Ever tracked too many metrics?

Or too few?

Ever felt your KPIs weren’t actionable?

Or that they weren’t moving you closer to your business goal?

We’ve all been there in one way or another.

The good news? There’s a way to unearth your most important metrics and drive your product growth…


Table of Contents

  1. Focus on a North Star That Captures Value
  2. Discover the Key Drivers to the North Star
  3. Plan for Growth – The One Metric That Matters

1. Focus on a North Star That Captures Value

Analytics is the measure of movement towards your business goal. Therefore, it is utterly important that you get your metrics right!

If you’ve been setting goals on number of sign-ups, or logins, you’ve been largely fooling yourself. Sign-ups and logins don’t say much about whether or not your product has helped customers achieve their desired outcomes. If you’ve acquired 100 new users and they filled out a registration form but never experienced the value of the product, they’ll likely log in once, maybe twice, and then leave for good.

Meanwhile, your sign-ups have gone up, but their growth is vanity.

Instead, the metric you want to focus on needs to capture the value that your product delivers to customers. This is the North Star Metric (NSM)—a powerful concept emerged in recent years from Silicon Valley companies with breakout growth.

Shifting focus to customer value allows you to move beyond driving fleeting, surface-level growth to instead generating sustainable customer growth—says Sean Ellis, a big champion and one of the fathers of the North Star Metric [1].​​​​​​​

Start With Your Users’ Desired Outcome

Ideally your NSM would capture the aggregate number of desired outcomes achieved by your customers using the product. This might be difficult to measure though. For instance, suppose your product generates qualified leads for your customers. Your customers’ desired outcome is therefore to close deals with the leads you provide—that is the value that the product ultimately delivers to them. So the NSM might be the number of deals closed by customers. However, since that happens outside of your product ecosystem, you are currently not able to track that. You might in future build a platform on which your customers could make transactions with their clients and so you would be able to track closed deals. However, this is not worth the effort—at least, not now. So, a better NSM would be number of lead profiles downloaded by customers, with the idea that downloading a lead profile means the customer deems that lead qualified enough to close a deal with. In other words, the number of lead profiles downloaded by customers, a measurable metric, is a proxy metric for the number of deals closed, which would be tougher to instrument.

To generalize this a bit, when setting your NSM, try to spot usage signals that strongly correlate with customers achieving a desired outcome through the core value of the product.

Find Out What Customers Value about Your Product

If you don’t know when and how your customers achieve a desired outcome with your product, there are essentially two ways you can go about finding that out.

1. Qualitative Research

Just ask your customers: they will tell you what their jobs to be done are and how they use the product to accomplish them. To that end, you could use tools such as:

  • Customer interviews
  • Digital surveys, at the end of a user’s session (e.g. to ask them if they were successful or not, what goal they’ve achieved during the session, etc.)
  • User testing (observe how users accomplish tasks)

Once you know what customers value about the product, then build a North Star Metric around that.

2. Quantitative Analysis

If you run a subscription business, you could analyze your data and see if a correlation exists between a customer with a certain usage pattern and the likelihood of, say, renewing their subscription. For instance, suppose that your product provides actionable insights to customers through data and analytics, and your customers use those insights to build their own business strategies. If a user sets a customized dashboard that they visit regularly does that correlate with renewing a subscription? If so, that could be a hint that users performing those key actions are achieving a desired outcome and your North Star Metric may be related to that, or perhaps to the information contained in those customized dashboards. One way to capture that would be to define your NSM as the total number of customized dashboard views over a period of time. That way you will focus on streamlining training, onboarding, marketing and user experience to get as many users as possible to perform those key actions (maximize value delivery).

Focus on a Leading Indicator of Sustainable Growth

There is a key aspect to take into account as you define your North Star Metric.

