Why Lean Teams Should Use Data, Even When the Numbers Are Small
How we choose what to measure on Substack and why it matters
We work with a lot of people in small businesses or lean teams that are part of larger businesses or non-profit organizations. They are smart, passionate and resourceful. They’re juggling a lot as they pursue meaningful objectives.
Data? It’s rarely at the top of the list.
We hear:
“We are still too small. The data isn’t useful yet.”
“I have bigger priorities right now.”
“Reviewing my data is just one more thing on my list of urgent tasks. And I’d have to figure out the tools. And I don’t even like data!”
We get it. We’re also a startup. We’re less than a year old. We’re strapped for time. We’re small in numbers. Really small. We’ve had a handful of client engagements and fewer than 1,000 subscribers across Substack and LinkedIn, our primary platforms.
Given that, you might think that this is an absurd time to be thinking deeply about analytics. And yet - here we are.
Here is why, despite being small, we review our (very minimal) data regularly - and why lean teams should too.
Reason #1: A Few Select Metrics Create Focus When Resources Are Tight
When there’s too much to do and not enough time, you have to focus somewhere. If you don’t, you end up spread too thinly. And when you’re building toward something larger, the signals you pay attention to matter - even if the signals are still small.
For us, those signals currently live on Substack.
Substack is not our product. It’s a platform where we’re cultivating community ❤️, testing ideas, earning trust, and attracting the kind of curious, builder-oriented audience that might eventually want to go deeper with courses and workshops.
Because of that, we intentionally invest time there to become a valuable part of the Substack Team community.
Reason #2: Growth Isn’t Linear. Data Gives You a Feedback Loop.
Building anything involves experimentation. Data gives you something to react to.
It helps you adjust more quickly, even when the numbers are modest. No matter how much we might love a feature or a “brilliant” idea, it may not resonate, or it may need refining.
Over the past few months in Substack, we’ve:
Experimented with format, features, and cadence.
Written more Notes.
Tried Recommendations.
Shared workshop concepts to gauge interest.
Promoted differently on LinkedIn.
Each week, we document a small set of Substack metrics, review Google Analytics and track LinkedIn engagement. The numbers are modest, but we’re starting to see small pockets of traction. We’re learning what’s resonating and with whom. That clarity guides our efforts and shapes where we invest our limited time. Without that feedback loop, we’d be guessing.
Reason #3: Data Helps You See Progress When It Feels Slow
There are stretches in any builder’s journey where you hit setbacks, or momentum feels invisible. It’s easy to compare yourself to another lean team that seems to be skyrocketing. It’s easy to question whether the effort is worth it.
This is where tracking a small set of meaningful metrics over time becomes grounding. When you look back at your numbers - subscriber growth, engagement patterns, steady increases - you often see forward movement that didn’t feel obvious at the time.
Data helps you see how far you’ve actually come.
How to Get the Biggest Return on Your Data (With Minimal Effort)
Start with priorities, not dashboards. Not all movement is progress- start by deciding what kind of movement you’re actually trying to create.
For us, the priority right now is building a relevant audience, not just a larger one. We want to know whether our ideas resonate meaningfully. And we want to steadily grow an email list we can responsibly market to when we bring our client-specific methods to a broader audience through courses and workshops.
Once priorities are clear, the data conversation begins to gain focus.
We typically see lean teams will engage with data in two ways: analysis projects and indicator metrics.
Analysis projects are deeper efforts to understand patterns of behavior. Mapping how someone moves through a website. Establishing a baseline before changing strategy. Answering a strategic question that can’t be resolved with a single dashboard metric.
Indicator metrics are the signals that our platforms generate to tell us what is happening. Traffic trending up. More people commenting. Subscriber adds per post increasing.
At We Dig Data, we’re focused on indicator metrics right now.
Analysis matters - especially baselines - but our current priority is directional clarity: Are the experiments we’re running creating movement in the areas that matter?
So we track a small number of Substack metrics tied directly to our priorities. That doesn’t mean other metrics aren’t important. It means they aren’t the ones guiding our weekly decisions.
Next Up
Next week, we’ll share more specifics about challenges you may encounter and how to navigate them. We’ll also walk through the exact metrics we track and why we’re intentionally ignoring the rest.
In the meantime, if you’re looking for step-by-step guidance on setting up Google Analytics in Substack or understanding the Substack dashboard, several strong walkthroughs already exist. Two good starting points:
What’s one metric you pay attention to right now - and why? Leave a comment. We’d love to compare notes.