500.

LTV should be well above CAC. If not, you're spending more to get users than they’re worth. Without this balance, growth burns cash instead of building a business.

One More Thing: LTV to CAC Ratio

Once you're tracking CAC and LTV, the next step is to understand how they relate. That’s where the LTV to CAC ratio comes in. It shows how well you're turning marketing spend into long-term value.

Here's the breakdown that'll save you a lot of headaches:

• Under 1:1: You're losing money.

• 1:1 to 2:1: Barely breaking even.

• 3:1: A strong balance of growth and margin.

• Over 4:1: You are spending too little and growing slowly.

As a rule of thumb, aim for a 3:1 ratio. It offers a healthy mix of return and reinvestment.

Why Slack Focused on Daily Active Users

Sign-ups mean nothing if users don’t return. I’ve seen teams celebrate big numbers, only to find most people never came back. A sign-up only shows curiosity.

Slack understood this early. They focused on Daily Active Users, the ones who kept showing up and using the product.

What is a DAU?

A Daily Active User is someone who logs in and takes meaningful action within 24 hours.

They don’t just open the app and leave. They send a message, create a task, or save a file.

As a product team, you define what counts as 'active' based on how your product is used.

DAU shows how many unique users take useful action each day. It’s a stronger sign of engagement than traffic or sign-ups.

What matters is whether they come back the next day. If they do, your product is becoming part of their routine. That’s when you know you’re on the right track.

Slack saw the same pattern. Teams either used it regularly or stopped altogether. That insight helped them focus on what mattered.

They made Daily Active Users their core metric because it showed whether the product was easy to get started with, useful in daily work, and valuable enough to return to.

DAU helped them answer key questions:

1. Which features brought people back.

2. Where users were dropping off early.

3. Whether teams were getting enough value to keep using it.

How DAU Drove Product Decisions for Slack

The team used Daily Active Users to guide key decisions:

• Redesigned onboarding to help teams start messaging right away

• Tuned notifications to be useful without becoming a distraction

• Built features like threads and shared channels to deepen engagement

Every decision came back to one simple question:

Will this help people use Slack every day?

This focus helped the team to:

• Remove features that created friction.

• Improve the ones users depended on.

• Stay aligned with Slack’s mission to make work simpler, more pleasant, and more productive.

The Essential SaaS Metrics Every Product Manager Should Track

As a Product Manager, your dashboard can feel like a cockpit. It's packed with numbers, graphs, and alerts. But with so much data in front of you, it’s easy to lose sight of what really matters.

I looked at how successful SaaS teams make decisions and found a common pattern. They focus on a few core metrics that link directly to growth, retention, and revenue.

Let’s break them down.

A) Acquisition Metrics: Turning Strangers Into Users

A-1) Sign-up Rate

Definition: The percentage of visitors who create an account.

Why it matters: It’s your top-of-funnel health check. A low sign-up rate means your messaging or UX is broken.

How to calculate:

How a Basic Video Lifted Dropbox’s Growth

Dropbox increased sign-ups by 10% by adding a short explainer video to their homepage. It showed the product in real situations, like sharing files with a team or accessing documents on the move.

That slight change made a big impact. It cleared up confusion and helped people understand the value immediately. It’s a reminder that showing how your product fits into real life can lead to stronger results.

A-2) Cost Per Acquisition (CPA)

Definition: How much you spend to gain one customer.

Why it matters: If CPA exceeds customer lifetime value (LTV), you’re burning cash.

How to calculate:

How HubSpot Replaced Paid Ads With Something Even Better

HubSpot spotted a problem early on. Paid ads were eating into their margins, and the numbers were heading in the wrong direction. So they made a sharp pivot.

Paid Ads Were Becoming Unsustainable

• Cost per acquisition kept rising

• The LTV to CAC ratio slipped

• Each new customer cost more than the last

• For a subscription model was unsustainable

Why HubSpot Chose Organic Growth

When HubSpot changed their approach, they shifted focus from paid ads to SEO and content marketing. It was a risky move that could have backfired.

But HubSpot had something clever up their sleeve. The plan was to use their own tools to prove they worked, becoming their own best case study.

Building Content That Mattered

The company began publishing content that tackled problems their customers faced. They also created guides, templates, and free tools that people genuinely wanted to share.

By offering something useful, they earned backlinks organically without paying for shady link farms.

Making Every Piece Count

Every blog post, guide, or template had a purpose. Someone might read an article about email marketing, then want to try their email tool. Or visitors would download a template and realise the full software was needed to make the most of it.

The team tested different calls-to-action. Buttons like "Start Free Trial" or "Download Now" were shown in multiple versions to see which ones got the most clicks.