Anytime you decide to focus on a metric that trends positive without a corresponding improvement in overall value delivered, it is probably not a good North Star Metric. This is the trap many fall into when they set their NSM as a revenue measure, such as MRR (Monthly Recurring Revenue), or ARR (Annual Recurring Revenue), or ARPU (Average Revenue per User). By focusing on value captured rather than delivered, they are not able to foresee disasters—revenue is a lagging indicator: it tells you what happened, not what will happen; by the time you can measure it, it is too late. (There is only one exception to that: transactional businesses—where the value delivery and capture moments almost coincide.)

An example to prove that is, suppose you were a subscription-based business and your North Star was MRR. Now suppose you have luck, and MRR looks great, for the first year, but, as the second year starts, it begins to decline. By investigating the matter, you find out that while MRR was trending up in year one, the majority of your “active subscriptions” weren’t actually using the product much and did not renew in year two. Focusing on revenue wouldn’t have been a problem if the MRR growth hadn’t outpaced the aggregate value delivered to customers. But because it did, your revenue growth became unsustainable. Had you focused on product usage as leading indicator—and driver—of revenue, you would have been able to predict the downward revenue trend way ahead of time, and you would have been able to take action and adjust the wrong course in time to avoid the disaster.

Not only does this example show us that there are metrics that are leading and actionable now, while there are metrics that are lagging and hence not actionable, it also shows us that some metrics drive while others get driven. The former are called Inputs or Drivers while the latter are called Outputs​​​​​​​. Getting to know your input metrics arms you with the power to affect the course of output metrics.

Customer lifecycle at a very high level. This is useful to show the leading vs lagging and the input vs output relationship in which metrics are connected to one another; that is: user activation drives active usage, which in turn drives revenue.
Figure 1. Customer lifecycle

Figure 1 represents the customer lifecycle at a very high level and it is useful to show the leading vs lagging as well as the input vs output relationship in which lifecycle metrics are connected to one another, which you can leverage to extend the customer’s lifetime with your product:

  • Activation predicts and drives Active usage—at first, when the user is new to the product, you need to show them its core value as quick as you can, otherwise you’ll lose them for good before they even experience it (drop off point #1). This is the worst drop off point that there can be and, at the same time, one of the best moments to affect user growth: if you improve the activation rate (people experiencing an ‘a-ha’ moment) at first visit, you will grow your active user base with a compound effect (more on that in section 2 of this article).
  • Active usage predicts and drives Revenue—when the user becomes active, they might still drop off if the product fails to deliver repeated a-ha moments (value) after the first (drop off point #2). If you provide a free trial to users, and they drop off at this point, you won’t be able to convert them to the paying customers. And, l​​ike we’ve seen with the MRR example, if you focus too much on value capturing while you are not delivering corresponding value, they might pay you once, maybe a few times more, but they will very likely churn when they feel that what you charge outpaces the value they get (drop off point #3).

In summary, ensure you define your North Star to express value delivered (not captured) through product usage (as in figure 2 below). The big benefits of doing that are:

  1. You can use the NSM as a leading indicator of customer value and business results. So, you can monitor it in real time and take corrective actions if need be.
  2. Setting growth goals for the NSM and improving it over time will benefit your customers and your business: users will get more and more value while using the product, and you will be able to extend their lifetime as customers and hence increase their CLV (Customer Lifetime Value)

With a leading indicator of customer value, you can change the future of your business!

Product usage is the input of an active user; Customer Lifetime Value is the output. Therefore, the North Star Metric should be defined around product usage.
Figure 2. Product usage is the input of an engaged customer whilst CLV is the output

Understand Which Engagement Game You Are Playing

Notice how the product-customer value exchange plays a vital role in the customer lifecycle: it ensures that your business is sustainable. As we’ve learned, the key here is to define the product’s North Star around the value you deliver to customers in exchange for the time and money they invest in your business. Therefore, it is utterly important to know what is exactly involved in the product-customer value exchange. Which largely depends on the type of engagement game you play.

