A Simple Growth Strategy
Leverage this Five Step Process to Kickstart Your Growth
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I’ve written before about Growth Strategy in the context of Patreon as part of a larger planning cycle. That was a complex, multi-week (maybe month!) process to get to a growth strategy for a company of that size ($1B in GMV).
It’s something to aspire to, but if you need to get started today you need a process that is more approachable. In today’s newsletter I’ll outline a shorter, five-step process for defining your growth strategy.
North Star -> Inputs
Map your learnings
Leverage learnings
Sequence
Build your backlog
Step 1: Identify your North Star(s) → Identify the inputs
As my friends at Reforge say, your North Star Metric (NSM) is:
The primary outcome metric that measures the success of a company's overall strategy and product vision. It should capture the core value delivered to customers.
But what does that really mean, and is it the same for all companies?
First, it’s an output metric. That means that if you do a bunch of things right (inputs) you’ll see this metric move over time. In an ad-driven business this might be something like Daily or Weekly Active Users (DAU or WAU) in a marketplace business it could be transaction volume (rides if you’re Lyft, bookings if you’re AirBnB). What’s most important is that if this metric improves it means that more customers are receiving more value from the product.
Speaking of value, you might be thinking “I’ll just use revenue as my north star! That’s ultimately what matters, right?”
WRONG.
Well, sort of. It’s true that revenue is the thing that pays the bills. But revenue maps more closely to the price customers pay rather than the value they receive. A retained, engaged user powers your growth model and leads to monetization.
So should you pick just one NSM? Probably not if you have a complex business; pick three instead. The reason being that one NSM won’t capture the nuance of your business—you might be growing DAU but are they just free, lower quality users or are they converting to paid?
When selecting these metrics look for a retention-based metric (ex: WAU), an engagement-based metric (ex: how frequently in a week is someone returning, like 4d7), and a monetization-based metric (ex: how many ad clicks do they perform).
After you’ve identified your three NSMs you need to break those apart into their inputs. This is similar to what you’d do when creating your growth model.
As an example, let’s break down WAU into some component parts:
# of new signups for the product
# of activated customers
# of retained customers
# of resurrected customers
Each of these input metrics contributes to the Weekly Active User. Some of these, like signups, aren’t great inputs because they don’t show real intent. Activated customers are better in that regard. You might also decide that while resurrected customers are important, they’re a small contributor to WAU currently and you don’t want to prioritize it.
You can do this for your three NSMs and it might look something like this:
Okay, now you’ve got your best attempt at NSMs and their inputs. The next step in creating your growth strategy is to organize what you know about them.
Step 2: Map your learnings
Mapping your learnings involves collecting and analyzing experiment results, research, customer conversations, metrics, and trends. This helps you understand the impact of these inputs on your outputs.
Here are a few resources I’ve created in the past that can help you:
What you’re trying to do here is to organize what has happened in the past and how that has contributed to moving your inputs forward. It also helps you to understand where you don’t have knowledge, where it’s lacking, and where it might be outdated and in need of a refresh.
Don’t be precious on format or structure here, something as simple as this can work:
[Input]
Learning / link
Learning / link
Learning / link
Once you’ve organized all of these nuggets into a nice, bulleted list you can start to make sense of them.
Step 3: Leverage your learnings
Assuming you have an archive of learnings from Step 2, this next step used to be challenging due to the need to compare different parts of your archive. Fortunately, LLMs can now simplify this process.
Here are a few ways that you could engage with an LLM to help shortcut the process.
Identifying Themes
Analyze this set of insights and learnings to identify major themes
Review these insights and extract common patterns and umbrella themes
Based on this collection of learnings, what are the primary themes that emerge?
Deep Diving
Focus on the insights related to [specific area/topic] and identify any recurring themes or patterns
Analyze the key learnings in the context of [specific challenge/goal] and highlight relevant themes
Comparative Analysis
Compare these insights with previous learnings and identify any new or evolving themes
How do these key learnings align or differ from past trends we have observed? Please highlight any notable changes.
