When I advise founders in accelerators, they often have a few paying customers, which is a great start. My next question to them is: “Do you know how you will get your next ten paying customers?”
Often, they don’t have a good answer.
You see, the first few customers came in from friends, others from adviser referrals, and the rest were seemingly random.
The problem with random is that random is not repeatable.
![](https://cdn.prod.website-files.com/65c4e268c9d10398295b1af5/6668a08ba85b476d8ce79256_1.webp)
Not only is repeatability a property of systems, it is also a necessary precondition for growth.
In the next series of posts, I’m going to dive into metrics, traction, and systems thinking, specifically the Customer Factory model and how to use it in different scenarios and stages of a product.
The Customer Factory model is a simple metaphor built on the premise that all businesses share a universal goal: To make happy customers.
It works by
- taking in unaware visitors as the input on the left,
- creating, delivering, and capturing value from these visitors inside the customer factory and
- creating happy customers on the right.
The rate at which a business model creates happy customers = Traction
![](https://cdn.prod.website-files.com/65c4e268c9d10398295b1af5/6668a093feb7b2638d65fbe2_2.webp)
When working with a team that has customers, the first task is baselining their traction and hitting the Groundhog Day Effect.
Here are the steps:
1. Turn revenue numbers into a rate (MRR/ARR)
Traction is a measure of the rate of growth, so an aggregate or single revenue number without a time period isn’t all that useful. The first step is understanding how much revenue the product has made in a given time period — monthly is a good start.
Use this to baseline their current MRR (monthly recurring revenue) or ARR (annual recurring revenue).
Note: MRR/ARR isn’t restricted to subscription-based businesses. All businesses need to establish repeatability and generate recurring monthly and yearly revenue.
2. Turn MRR/ARR into a customer throughput rate
The next step is understanding where this revenue comes from, i.e., which customer segment. Finding multiple customer segments at multiple price points is pretty typical at this step. This, too, isn’t repeatable.
While it’s perfectly normal (and even a good idea) for a startup to test multiple customer segments at the outset, they must pick a single primary early adopter segment (beachhead market) to focus on reasonably quickly. This is because it’s hard to optimize multiple business models in parallel.
The ideal is pursuing a 1 product - 1 customer segment - 1 business model rule until product/market fit.
The deliverable from this step is understanding the early adopter archetype, which informs GTM (go-to-market) strategy:
![](https://cdn.prod.website-files.com/65c4e268c9d10398295b1af5/6668a09a8f8886bcd51daefb_3.webp)
3. Build a Customer Factory dashboard
The final step is creating a weekly Customer Factory dashboard. My preferred way of doing this is creating a slide deck with 52 slides (one for each week) and manually inputting the numbers every Sunday (or Monday):
![](https://cdn.prod.website-files.com/65c4e268c9d10398295b1af5/6668a0ab79b9883079995c34_4.webp)
When the team starts measuring their metrics this way, something uncanny happens. They encounter the Groundhog Day effect.
What is the Groundhog Day Effect?
Once the team starts measuring their Customer Factory as batches (cohorts), system repeatability quickly kicks in, and the metrics start flatlining.
![](https://cdn.prod.website-files.com/65c4e268c9d10398295b1af5/6668a0bf1b0cbb929c7eda1a_5.webp)
I named the Groundhog Day Effect after the movie with the same name. In the movie, the protagonist, played by Bill Murray, is stuck in a loop where his life repeats daily until he has a breakthrough insight that breaks the loop. If you haven’t watched the original, there are numerous plot remakes that I’m sure you can relate to.
On the one hand, this flatlining of metrics can be depressing. Because once steady traffic sets in, despite best efforts, this graph flatlines. No one wants to walk into a meeting with a flatline graph.
On the other hand, this can be highly empowering. Once you have a stable benchmark of a product, it permits you to aggressively experiment with bold new ideas to effect a spike in the flatline. If you create a spike, the next course of action is to run more of whatever you did to make the line stick at the higher level.
Your goal is to do everything possible to repeatedly and systematically drive all of these lines up and to the right guilt-free of vanity.
Resources
Download the Customer Factory Dashboard template