Hi friends 👋

Here are some of my best reads this week:

1. Your metrics belong in a system
2. Choosing your North Star Metric
3. When PLG works
4. Quickies: Payback period > CAC/LTV in SaaS

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#1 Your metrics belong in a system

Being good at SQL or data visualization is like being good at navigating with a map. The thing is, someone needs to make the map – a system of metrics – in the first place, and that's a totally different skill, which most companies tend to ignore.

Companies often start off by caring about non-actionable lagging metrics like user or revenue growth and then start looking into things that feel interesting, like daily active, daily uninstalls, monthly active, retention curves, power user curves, and so on. But not having a system becomes messy very fast.

What's wrong with not having a system of metrics?

• A tight, premature focus on a small number of metrics creates blind spots. You could be stuck with implicit assumptions but have no way of challenging them. There could be a grave problem or big opportunity outside your observed view.
• E.g., GrubHub and Seamless both do food delivery but calculated revenue differently. Seamless equated revenue for GMV (Gross Merchandise Volume = order size and number of orders), while GrubHub viewed revenue as GMV multiplied by the average commission. A subtle difference to include "commission" in the system drastically changed how the two companies optimized for revenue. While Seamless search results sorted restaurants alphabetically, GrubHub realized they could sort them in order of commission earned. These differences made GrubHub's revenue much higher.

How to build a system of metrics

Before diving into numbers, you need to step back and come up with a holistic system. You need to map your terrain, before you figure out your path.

1. Understand Growth Accounting. A metric moves from one point to another over a period of time, because some things add to it, and some things subtract from it. Growth Accounting is about breaking down the different components that cause a move.
2. Figure out your core metrics. Establish a few core metrics for which you want an exhaustive breakdown of any movement. You'll want to have at least one leading indicator that closely captures the value your business provides. E.g., For eesel (a tool that gathers all your work apps together) this is "engaged users," which are users that access a document or use commands.
3. Figure out a cadence. Look at the frequency at which someone gets value. E.g., Airbnb measures retention at a yearly level because that's how often they expect people to make bookings. Eesel's value is derived every week, but they define metrics at a monthly level because of limitations with their churn definition.
4. Break down what adds or subtracts: Explicitly introduce language to discuss the different components that move a metric. E.g., For monthly active users, there's: New (Users that showed up for the first time this month and are Active) + Churn (Users that were Active in the past month but not this month) + Resurrected (Users that joined before, weren't active in the past month, but are now active)
5. Introduce metrics to make connections: Establish how different metrics relate and introduce any concepts needed to make connections. E.g., eesel introduced metrics to make connections between active users, engaged users, and paid users to avoid false interpretations.
6. Fill in any gaps: If some parts of the business isn't captured yet, introduce concepts to cover this ground. E.g., eesel wanted to make a discinction between "New active users" and "New users" because you can sign up for eesel and never become active. So, in addition to breaking down active users (last step), they introduced another metric called "New inactive users."
7. Introduce a small number of calculated definitions: You may want to introduce some calculated metrics on top of your canonical metrics for simplicity. E.g., For active users, you could define "Net Churn" as Churn - Resurrected if the latter is pretty marginal. For revenue, you could use Quick ratio (ratio of New + Resurrected + Expansion over Churned + Contraction). The premise is that these calculated metrics make it easier to digest and extract insights.

​Read the article​

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#2 Choosing your North Star Metric

Choosing one guiding metric can be hugely effective, as all energy and brainpower will flow in that direction. But it can also be dangerous: by maintaining a laser focus on a single metric for too long, teams risk short-term thinking, missing new opportunities, and sacrificing the user experience.

Six categories of North Star Metrics

1. Revenue (e.g., ARR, GMV): The amount of money generated
2. Customer growth (e.g., paid users, market share): The number of users who are paying
3. Consumption growth (e.g., messages sent, nights booked): The intensity of usage of your product, beyond visiting your site
4. Engagement growth (e.g., MAU, DAU): The number of users who are simply active in your product
5. Growth efficiency (e.g., LTV/CAC, margins): The efficiency at which you spend vs. make money
6. User experience (e.g., NPS): The measure of how enjoyable and easy to use customers find the product experience, overall

A framework for choosing your NSM

The #1 question to start with: Which metric would most accelerate my business' flywheel if it were to increase today? A good place to start is your company's business model.