Using Their Own Medicine

HubSpot used their own analytics platform to track what was working. When a piece of content performed well, they doubled down on that approach. When something fell flat, they dropped it and tried a new angle.

This removed the guesswork. Data showed exactly where to focus. Over time, HubSpot built what business people call a "moat", an edge that made it extremely hard for rivals to compete.

Key outcomes:

• Customer acquisition costs dropped by 30% - more customers for the same spend.

• Higher quality leads from organic searchers who were serious about buying.

• Long-term traffic that kept delivering results without ongoing ad spend.

The organic traffic built became like a money-printing machine that kept working even without active spending.

B) Activation & Engagement Metrics: Are Users Hooked?

B-1) Activation Rate

Definition: The percentage number of users who hit their "aha moment" (e.g., first key action). That shows they’ve understood the core value of your product.

Why it matters: If users don’t activate, they’ll churn.

How to calculate:

How Twitter Kept New Users Hooked

Twitter found that new users who followed at least five accounts in their first week were much more likely to stay active. The data showed that a busy feed made the platform feel useful and worth returning to, while a quiet one often led people to leave.

To fix this, Twitter redesigned its onboarding. It encouraged users to follow more accounts through personalised suggestions and trending profiles. This improved retention and showed just how important early engagement is for long-term growth.

B-2) Daily/Monthly Active Users (DAU/MAU)

Definition: Users who engage daily (DAU) or monthly (MAU).

Why it matters: Measures habit formation - the core of sticky products.

How to calculate:

How Slack Became the App Everyone HAD to Use Every Day

When Slack launched in 2013, they paid close attention to who kept coming back each day.

The metric that worked

• 42 million people opened Slack every day at its peak.

• Over 50% of monthly users returned every day (DAU/MAU > 50%).

• Average session length hit 90 minutes, longer than most social apps.

Why DAU mattered more than anything else

Dependency

• Teams at IBM, Amazon, and Airbnb relied on Slack.

• Email traffic fell 32%.

• Meetings fell 27%.

Organic growth

• New hires asked to be added to channels.

• Adoption spread through use, not campaigns.

Market ripple

• Microsoft Teams and Google Chat copied Slack’s experience, not the other way round.

Exit value

• Salesforce paid £27.7 billion for a daily habit, not just a messaging app.

C) Retention & Churn Metrics: Keeping Users for Life

C-1) Customer Retention Rate

Definition: The percentage number of customers who stay over a period.

Why it matters:

• Lower cost: Retention is 5 to 25 times cheaper than acquiring new customers.

• Easier sales: Existing customers buy more often with personalised engagement.

• Higher revenue: Repeat purchases boost lifetime value, with 60–70% conversion rates compared to 5–20% for new leads.

How to calculate

Why Cancelling Prime Feels Like Breaking Up With Your Family

Amazon Prime has cracked the code on customer loyalty - they keep 99% of their members after two years. Here's how they've been able to do it:

• Prime’s family sharing turns one account into a household habit.

• Each person gets a perk: favourite shows, free delivery, or music.

• Cancelling means telling your partner the series stops.

• The more people rely on it, the harder it is to walk away.

C-2) Churn Rate

Definition: The percentage number of customers who stop using your product in a set period.

Why it matters:

• High churn cancels out growth, no matter how good your acquisition is.

• It signals product, onboarding, or support issues that need fixing.

How to calculate:

How Groove Turned Failing Users Into Loyal Customers

Groove was getting steady signups, but their 4.5% monthly churn rate was quietly killing their growth.

To understand why users were leaving, they watched closely what happened in the first 10 days. The data revealed two red flags they had missed:

• Most first sessions lasted less than 2 minutes

• Users weren’t coming back after that first visit

Early action

Groove began sending targeted emails to users who showed signs of struggling. Instead of generic advice, they offered specific, useful tips and help like “Need a hand? We’ll walk you through setup.” They tailored support to real user behaviour without making assumptions.

Onboarding to the rescue

They also built support on the onboarding journey. By stepping in early, they kept users engaged and reduced churn.

Immediate results

The results were staggering:

• Over 40% of those "saved" users stayed active past 30 days.

• Key user segments saw a 71% drop in churn.

• Growth came from retention - both new and existing customers kept coming back.

D) Revenue Metrics: The Lifeblood of Your Business

D-1) Monthly Recurring Revenue (MRR) & Annual Recurring Revenue (ARR)

Definition: The steady revenue you earn from subscriptions, whether monthly (MRR) or yearly (ARR). Not one-off sales, but income you can rely on again and again.

Why it matters:

• This is your growth heartbeat - MRR/ARR tells you if your business is actually growing, plateauing, or declining.

• It helps you plan with confidence: hiring, spending, and investing are all easier when you know what’s coming in.