According to research conducted by Amplitude over 12,000 companies and 5 trillion user actions, all digital products play one of three games of user engagement [2]:

  • The Attention Game: products in this game try and maximize brain share—time spent in-product means more ads display—in exchange for fun, information, and self-expression. Companies in this category are media, gaming, any company living on ads.
  • The Transaction Game: products playing this game try and maximize wallet share in exchange for pleasurable, cost-effective, and efficient shopping experiences. Companies in this game are e-commerce platforms.
  • The Productivity Game: products in this game help people do their jobs in an easy and reliable way in exchange for a subscription. This game is predominant in the business-to-business software and software-as-a-service industries.

The following table can provide you with ideas as to how to define your North Star in relation to the engagement game you play:

GameAttentionTransactionProductivity
Value creationValue creation for products playing the attention game revolves around content choices and personalization of the user experience through customer engagement
data.
For companies playing the transaction game, value creation means obsessing about providing customers with best deals, low shipping costs, and fast and reliable delivery.This is possibly the toughest digital game to be played: companies in this field have a hard time getting customers to realize the full value of their product. Software can be really daunting and time-consuming for new users to learn. That’s why being good at this game means being obsessed about product usability. Unlike in the attention game, time spent needs to be as low as possible. As a product person, you need to lower barriers to customer adoption, making your interface easy to learn, and worth their investment in time and money.
Value delivered by the ProductEntertainment
Information
Self-expression
Utility
Status
Fulfilment
Utility
Efficiency
Mastery
Value exchanged by the CustomerAd engagement
Subscription
New content
Referrals
Purchase
Price signal
Referrals
Subscription
Upgrades
Referrals
Example North StarsTime spent within the product
Sessions over a period of time
How many times people perform a critical event (e.g. watch movie, listen to music) over a period of time
Purchases per prime subscriber
Purchases per customer visit/session
Average records created per account
Number of engaged cloud subscribers

Verify That Your North Star Is a Good Metric

As you discover and define your North Star, make sure it has all traits of a good metric. Still Amplitude recommends using the following checklist [3]: 

  1. It expresses value (as it should be very clear by now). We can see why that value matters to customers.
  2. It represents vision and strategy. If you’ve defined the NSM well, you should be able to see product’s vision and business strategy in it.
  3. It’s a leading indicator of success. It predicts your business’s future results, rather than reflecting the past.
  4. It’s actionable. We can take action—now—to affect its course.
  5. It’s understandable. It’s framed in plain language that non-technical partners can understand. And so it can be used and reported at all levels within the organization, as well as in our relationship with the outside world.
  6. It’s measurable. We can instrument our product to track it.
  7. It’s not a vanity metric. When it goes up, we can be confident that the change affects long-term sustainable growth, not simply feel good about it.

Avoid Analysis-Paralysis and Evolve Your North Star as You See Fit 

Please do not get paralyzed if your North Star is not perfect. While you should define it precisely, it can still evolve as you learn more and as your business itself evolves. The key is to come up with a NSM that is directionally sound and then adapt it as you see fit. New products might need to update their North Star every 6 to 12 months. More established products adapt it every 12 to 36 months, typically. 

Examples

The following are a few examples of North Star Metrics for high-growth familiar companies out there; you can clearly see how each company’s core value and engagement game is reflected in their NSM:

COMPANYCORE VALUEENGAGEMENT GAMENORTH STAR METRIC
AirbnbConnecting people who need a place with people who can hostTransactionNights booked
AmazonOnline shopping made easyTransactionSales per month
MediumWhere people share ideas and storiesAttentionTotal Time Reading
HubspotEmail tracking toolProductivityWeekly Active Users
QuoraFacilitate the sharing of knowledge in the worldAttentionQuestions answered
LinkedInConnect the world’s professionals to make them more productive and successful.AttentionMonthly Active Users
SpotifyGive artists the opportunity to live off their art and fans the opportunity to enjoy and be inspired by these creatorsAttentionTime spent listening
UberTransportation as reliable as running water, everywhere for everyoneTransactionWeekly rides
AmplitudeHelp product teams rapidly build digital products that work better for the customer and grow their businessProductivityWeekly Learning Users

Though we’ve said loud and clear that you shouldn’t use revenue as North Star, we’ve also anticipated that companies in the transaction again are somewhat an exception to this rule. Amazon’s NSM, for instance, is a lot closer to a revenue count than to a customer value measure. However, since in a transaction game the value delivery and capture moments practically coincide, the leading vs lagging indicator distinction is less relevant in this case as opposed to the other engagement games. But one could still argue that “Sales per month” doesn’t necessarily translate into “Revenue per month”—think about goods getting returned within 30 days. So, in that way, the Amazon NSM can still be seen as a leading indicator of both customer’s desired outcome (people found the products they were looking for and purchased them) and business results (Amazon’s revenue).

