AARRR: Come Aboard the Pirate Metrics Framework

Set sail for product-led growth with the five-stage AARRR framework.

Best Practices
January 19, 2024
Image of Noorisingh Saini
Noorisingh Saini
Global Content Marketing Manager, Amplitude
paper boat sailing across water water

AARRR is an acronym for acquisition, activation, retention, referral and revenue. Also known as the “pirate metrics,” it’s a framework used by startups to drive product-led growth.

Entrepreneur, investor, and startup advisor Dave McClure introduced the concept of pirate metrics at a time when product roadmaps and philosophies were chaotic or subjective. This framework, which stands for acquisition, activation, retention, referral, and revenue, is also called the “pirate metrics,” given the acronym’s similarity to the classic pirate exclamation—“aarrr, matey!”

While this framework has nothing to do with swashbuckling, it does channel a pirate’s daring entrepreneurial spirit into an orderly, measurable sequence of well-defined stages, funnels, and loops that support product-led growth.

Most importantly, it trains you to examine how users interact with your product at all stages. Organizations rely on this framework to help prioritize product development around business goals instead of more subjective or arbitrary considerations.

Key takeaways
  • AARRR stands for acquisition, activation, retention, referral, and revenue.
  • You can use the AARRR framework to guide and direct your brand’s marketing activities. You can better meet their needs by adjusting specific strategies and tactics based on the user's journey.
  • The framework provides product teams with information to make data-driven decisions and achieve product-led growth. It also helps teams identify the most effective metrics to measure at each part of the framework via an analytics tool.
  • Startups benefit most from the AARRR pirate metrics framework, where scalability is often an afterthought to building a great product. Instead, McClure argues that you should prioritize scalability and monetization at the outset of product development.

What is the AARRR framework?

The AARRR framework helps product teams leverage analytics to drive their strategy to develop and test their product usage/growth hypotheses.

According to McClure, a company should seek to solve a customer’s problem, monetize the solution, and generate more revenue than it costs to construct or provide it.

AARRR provides an experimentation framework to help teams effectively prioritize and sequence product development activities:

  1. Build a product to a functional or sellable prototype level.
  2. Demonstrate you can acquire customers.
  3. Demonstrate you can acquire them profitably and ideally at scale.

The AARRR acronym stands for:

AARRR acronym written out
  • A: Acquisition metrics identify the initial user entry points for engaging with your product or service. You can use the derived data to determine the success of marketing campaigns and strategies.
  • A: Activation metrics measure how effectively users move from curiosity in the acquisition stage to understanding how your product or service provides them value.
  • R: Retention metrics illustrate stickiness by showing how many users return to your product over a period of time. Understanding retention is vital for any growth-focused company—it doesn’t matter how many customers you’ve acquired if they abandon the product or service after first use.
  • R: Referral metrics gauge how many users become “net promoters” or evangelists due to the high value they derive from your product. Referrals can happen organically or as a result of company-designed incentives or programs.
  • R: Revenue metrics demonstrate how and how well your company turns engaged users into paying customers.

AARRR pirate metrics with examples


There are many ways to acquire users, but the most desirable channels are high-volume, low-cost, and high-performing. Marketing teams can adjust channels, campaigns, copy, graphics, or design to determine their acquisition sweet spot.

Teams should also consider their campaign theme, brand promise, or call to action (CTA) and its relevance to their target audience segment and channel source.

Examples of acquisition metrics include:

  • Number of new signups or qualified leads: This measures high-intent users likelier to convert to customers.
  • Customer acquisition cost (CAC): Measures how much your company spends to turn somebody into a customer.


The goal of activation is to get users to discover the value of your product or service—”aha” moments where initial exploration transforms into true engagement. You can assess engagement via time on site, the number of page views, the number of clicks, or specific actions taken.

An oft-cited example of activation comes from Facebook. Early on, the social media giant discovered that users who gained seven friends within the first few days of account creation quickly realized the social media network’s value. Gaining seven friends was Facebook’s “aha” moment and became an effective activation measure.

Investigating behavioral cohorts can reveal how “aha” moments differ among segments. This can inspire product adjustments so users experience these moments sooner, before user drop-off.

