What is the one thing that both investors and entrepreneurs care about? It’s growth or traction.
The problem is that traction means different things to different people. And, it’s not enough to pick any metric for the y-axis of your hockey stick curve that conveniently happens to be going up and to the right and pass it off as traction.
Instead, you have to pick a single metric that serves as a reliable indicator of business model growth.
This begs the question: How do you measure traction?
In today’s issue, I’ll share how to reliably define and measure traction for your business and show you how to use it to drive focus on what matters at every stage of your product.
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What is traction?
While it is tempting to measure traction in terms of revenue or, better yet, profit, the problem with both of these metrics is that they are trailing indicators. They tell us that the business model did indeed work in the past, but they don’t necessarily tell us why or how to grow the business model in the future.
A better definition of traction focuses on leading indicators that can predict future business model growth.
Future business model growth comes from past customer actions.
We can model these past customer actions as macro steps in a Customer Factory:
Traction, then, is the output (or throughput) of your Customer Factory. Unlike relying on revenue, this approach converts revenue into something more actionable — customers and their actions that lead to traction.
For example, traction in a coffee shop is better measured by the weekly coffee cups sold. Even better is turning that metric into the number of customers that bought those cups of coffee (probably not one-to-one) and understanding leading metrics like traffic per week, repeat visits per week, and referrals per week, which will do a lot more to understanding how to grow this business than just watching weekly revenue metrics.
If you have a multi-actor model like Facebook with users and customers or Airbnb with buyers and sellers, you’ll need to build two customer factories — one for each side that plugs together.
The universal job of any business is to build a repeatable and scalable customer factory.
The Customer Factory isn’t just a cute metaphor. The reference to a factory is intentional because it opens the door to systems thinking.
The slowest machine on a factory floor always constrains throughput. Identify and improve that step, and you improve throughput (theory of constraints).
Business models are no different.
This is the key insight for focusing on what matters and ignoring the rest.
In the following sections, I’ll highlight how to use the Customer Factory metaphor to define your go-to-market strategy by product stage.
1. Business Model Fit
Before building out a real-world factory, it would be smart to run some quick numbers to test feasibility and viability. If the factory doesn’t have a chance of turning a profit, why would you build it?
You can do the same with any idea.
Starting with a minimum success criteria goal and target pricing and customer assumptions, you can test the feasibility and viability of your Customer Factory.
Mindset: Simple models help us understand the complex.
For how to do this, check out the Business Model Design masterclass bundled with a newsletter subscription.
2. Problem/Solution Fit (Demand Validation)
Next, we need to get the factory running. But before buying expensive equipment, wouldn’t it be prudent first to study, then test demand — and even better to get some orders in?
That’s the deliverable from the Problem/Solution Fit stage - Validate demand through repeatable sales.
More specifically, you acquire “qualified” early adopters (raw materials or leads) into your customer factory. A qualified early adopter is someone who has taken a tangible action, like expressing strong interest or preordering, toward becoming a happy customer.
Contrary to conventional belief, you almost never need a working product to acquire users (and customers).
Mindset: Sell before you build.
Another point to emphasize here is repeatability, a fundamental system property. Simply acquiring X customers to declare problem/solution fit isn't enough. You need to build a system that can repeatedly acquire X customers/week to keep your customer factory running.
Mindset: The Customer Factory never sleeps.
3. Solution/Customer Fit (Value Delivery)
After validating sufficient demand, as defined by your traction model in step 1, you turn your attention to converting your newly acquired users into happy customers by moving them through the steps: activation, retention, realizing (keeping) revenue, and asking for referrals, in that order.
As before, it’s important to emphasize that the factory doesn’t go to sleep at this stage. In other words, your Customer Factory needs to acquire new users continually. But you shouldn’t move everyone through the factory at the same pace.
It’s important to recognize that since you’re building this particular factory for the first time, it will need fine-tuning. Instead of trying to scale throughput too quickly and having quality suffer, a better approach would be to start with smaller batches and progressively level up.
Mindset: Rollout in batches.
This lets you manage your risks more systematically and focus on your next key deliverable: Repeatedly delivering value or making happy customers.
The two key metrics that define this stage are activation and retention.
4. Product/Market Fit (Achieve Escape Velocity)
As your batches become more repeatable, your focus shifts towards optimizing for growth. This often starts with product optimization (new features), price optimization, and channel optimization.
The goal is to find a scalable channel or a self-powered growth rocket.
Mindset: Repeatability before scalability.
There are generally three types of value (assets) you capture from existing customers:
- money (revenue)
- content and data (byproducts of retention and engagement)
- referrals
A self-powered growth loop reinvests these assets toward new customer acquisition. Let’s walk through three kinds of growth loops.
1. The Revenue Growth Loop
This growth loop reinvests revenue generated from existing customers to drive new customer acquisition. Money or capital is the propellent here, used to buy ads or hire people to run these campaigns.
Some commonly used ways for building out this growth rocket include:
- Performance marketing, e.g., Facebook Ads, Google Ads, print ads, and TV.
- Sales, e.g., outbound sales, inbound sales
- Company-generated content e.g., newsletters, social media posts
2. The Retention Growth Loop
The core retention loop in the customer factory, or happy customer loop, is used to drive customers back into your customer factory. While this is critical for making happy customers and maximizing your customer lifetime, that alone doesn’t create a sustainable growth loop.
You can turn the retention loop into a sustainable growth loop if you can utilize derivative assets created through usage by your existing customers to attract new customers.
Content and data are typically the commonly used propellents here.
Some ways to build out this engine include:
- User-generated content e.g., YouTube, Pinterest
- Reviews e.g., Yelp
- Data e.g., Waze
3. The Referral Growth Loop
This growth loop is built on referrals where you use your existing users to drive new users into your customer factory. Happy users/customers are the propellents here.
Building a referral growth loop can take many forms:
- Word-of-mouth
- Referral programs
- Inviting friends/team members
If you successfully find a possible growth rocket candidate, you then double down on optimizing your growth rocket engine and realize a scalable business model.
Key Takeaways
- Traction is the goal.
- Traction is the output of a working business model.
- Traction is customer throughput.
- Build your customer factory in stages as batches of customers.
- Each stage is wired differently to deliver the required throughput at that stage.
- Focus on constraints to improve throughput until you’re ready to move to the next stage.
- Each stage is repeatable.
- Achieve repeatability before pursuing scalability.