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2. Discover the Key Drivers to the North Star

Much like the North Star Metric is an input to and a leading indicator of Revenue, there exist metrics that work as inputs to the NSM, which you can act upon to affect its course.

So how do we discover the NSM’s inputs?

Draw the User Journey

In the previous section, we talked about active users (i.e. engaged customers), key actions, engagement, retention, etc. These metrics are  linked to one other via input/output relationships as they are part of the user (engagement) journey.

Each product has its own user journey, but we can identify those steps that are common to all products and draw a generic user journey, which we can use as a blueprint.

The user journey on Figure 3 is my own improvement over the one published by Mixpanel in their Guide to Product Metrics [4]. It represents how each month (or day, or week) users move through the engagement funnel: starting from going to your product (measured by Reach); then becoming active—for which we can measure breadth (how many Active users there are) and depth (their Engagement)—; and finally coming back next month (Retention) and advocating for your product (Referral):

The user journey represents how each month (or day, or week) users move through your engagement funnel, starting from landing on your product (measured by the Reach metric), then becoming active—for which we can measure breadth (how many Active users there are) and depth (their Engagement)—, then coming back next month (measured by the Retention metric) and ultimately becoming advocates and champions of your product (measured by the Referral metric).
Figure 3. The user journey and its key metrics

Reach, Activation, Active users, Key actions, Engagement, Retention and Referral are all the key metrics involved in the user journey. Let’s explore them one by one to understand which could be picked as a North Star and which could be used as lever to reach the North Star.

Reach

Reach is the total number of people who have used the product in a recent time period (day, week, month, quarter—depending on the product usage frequency). For B2C (business-to-consumer) companies, this is typically the number of paid accounts (for a subscription business), or purchasers (for an e-commerce business). For B2B (business-to-business) companies, this key metric is often product install base or number of paid licenses.

Reach is a key metric since it represents the universe of users that could potentially become active in the period you analyze, and it includes both new and returning users (organically or through re-engagement campaigns).

This is the top of the engagement funnel. If the product has good engagement and retention, expanding Reach via acquisition, re-engagement campaigns, or virality loops, will affect the growth of the active user base.

Reach is therefore an input to and a leading indicator of active usage.

This metric should be an absolute count. Alternatively, you could also represent it as % penetration of the market. That way you make it more actionable for those in your company responsible to increase the product’s market share (e.g. Sales teams).

Another way of measuring it is as % of install base or paid licenses that actually used the product in a given time period. That way you give a measurable metric to those responsible to ensure maximum utilization of customer subscriptions (e.g. Customer Lifecycle Marketing teams).

Activation

Activation measures how effective you are at converting a new user into an active user; that is, one that gets the core value of the product for the first time. Since the famous Facebook’s 10 friends in 7 days a-ha moment, it’s become a common Growth Marketing practice to look at usage data to spot correlations between behavioral patterns and long-term user retention.

Ideally activation reflect that correlation so you can use it to ensure new users stay for the long run. However, depending on the complexity of the product, that might require you to carry out some complex data analyses.

Alternatively, you could simply define activated a user that performs an initial key action—one through which they get its core value for the first time. This tightly relates to the North Star, which—by now we know—needs to express value. So, if you’ve already defined the NSM, you should know what customers value about your product and define Activation as the % of new users who experience that value for the first time.