Activation metrics include:

  • Activation rate: The rate users find their “aha” moment. This indicates that the customer has oriented themselves with the product and what it can offer them.
  • Time to activate: The time it takes to move users through the onboarding flow from acquisition to activation.
  • Free-to-paid conversions: The number of users who convert from free trials to paid subscriptions.


All product teams want to avoid a “leaky funnel,” where users convert, often with some cost, but then quickly abandon the product or service.

A self-service digital analytics platform like Amplitude can enable granular views of user retention. Teams can specify starting and return events to evaluate usage over customizable intervals.

Retention metrics include:

  • Retention rate: How often users return to engage with your product.
  • Churn rate: The inverse of your retention rate, churn rate measures how many users stop returning to your product.
  • Customer lifetime value (CLV): Indicates the value of a customer across their entire relationship with your company. Lifelong, frequent customers provide more value to a business than one-time customers.


Referrals are like sought-after pirate treasures. Referring users are so satisfied with your product that they help you acquire new customers with little to no expense to the company.

In product-led growth, word-of-mouth and other referrals can generate viral growth loops that can exponentially expand your user base. This organic promotion can massively drive growth without additional resources or investment.

But you can also engineer referrals. For example, Dropbox enjoyed massive success by offering increased free storage to users in exchange for referrals.

McClure advises product teams to pay attention to referral behaviors that successfully result in new customer acquisition since some cohorts can refer without much effect. Capturing word-of-mouth referrals can be hard to measure, making referrals hard to quantify. However, campaigns that include referral promotions can hint at the level of community promotion.

Referral metrics include:

  • Number of invites shared by active users: The number of invites sent by your active users to their networks. This metric helps you determine how widely the offer spreads in the community.
  • Recipient conversion rate: The number of people invited to engage with your product or service who successfully sign up for a free trial or paid subscription.


Revenue is the most critical accountability metric. Marketing campaigns or product updates may increase acquisition or activation moments, but monetizing the resulting user engagement is the ultimate goal.

If that monetization doesn’t occur, your team might focus on boosting traffic and activation with a different segment or behavioral cohort.

To determine if your product is creating profitable growth, you’ll want to look at minimum, break-even, and revenue exceeding your users' acquisition costs.

Revenue metrics include:

  • Net revenue retention (NRR): The revenue you retain over a given period, usually measured monthly.
  • Monthly recurring revenue (MRR): Measures your monthly predictable, regularly recurring revenue.
  • Average revenue per user (ARPU): The revenue your company generates per user.

How does the framework work?

The AARRR framework discourages product teams from over-developing features—instead, they should devote 80% of their efforts to existing feature optimization and 20% to new feature development.

This approach, which is now fairly commonplace, suggests that companies should start with a hypothesis, then A/B test extensively, measure conversion improvements, and repeat the process over and over, hopefully developing more robust hypotheses along the way.

To truly adopt a data-driven strategy, teams should assess results through a quantitative, qualitative, comparative, and competitive lens. This means tracking usage and conversion numbers or percentages, studying behavioral cohorts, comparing user behaviors in different scenarios, and tracking competitor activities.

Thankfully, the cost of building experiments and acquiring customers has decreased, meaning product or growth hypotheses can be validated or disproven more quickly. The goal is to avoid developing vanity metrics that can create aesthetically pleasing graphs but don’t provide any real insight.

But you can steer clear of fool’s gold using analytics tools that enable you to granularly define and measure what constitutes a daily active user (DAU). If your product team takes DAU at face value as a sign of smooth sailing, they may overlook important factors.

There could be a short-lasting wave of PR-driven user registrations, and many of those users might never return. Or, those users might not take the actions that lead to your product’s “aha” moments and long-term retention.

Product teams must think in terms of loops, not just funnels. For example, imagine a music streaming service advertising a popular artist’s new release:

  • A curious user creates a free account in which song selection is limited, and ads interrupt playback.
  • After listening to the new release, the user continues exploring the service, discovers the user-curated playlists, and enjoys the app's personalization via the algorithm.
  • The user tires of ads and purchases the full subscription. The user is introduced to more content in the platform, like suggested albums based on their preferred genre, continuously driving engagement.
  • The user shares playlists with friends, creating new users whose own curiosity drives them to explore the platform, and the cycle begins anew.