• Marketplaces and platform → Consumption growth. Examples: Airbnb (that makes money from usage; nights booked), Twilio (that charges a flat fee; messages sent)
• Paid growth driven businesses → Growth efficiency. Examples: Blue Apron (that ships a physical product; margins), Calm (that has a digital product, LTV/CAC or payback period = how quickly you can reinvest in growth)
• Freemium team-based B2B products → Engagement and/or customer growth. Examples: Businesses grow through a bottom-up acquisition model: Slack (DAU14), Coda (Number of Paid Team)
• UGC subscription-based products → Content consumption (rather than engagement – the latter one being more active, like creating a video). Examples: Twitch or Loom that are driven by content creation (e.g., five-minute plays, or videos created that are viewed)
• Ad-driven businesses → Engagement. Examples: Pinterest (that doesn't expect its users to need the product daily; WAU), Spotify's podcast business (podcast listening is more sporadic for users; MAU)
• Consumer subscription products → Engagement or customer growth. Examples: Duolingo (that has a large free-user base that eventually migrates to paid and thus focuses on engagement; DAU), Patreon (growth of successful creators)
• Products that differentiate on experience → User experience. Examples: Superhuman (NPS), Duolingo ("learning competency" – a metric that matches their user goals)

Alternative: Using "jobs to be done" to determine your NSM

• An alternative approach to choosing your North Star Metric is to ask yourself: What "jobs" are our users hiring our product to do? In this case, the North Star Metric needs to measure what matters most when fulfilling the job to be done for the customer or user.
• For example, Plaid's job to be done: "Link my bank account to an app I'm using". Thus, prioritize "bank accounts linked."

To nail your output metrics (NSM), calibrate the input metrics

• Your team can't impact an NSM (such as increasing active users or increasing revenue) directly. Instead, these metrics are the output of the team's day-to-day efforts, such as increasing the conversion of a flow or driving more traffic to the site by running more Google ads.
• Once you have your North Star Metric (an output), your next step is to break this metric down into its parts and decide which metrics (the inputs) to invest in.
• Example: Airbnb's NSM is "nights booked." → They list out input metrics that feed into this higher-level metric (e.g., increase the guest conversion rate, add more Airbnb homes, or boost the number of visitors to the site) → Come up with concrete goals (e.g., "Add 10,000 new homes to the platform in Q1").
• In the earliest stages of a company, you shouldn't focus on one NSM but rather just aim to answer one question: "Am I building something people want?" → Focus on cohort retention instead (are enough people sticking after using your product?)

​Read the article​

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#3 When PLG works

Most things people call "product-led growth" are actually not product-level loops but just superimposed hooks. While these can drive growth (like reward/referral programs) and, in the best scenario, even compounding results (like SEO or user-generated content), they're not built in the product itself but rather on top of it.

In general, PLG ( = when existing users drive your growth) only works for a specific type of businesses:

• Those who grow with invitations (e.g., when you talk to others on Zoom, they have to install Zoom first), where the person inviting and the person being invited both significantly benefit from the other's use of the product. The benefit to both parties has to be getting an important job done, which often means getting paid or enabling communication.
• Those who grow with "billboarding" (e.g. sending people your Calendly/Dropbox link that shows the URL/page.), when the use of your product creates a public advertisement.

In addition, you could include the following:

• Those who grow through WoM that naturally emerges from a delightful product experience (entertainment or utilitarian, e.g. people watching Netflix shows and tell their friends), or through a movement that creates "tribal affinity"
• Those who grow through programmatic SEO/UGC (Quora, Stack Overflow, Airbnb, Yelp, Wikipedia, IMDb, and others that produce a huge long-tail of pages that help searchers with niche interests).

​Read the thread​

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#4 Quickies: Payback period over CAC/LTV

• In SaaS, instead of CAC/LTV, you should be looking into payback period. Payback period = CAC/Revenue → You'll instantly know how long it takes to be profitable on a customer – and it works equally for all price points (enterprise clients cost more to acquire, but their payback period can be even shorter than lower-tier users). Read the LinkedIn post ​

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​That's it for this week. I'd love to know what was your favorite read this week!

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Cheers, Anna

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P.p.s. Did you know you can now find all previous summaries here?

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P.p.p.s. Connect with me on LinkedIn and Twitter! (Warning: I mainly post memes and rants about marketing, but if that's your jam, let's be friends. I'm also Head of Growth at an EdTech startup and a freelance consultant for B2B SaaS startups, but honestly, I'm more into shitposting than personal branding.)