The reason why you want to look at a first core value action is that in today’s world there is massive competition for brain share. According to a survey by Statista, more than 80% of users never come back to an app after 7 days from first visit [5]. Ensuring that a new user experiences that ‘wow’ moment during their first visit increases the likelihood they will come back and form a usage habit.

Activation is therefore both an input and a leading indicator of active usage. But more importantly, improving activation has a compound growth effect: not only does its improvement directly affect the growth of the active user base but it indirectly affects the upward movement of metrics that are driven by active usage, such as Retention and Referral.

It is not a good idea to express activation as an absolute count since sudden growth of users acquisition might mislead you into thinking that your product is activating more than it actually is.

Active Users

Active users are all users (not only the new ones) that have performed a key action and received value from your product over a given period of time. Value could be defined as one action (e.g. listen to 1 song) or as a set of actions (e.g. listen to 2 songs and save 1 to playing list).

This metric is key since it measures the breadth of activity, or, in other words, how broad the active user base is.

Compare this against Reach—which is the ceiling, the maximum Active Users count you could potentially achieve.

Products that promote habitual daily use, such as Twitter or Instagram, look at DAU (Daily Active Users). Business software (e.g. Hubspot) is better measured via WAU (Weekly Active Users) since it is not necessarily used every day. Whereas MAU (Monthly Active Users) are best suited for products that have a monthly user frequency (e.g. bill payment).

Active users is a very common North Star Metric for companies that care about growing the number of users receiving value from their product out of their potential reach, and, in so doing, increase market penetration. More often than not, this approach is taken by B2B companies. However, this is not a real clear cut; for instance, B2C companies like Facebook have DAU as North Star

If you decide to define the NSM as the count of active users, be careful about how you define being active. For a product that heavily relies on network effects (e.g. a telephone network, a social network, a messaging app, etc.) the simple number of users logging in daily represents itself the value users get out of it. In other words, the more users log in every day (the more users contribute to my social media feed) the better the product is, the more value each user receives daily. Which is why DAU is the typical NSM for a social media site, regardless of which actions its users perform once logged in.

But, for all other products, simply counting logged in people doesn’t say much about the value they get. It becomes therefore really important to define an active user as someone performing one or more key actions, through which they receive the product’s core value.

Engagement

If active users measures the breadth of activity, engagement measures its depth: the former counts how many people get value; the latter how much value each active user gets on average.

Engagement could be defined as the number of key actions taken, minutes of songs listened to, or number of transactions completed. It is important to divide it by the active users count to measure the depth of engagement per user with the product (see the 2.5 key actions/MAU in figure 3). Otherwise, a sudden active users growth might mislead you into thinking that your product is more engaging than it actually is.

Engagement is an input and a leading indicator of active usage. If engagement goes down, that means that, on average, users are getting less value from the product; sooner or later, that will impact user retention and hence the total number of active users will decrease mid- to long-term. Vice versa, if engagement grows, on average users get more value out of the product, hence they will come back for more and, in the mid- to long-run, the active users base will grow.

I’ve seen few companies setting Engagement as their North Star Metric. I personally don’t think it is a good choice since it doesn’t account for the underlying active users growth.

Key Actions

Much like active users, key actions is a way of measuring the product’s active usage: it counts the total aggregate value delivered to users through key actions they’ve taken. Quite a good number of companies use this approach for defining their North Star Metric. For instance, Uber’s NSM is Weekly rides (which well summaries the growth of both sides of its market—the riders and the drivers); Spotify NSM is Time spent listening. This choice is primarily made by B2C companies.

Retention

As we talked about engagement, we’ve mentioned its relation to retention by saying that if engagement goes up or down, so should user retention in the mid- to long-term. In other words, engagement is an input to and a leading indicator of retention. Retention is a laggard by its very nature since you can only really compute it at the end of a period (day, week, month, quarter) as it measures the % of people returning during the current period from the previous one; so you have to wait until the current period is complete for the computation to be accurate, whereas you can gauge engagement in real-time. This means that if you want to make an individual or team responsible for retention, their main lever to pull should be user engagement or activation (which focus on the very first rugs of the ladder of engagement): make users engaged, or let them have a first great user experience, and they will come back of their own volition.