If they haven’t already, your product team might directly add functionality to promote referrals—a simple button to share a product or platform invite easily can do wonders. Incentive programs, such as mutual discounts when a customer converts a peer, are also popular. Executing a cohort analysis or conducting direct customer interviews can also illuminate critical factors influencing a product user to become a product evangelist.

Who should use the AARRR framework?

McClure designed the framework for the startup world, where everyone should be a pirate. He noticed that teams at young companies could build great products that aren’t necessarily scalable or monetizable—because many founders are more preoccupied with features than financials.

The AARRR framework helps reprioritize efforts to solve user problems to, in turn, meet the business’s needs. And that lesson can be practical for any organization, regardless of size or growth stage.

Too often, companies model themselves after outliers with runaway user adoption. Instead, McClure argues, organizations should employ a rational framework for growth. Product managers should focus on sticky and unique features that inspire conversions. Furthermore, repeat purchases and retention are the ultimate product validation since initial payment often just reflects effective marketing.

Understanding the AR funnel

To optimize your product, you should deeply understand customer behavior across every point of their journey. Doing so allows you to collect rich data to identify problem touchpoints to inform resource allocation.

Basic AARRR model example

Let’s imagine you have a business called “Make Believe”—a startup software company looking to grow quickly.

Acquisition stage

You create interest in your product by maximizing engagement on various channels. To do so, Make Believe designs a blog to capture search engine optimization (SEO) keywords related to its offering and boosts the blog on various social media channels.

To determine the effectiveness of this outreach, Make Believe uses metrics like click-through rate, cost per thousand (how much the company paid for 1,000 online views or impressions), and customer acquisition cost.

Activation stage

Determining what drives your “aha” moment users is essential because this is where Make Believe will begin onboarding new users. They determine that the initial marketing campaign attracted thousands of curious potential customers, but they needed to see how many people successfully signed up for the product.

To do so, they look at metrics such as activation rate or the number of free-to-paid conversions to hone in on the events or sources that generate the most follow-through.

Retention stage

It’s not enough to have users implement Make Believe’s solution into their business—they need to keep using the product. Retention is what will prove the product’s value and drive monetization.

To gauge this, Make Believe looks at retention rate and its inverse, churn rate. To predict anticipated revenue, they also look at CLV.

Referral stage

Make Believe wants to ensure their product and accompanying promotional content is as easy to share as possible. They determine that this and rewarding loyalty through promotions will drive referrals—effectively “free” promotions for the company.

To measure referral, Make Believe evaluates the number of “shares” across various social media channels and the number of signups with a promotional code offered to referrals from their power users.

Revenue stage

The bottom line will ultimately reflect customer satisfaction. Make Believe discovers it can drive revenue by offering annual subscriptions with discounts and promotions.

They evaluate metrics such as net revenue retention and monthly recurring revenue to determine how efficiently they allocate resources.

Use pirate metrics to right the ship with Amplitude

If you’re looking to scale, a comprehensive understanding of your customer’s behavior will be your most essential tool. Using metrics to determine what is and isn’t working at each stage of the AARRR framework can eliminate guesswork and wasted resources from your product development process. This pirate framework will equip you with data to help create loyal customers who evangelize your product—and for any business, that’s the greatest bounty of all.

The first step toward achieving this big-picture goal is identifying the product metrics that enable you to optimize your product and customer journey. Knowing which product metrics to track will help you benchmark where your product is today and understand what steps you can take to drive scalable, sustainable growth for your business.

Check out The Amplitude Guide to Product Metrics for help choosing the right combination of metrics today.

About the Author
Image of Noorisingh Saini
Noorisingh Saini
Global Content Marketing Manager, Amplitude
Noorisingh Saini is a data-driven content marketing manager and Amplitude power user. Previously, she managed all customer identity content at Okta. Noorisingh graduated from Yale University with a degree in Cognitive Science, specializing in Emotions, Consumer Behavior, and Behavioral Decision Making.

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