• It gives you a clearer picture of product-market fit. If MRR is steadily growing and churn is low, you’re on the right track.

How to calculate:

The New York Times’ Subscription Shift

In 2011, The New York Times put up a paywall. Critics called it business suicide mission and avid readers even threatened to leave.

But here's what happened after the dust was settled:

• Value stacking increased retention: Each product added a new reason to stay, making it harder to leave.

• No reliance on ads: Focus shifted to content users will pay for.

• Stronger signals: Monthly revenue gave a clear view of growth and allowed faster decisions.

• Financial stability: ARR gave them the confidence to make bold moves, like acquiring The Athletic for £550 million.

• A compelling bundle: By 2024, they reached 10.8 million digital subscribers across News, Games, Cooking, Wirecutter, and more.

D-2) Average Revenue Per User (ARPU)

Definition: Revenue generated per customer.

Why it matters:

• Helps to improve pricing tiers.

• Shows if users are upgrading, downgrading, or if certain segments bring in more value than others.

How to calculate:

How Spotify Turned Listeners Into Paying Customers

In its early days, Spotify had strong user growth, but not all users held the same value. Free accounts generated ad revenue. Premium subscribers paid full price. Discounted plans like family and student offers improved retention but brought in less per user.

The real turning point came when Spotify shifted its focus from chasing new sign-ups to understanding the true value of each user.

Here’s what they did:

Optimised the mix: Instead of just growing user count, they focused on shifting the right users into higher-value buckets. ARPU rose without huge spikes in user growth.

Followed the money: Premium users brought in significantly more revenue per person than free users relying on ads.

Refined their upgrade strategy: Free users got trial offers based on listening habits. Solo subscribers were nudged toward Family plans. Advertisers got better targeting to lift ad revenue.

E) Expansion & Referral Metrics: Growing Without Burning Cash

E-1) NPS (Net Promoter Score) – The Ultimate Loyalty Litmus Test

Definition: NPS measures how likely your customers are to actively recommend your product to others on a 0-10 scale.

Why It Matters:

• Predicts growth: Promoters (9-10 scores) drive 80% of referrals

• Exposes risks: Detractors (0-6) are churn bombs waiting to explode

• Benchmarks performance: Compare against industry standards

How It Works:

Ask: 

“How likely are you to recommend us to a friend?”

Categorise:

• Promoters (9-10): Your evangelists

• Passives (7-8): Satisfied but indifferent

• Detractors (0-6): At risk of leaving (or worse, bad-mouthing you)

How to calculate:

Calendly Solved a Problem So Annoying, It Sold Itself

Back in 2013, scheduling meetings was pure chaos: endless emails, crossed wires, and hours lost to sheer admin hell.

Then Calendly showed up with a simple fix, and something wild happened:

Users obsessed over it!

• Colleagues encouraged colleagues to use it.

• Recruiters preferred candidates to book through it.

• Teams adopted it bottom-up, without a manager’s mandate.

For years, Calendly's NPS sat at an impressive 70 – outstanding for SaaS. Now at 50, it still leads the pack, proving customers happily recommend it.

Why NPS Worked

• Word of mouth in action: 70% of new signups came from user-shared links, slashing CAC.

• Guided product growth: Promoters (9–10) highlighted strengths; detractors (0–6) exposed flaws.

• Sustained organic growth: Ads became optional. Happy users drove referrals, and churn stayed low as the product became habit.

E-2) Virality Coefficient

Definition: The average number of new users each existing customer generates.

Why it matters: 

• Scales itself: Users do the sharing, reducing ad dependence.

• Multiplies over time: Each wave of invites brings new users.

• Proves demand: People only share what they truly value.

How to calculate:

Key Points

• Viral coefficient > 1: Exponential growth - your product spreads fast.

• Viral coefficient < 1: Growth isn’t viral; referrals won’t keep your user base growing on their own.

How Dropbox Turned File Sharing Into a Growth Machine

In 2008, Dropbox cracked the code on viral growth by making cloud storage so useful, people couldn't help but share it.

They made everyone a winner

Most referral programs only reward the person doing the inviting. Dropbox was different - when you invited a friend, you both got 500MB of free storage. You and your friends naturally became their sales rep through their reward program.

Sharing reduced friction

Sharing was baked right into using Dropbox. Users didn't need to fill out forms or hunt for coupon codes. If they wanted to share a file, all they had to do was click, invite and done. The reward happened automatically.

The numbers were insane

The average user sent out 4 invites, and half of those people signed up. That meant every new user brought in 2 more users, which created a snowball effect.

Dropbox exploded from 100,000 to 4 million users in just 15 months. Seven out of ten new sign-ups came from referrals, which meant their cost of acquisition plummeted to nearly zero.