However, retention doesn’t just grow organically as a result of good activation and engagement. You can also think of tactics to instil retention artificially (e.g. promotions, notifications, re-engagement loops): value might be available for users to grab but if they don’t know that, you can program features helping them find it repeatedly (e.g. a notification on new content available or a new recommendation to check out).

Retention is particularly important in the growth stage of the product. Without a solid retention rate, you can’t grow sustainably. If you have a leaky bucket, you can still grow via acquisition, but it’ll be a lot less sustainable given new users churn quickly. Which is why you need to think about experimenting with retention tactics quite heavily in the growth stage and learn which features (both organic and artificial) have people come back to and get repeated value from the product.

But because retention is a lagging indicator, when deciding on time frame for retention goals, pick a range that is long enough to capture the reasonable repeat visit cycle of your customers, yet short enough that teams can get feedback to iterate quickly. For instance, if product’s repeat visit cycle is 1 month, focus on 1-month retention, but then also measure 1-week retention as a leading indicator to the monthly one. That way you can reduce the experiment duration and learn more quickly.

All that being said, when you look at retention in relation to a North Star, this metric is an input to and a leading indicator of active usage—if user retention goes up, you can foresee that the total number of active users (and hence the aggregated value delivered) will go up as well.

Referral

Referral is the percent of active users that refer other people to the product: you can use this metric to measure the effectiveness of the viral loops (both natural and artificial) you’ve built into the product to self-perpetuate its growth by new user acquisition. Some products are built with natural viral loops. For instance, collaboration tools such as Slack or Miro. Since their value is derived by the network effect, these products have an organic way to grow via referral: a new user becoming active will almost certainly invite friends and colleagues to use the product. Other products do not have that organic network effect and therefore build artificial viral loops, which are typically based on promotions or initiatives of that nature. Products like Hotmail and Dropbox have famously grown with similar tactics. For instance, the “Get free email at Hotmail” promotion or the “Get 500 MB of bonus storage if you invite a friend” promotion.

Since referral feeds reach, it is an input and a leading indicator of your product’s active usage.

Structure Your Metric Constellation

​​​​​​​Now that you know all key metrics in the user journey and how they relate to one another, the easiest way to represent the North Star Metric and its constellation of Inputs is via a driver tree, called the North Star Metric Framework. If you’ve chosen to measure active users as your NSM, your driver tree should look like the following:

The North Star Metric framework is a product's key metrics driver tree that shows which inputs can be used to reach the North Star and which work needs to be done to move those metrics up.
Figure 4. The North Star Metric Framework

Notice that the tree in figure 4 does not only include the drivers we’ve just discussed—called Level 1 Inputs—but also more granular metrics—called Level 2 Inputs—which are more specific and drive the Level 1 Inputs and the North Star (e.g. Acquisition and Resurrection would be two great examples of level 2 inputs for Reach).

Also it, includes all the individual and team work that needs to be done to drive the metrics up: experiments, new feature releases, testing, etc.

The beauty of such framework is that it represents both an upward flow of impact (an individual achieving their goal should advance the team toward its goal, which should in turn get the department or company closer to its goals) and a user engagement funnel (people reach your product, get activated, engage with it, get retained, become advocates and refer new users to it)—very much in line with the famous Pirate Funnel by Dave McClure [6]. So, the framework contains all the ingredients upon which you can set a successful Analytics strategy.​​​​​​​

The business-specific input is not part of the user journey but it is another key product metric that you can leverage when the product reaches the stage in which optimizing the business model becomes your new focus (more on that in the next section).

In the remainder of this article, we’ll take into account a fictitious case study to show you how to use the NSM Framework to feed the Growth Process.

