DDeep Dive with Ali Abdaal
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Entrepreneurship

Mapping a Growth Model Around a North Star Metric

Difficulty
Advanced
Time to result
~weeks to results
Steps
7
Confidence

The first step of the growth levers process, worked live on the episode. A growth model starts with a North Star metric: the number that increments when you deliver value to customers, ideally spanning acquisition through to retention and monetisation. Around it sit acquisition levers feeding in, a habituation rate converting new users into loyal ones, engagement and retention levers keeping them, and a monetisation rate expressed as revenue per North Star unit. Positive feedback loops are drawn in explicitly. A small set of check metrics, such as refund rate or satisfaction score, are watched but never optimised. Once numbers are attached, you can ask which ratio could realistically be multiplied ten times, which is what tells you where the leverage really is.

Origin

Extracted from Deep Dive with Ali Abdaal

How to run it

  1. 1

    Define the North Star metric

    Find the number that increments when you deliver value to a customer, not the number that increments when you get paid. Ask how people would naturally behave if they were getting a lot of value, and pick the behaviour that best reflects the mission.

    Pro tip If the exact measurement is thorny, agree the principle first and use rough proxies; a directionally accurate number is enough to steer the business.

    Watch out Revenue is easy to measure but is the wrong North Star, because it is downstream of value delivery and invites ideas that are orthogonal to customer value.

  2. 2

    List the acquisition levers above it

    Name the handful of genuine sources of new audience or new customers and rank them. Most businesses find far fewer real sources than they expect once collaborations, cross-posting and other minor channels are honestly assessed.

    Pro tip If one lever is obviously dominant, say so out loud; a simple top of funnel is a gift, not a failure of analysis.

    Watch out Do not list channels you wish worked. Check whether the crossover traffic actually exists in the data.

  3. 3

    Define the habituation rate

    Put a conversion rate between first exposure and loyal, repeat consumption, and work out what has to happen for someone to cross it. In software this is the aha moment; identify the equivalent event and the micro-metrics that drive it.

    Pro tip Interview people who became loyal in the last one to three months and ask what the first thing they saw was and why they did not bounce.

    Watch out Measure this on new users specifically. Metrics dominated by your existing loyal audience will not tell you whether you are welcoming newcomers well.

  4. 4

    List the engagement and retention levers

    Name the content types or product experiences that keep existing customers coming back, and pick one high-level metric that tells you whether you are doing enough of them.

    Pro tip Look for implicit feedback loops, where volume raises visibility and data, which in turn raises volume, and draw them on the chart.

    Watch out Levers that grow the audience and levers that retain it are often different, and can even feel at odds. Model them separately.

  5. 5

    Add a monetisation rate

    Express monetisation as revenue per North Star unit, covering every income stream that depends on the audience. Break it down later into the proportion monetised actively versus passively and the average value of each.

    Pro tip Segment out revenue only once acquisition channels exist that are independent of the core audience.

    Watch out Monetisation sitting downstream of the North Star is normal. Do not force every revenue stream into the North Star itself.

  6. 6

    Add a small set of check metrics

    Choose a few numbers, such as refund rate or customer satisfaction, that you watch to make sure you are not breaking something while optimising. These are not drivers and are not to be optimised.

    Pro tip Keep the list deliberately short so the check metrics do not become a second scoreboard.

    Watch out Adding check metrics you never actually look at is worse than having none, because it creates false comfort.

  7. 7

    Ask which ratio you could realistically 10x

    Go through the model and ask which conversion rate, audience number or monetisation rate could plausibly be multiplied ten times, and whether doing so would multiply the business. That comparison, not enthusiasm, decides where resources go.

    Pro tip Sanity-check the ambition against outliers in your category before betting on it.

    Watch out Some numbers cannot be 10x'd at all. Pursuing them anyway burns years.

In the wild

Ali Abdaal lands on monthly returning viewers

After rejecting revenue, lives changed and true fans as too hard to measure, the pair worked back to a metric already sitting inside YouTube analytics: monthly returning viewers. It combines reach and loyalty, it stops counting people the business is no longer serving, and it can absorb Instagram followers and email openers as proxies later. When Ali checked the number live it was 1.7 million for the last 28 days against 5.5 million subscribers, giving roughly a 20% ratio and a baseline he had badly underestimated. Acquisition levers, a habituation rate, retention content and a dollars-per-returning-viewer monetisation rate were then hung around it.

A single steering metric replaced a fourteen-tab spreadsheet, with a measured baseline of 1.7 million.

Aha moments in consumer software

Lerner uses well-known habituation events to explain what the conversion from new to loyal looks like in practice: with Headspace, doing a couple of meditations and finding them helpful; with Netflix in its early days, finding three titles to add to your queue within ninety seconds; with Facebook, adding seven friends so the news feed populates. Each is a specific, measurable event rather than a vague sense of satisfaction, which is what makes it possible to design the first-run experience around it.

A concrete first-session event becomes the thing the team optimises rather than generic engagement.

Common mistakes

Using revenue as the North Star

Revenue is easy to measure, which is why teams reach for it, but working backwards from a revenue target generates ideas that may be completely orthogonal to customer value. Focus first on acquiring customers and delivering value; monetisation is the easier second problem.

Splitting into several models too early

Ali suggested modelling his business as three separate companies. Lerner pushed back because at that stage the split adds complexity rather than removing it; get to one simple highest-level model first.

Demanding a perfect number before starting

Waiting for a metric that feels rigorous means never building the model. Rough proxies and estimated de-duplication across platforms give a directionally accurate number, which is enough to steer by.

From the transcript

the first thing we have to figure out is your Northstar metric and this is the number that increments when you deliver value to customers

Matt Lerner · 42:30

so there's a piece of this model we're g to have to think about which is how do you get loyal subscribers how do you…

Matt Lerner · 57:00

so there's this whole other bucket of metrics you shouldn't have too many of them and these are not your drivers and they're not Northstar…

Matt Lerner · 1:29:00

From the episode

How to Scale your Startup with Growth Levers: Matt Lerner