Based on the insights from this period, how do they compare to our earlier findings? What new themes are emerging?
When you identify your themes and patterns the next part of step 3 is to identify which growth loops would benefit by acting on these insights and whether that loop could impact several inputs across multiple North Star Metrics.
For example, if you have a user generated content loop powered by sharing of a piece of content then that impacts sharing, signups, activated customers, free trials or upgrades (if your product is usage based).
You may also discover that some of these themes point to growth opportunities you didn’t know previously existed. Let’s say you don’t have a user generated content loop but you identify a common theme that people are screenshotting and sharing something from your product with their teammates via Slack. Perhaps there is an opportunity to harness that organic enthusiasm and build it into the product thereby creating a loop.
Your goal here is to create a list of opportunities based on the insights you’ve organized in Steps 2 and 3. In the next step, we’ll organize and sequence them.
Step 4: Sequence
In order to sequence you need to develop the ability to estimate impact. Even if it’s merely a hypothesis. A simplified growth model can help here because you can adjust the levers of the model based on actions you might take in response to the themes in steps 2 and 3. So if one of your insights points to the opportunity to create a new loop; what does that loop’s performance look like and over what time period? If another insight points to significant friction in the sharing experience what would happen if you improved the experience by removing that friction? Creating a growth model for a single loop using the simplified growth model above is the right next step.
You’ll want to sequence using a prioritization methodology - RICE, DRICE, Effort vs. Return 2x2… I don’t care what you use, just pick something and please do it in a spreadsheet so you can stack rank the sized opportunities.
You’ll end with a sequenced or stack-ranked list of opportunities. This is the basis of your Growth Strategy: ‘Here are our opportunities and here is the order we think we should address them to have the greatest impact on our loops.’
Step 5: Backlog Building
Technically speaking, the strategy creation process ended in the last step. But a 4-step process without the execution doesn’t make a lot of sense to me.
This last step is when you put the oars in the water and start to row. Here you’ll break down the sequenced opportunities even further into their component parts—primarily experiments—designed to test the hypotheses contained within those opportunities.
For example, if you’ve identified that removing friction in the sharing process is important you might break that down into a series of hypotheses such as like:
Sharing should be more obvious
Copying a link is more important than sharing directly to a specific channel
Users don’t know that they’ve successfully copied the link
And those would lead to a backlog of experiments designed to make sharing more obvious, make link copying the primary action, and provide feedback that the link has been copied successfully. Some of these are low risk and you might just change them; others could have downside risks or measurable impact that you’d want to know so they’ll be a good experiment candidate.
You’ll want to leverage your experiment docs here and make sure each element of the backlog tests a hypothesis effectively. Running an experiment for existing loops is more straightforward because you have a control version already. Standing up a new loop will require a different process because it’s much harder than optimizing something that already exists. Oftentimes a new loop requires a new product experience or feature. I’ve taught this concept in the Advanced Growth Strategy program at Reforge; so I’ll save it for another newsletter.
In the sharing example though if the sharing loop doesn’t exist you’ll have to create the functionality and then optimize it. You could test adoption of that functionality via a painted door test and that might then go in your backlog first.
Wrapping It Up
While Growth Strategy creation can be complicated; if you’re just getting started you can drastically simplify.
Start with understanding your North Star Metrics (I recommend 3) and the subsequent input metrics that drive them. Next, across those input metrics assemble everything you know about them from experiments, to customer feedback, to first hand research and metrics. Find patterns in those learnings to create opportunity themes (using an LLM can help) and then look at those patterns through the context of your current (and potential) growth loops. Leverage a simplified growth model to help you create a sequence of opportunities and then break down those opportunities into a structured backlog of changes and experiments.
Following this process will get you to a straightforward growth strategy quickly and help identify where you may have gaps in your knowledge.