Case Study

Suppose your product is called BoardWhite—a software-as-a-service application allowing people to create whiteboards, draw on them, share them, comment them, edit them collaboratively during workshops, etc. You offer a free trial, after which people have to pay a subscription if they want to keep on using it. You have identified your North Star Metric as Monthly Active Subscribers (MAS), which you defined as:

Monthly subscribers (both free and paid) who have interacted with at least 1 whiteboard, by creating/editing their own or editing somebody else’s​​​​​​​

​​​​​​​You have also identified the Level 1 Inputs as follows:

  • Reach = # of monthly subscribers (both free and paid)
  • Activation = % new subscribers with 1st whiteboard created or edited (their own or somebody else’s)
  • Engagement = # whiteboards interacted with / MAS (i.e. how many whiteboards an active user interacts with on average on a monthly basis)
  • Retention = MAS retention rate (i.e. % active users returning every month from month prior)
  • Referral = % MAS inviting new users (every user can invite anyone to be a viewer/commenter/editor of a dashboard of theirs)
  • Business-specific = CLV to CAC ratio (to maximize profits per user)​​​​​​​​​​​​​​
The North Star Metric Framework for BoardWhite, a fictitious company.
Figure 5. Example NSM Framework

Notice how each key metric has an owner: a department or team responsible for it. Working out their NSM Framework, BoardWhite feels confident that they can focus the entire company’s efforts toward achieving the company’s Monthly Active Subscribers target, their North Star, and each team has figured out their own OKRs (Objectives and Key Results) based on the NSM Inputs that they can affect directly or which they share with other teams.

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3. Plan for Growth – The One Metric That Matters

According to the authors of Lean Analytics, there should always be One Metric That Matters the most at every stage of your product growth [7]. Looking at CLV (Customer Lifetime Value) isn’t wise when you are validating a problem. Similarly, looking at acquisition and experimenting with all sorts of channels isn’t meaningful when you haven’t even reached Product-Market Fit and your funnel looks like a leaky bucket.

This is why one of the keys to product success is achieving real focus on what matters right now and having the discipline to maintain it.

The One Metric That Matters (OMTM) is the one number you’re completely focused on above everything else for your current stage, until you reach the next one.

But how do we find it?

Look at the Stage of Your Product 

The best way to decide the OMTM is to look at the kind of business you are and the stage you are at. Of the two, however, the stage of the product is the most important. In other words, the raison d’être of OMTM is to derisk the riskiest area right now so you can fix it and move to the next stage with confidence:

  • If you are in the Product-Market Fit stage, trying to build an MVP that sticks, your focus will be on activating users and keeping them engaged so they come back. Hence your focus should be on Retention as a lagging indicator, and on Activation and Engagement as leading indicators: until these metrics don’t look good (e.g. you are not activating enough users; or, you are not engaging enough; or, you are losing a new users’ cohort after a few days, etc.), you need to focus on understanding if any part of the product is gaining any traction and perhaps pivot to serve only that niche audience that is heavily engaged with that one feature and leave everything else behind (see the story of Burbn evolving into Instagram [8]).
  • If you have Product-Market Fit and you now want to learn which acquisition tactic impacts growth the most, then you will focus on expanding Reach via experimenting with different channels – you no longer have a leaky bucket and so it is the right time to learn which channels work and add to the top of the funnel. A key level 2 input here will be Acquisition​​​​​​​.
  • If you are looking to get into Growth and Hyper-Growth through virality loops, your focus will be on moving Referral up – more people becoming champions and inviting friends means Acquisition gets a growth compound effect: each new user will bring more users.
  • If you’ve proven the product engages, retains, self-perpetuates via virality loops, and you now want to optimize its business/revenue model, your focus will likely be on maximizing CLV (Customer Lifetime Value) over CAC (Customer Acquisition Cost) in one form or another. A Business-specific metric such as CLV/CAC or Free to Trial Conversion is what you will therefore focus on in this stage—the higher this ratio, the more profitable your business is, the more acquisition campaigns you can afford to grow your customer base even further.

Take the Pulse

Your product stage will largely determine which area to focus on right now to derisk it and move on. However, since the launch of the product, you have defined its key metrics constellation and been tracking them. You should therefore be able to read and report their status—the current baseline.

The baseline is an eye opener: as you are able to read it, it tells you exactly how you are doing and which metrics need immediate attention or which ones are low hanging fruits waiting to be grabbed for a quick impact on growth.

Suppose that at 31st Dec 2021 you measure the baseline, and it looks like the one in figure 6 (dotted line boxes):

Baseline at 31 Dec 2020 of BoardWhite's key product metrics.
Figure 6. Measuring the baseline

You are not very happy with it, especially since active users are only 32% of your product’s reach. Which means that only a third of subscribers are getting value from your product and which poses a big threat both to the free-to-paid conversion rate and to the subscription renewal rate. Similarly, level 1 inputs are not looking great and are part of the problem: e.g. 30% retention; 25% activation; 5% referral… there is a lot of room for improvement!​​​​​​​

Work out a Growth Model

At this point, what you need to do is to put the data on a spreadsheet. Starting with the baseline on 31 Dec, you then calculate a benchmark forecast of the key metrics (NSM along with level 1 inputs, along with any relevant level 2 inputs); meaning you project out their outlook based on pure historical trends. That way you can see how much you would be growing (or declining) for, say, the next 12 months, without intervention: no experiments, no new features or campaigns—just organic growth. Some would call this outlook the business-as-usual growth forecast (the benchmark growth).

At this point you decide by how much you want and can afford to grow the NSM by year end. Say that via experimentation and growth tactics, you think you can grow it by 4 times in one year. Since the Level 1 and Level 2 Inputs directly contribute and drive the NSM, you work out several growth scenarios that would lead you to achieve the set NSM target.

All you are left to do now is to select the growth scenario that has the highest return on investment. Suppose that the one you choose has you tackle Retention first with the objective to increase it to 65% by Q2; then Activation to reach 50% by the end of Q3; and, finally Referral to reach 20% by the end of Q4. In other words, growth objectives and targets for 2021 look like in figure 7:

BoardWhite's growth objectives and targets for 2021.
Figure 7. Setting growth objectives and targets

Define Your Growth Plan

The careful reader will have noticed that throughout the year, the chosen growth model, includes One Metric That Matters the most for each quarter, which corresponds to the lever the team will use to reach the North Star target by year end. In other words, the growth plan will look like the one in figure 8:

BoardWhite's growth plan showing the relationship between the North Star Metric's goal for 2021 and the different One Metric That Matters goals throughout the year, which will allow the company to achieve the North Star Metric goal.
Figure 8. Growth plan: the NSM goal and the OMTM goals to achieve it

Many confuse the North Star Metric (NSM) with the One Metric That Matters (OMTM). However, the above picture beautifully shows what relationship there exists between the two: while the NSM sets a mid- to long-term trajectory for your business (6 months to a few years), the OMTM sets a short-term plan and tackles the highest area of risk—or the one with the highest potential for growth—right now, so you can fix it and move to the next OMTM.

The work on the OMTM could be performed by a single team (e.g. the Growth team being responsible for Activation in the case study) or by multiple teams (e.g. Retention is a game for both Product and Marketing in the case study example).

What is key to understand is that the NSM is the goal of the entire company and defines who you are, the vision and the value you provide to the market; whereas the OMTM shapes what departments and teams need to do to achieve the company’s goal. This framework comes in really handy to set teams’ OKRs (Objectives and Key Results).

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References

[1] https://blog.growthhackers.com/what-is-a-north-star-metric-b31a8512923f

[2] https://amplitude.com/user-engagement/three-games-of-engagement

[3] https://amplitude.com/north-star/the-north-star-checklist

[4] https://discover.mixpanel.com/rs/461-OYV-624/images/Guidetoproductmetrics-Mixpanel.pdf

[5] https://www.statista.com/statistics/259329/ios-and-android-app-user-retention-rate/

[6] https://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-version

[7] https://leananalyticsbook.com/about/

[8] https://www.investopedia.com/articles/investing/102615/story-instagram-rise-1-photo0sharing-app.asp

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