Why growth models fail

Why most growth models don't get adopted, how you can avoid this fate, and a template model to get you started.

A few weeks ago, Lenny Rachitsky and I published an essay on the equations behind the top business models in tech. One of the most common questions we got was: how do I actually put this into practice at my company?

When a business equation is translated into its analytical form (usually a spreadsheet), it is often called a “growth model”. They can be a powerful tool for understanding how a business works and where to allocate resources to inflect growth.

I’ve built growth models for many businesses and observed it done for many more. I’ve also noticed that it has become popular to post, blog, and podcast about it.

But here is the dirty secret: growth models usually don’t get used. It is often a useful exercise for the person building it, but they are rarely adopted broadly within a company.

In this essay, I outline the five most common pitfalls that cause growth modeling efforts fail and how to avoid them. I also include an example model to help bring these lessons to life.

Pitfall #1: Using a growth model to forecast your business

Here is a very common failure mode:

1. Build a fancy growth model

2. Try to use it to forecast revenue or user growth

3. The results prove to be inaccurate

4. Others at the company lose confidence in the model

Growth models don’t produce reliable forecasts for the simple reason that they rely on many assumptions that are each hard to predict. When you stack these assumptions on top of each other, it compounds this unpredictability and produces unreliable results as soon as you get 6-12 months into the future. 

Growth models are primarily useful for making relative tradeoff decisions. For example, if a growth team could focus on lifting global activation rates by 10%, or improving conversion to signup from paid marketing by 25%, or increasing referrals per customer by 5%, which of those would drive more revenue growth?

This raises a key distinction with a different kind of tool: an operating model. Operating models are typically owned by the finance team and produce a forecast that the company is goaled against and is reported to the board. To create the reliability needed for this purpose, they are based on fewer and better understood inputs. For example, in an operating model you typically would not break out the different steps in a conversion funnel, but in a growth model you usually would.

The people maintaining these models should absolutely learn from each other. But keeping the two models separate is an important element of success.

Pitfall #2: Not putting your growth model into a spreadsheet

Initially, simply laying out your equation in a doc or presentation can help the team start to understand the key metrics in the business and how they interact.

However, if you stop there, you will miss most of the value, for two reasons. First, before it is in a spreadsheet you can’t actually play with inputs to see what happens to outputs. How much is that 10% improvement in activation rate actually worth? The results are often nonintuitive.

But more importantly, in a spreadsheet there is nowhere to hide. You must actually figure out how all of the metrics link up to produce sensible outputs. You have to go track down all of the baseline rates for each assumption. In going through this process, you’ll inevitably realize you didn’t totally understand the equation or your business. Simply getting the model to work is a meaningful part of the value of the whole exercise.

Pitfall #3: Building “one model to rule them all” 

For relatively simple businesses, such as D2C or some SaaS models, you might be able to get away with one model that has all of the inputs you need. But many businesses are simply too complex to express in a single model, and you’ll end up with junk in, junk out.

Let’s take marketplaces, which is the business model I’m mostly deeply familiar with. For Airbnb, you have the demand side of the business, which may be simple enough to model: you acquire travelers, they retain at some rate, retained travelers make a certain number of bookings per year, and each of those bookings has an average price and margin structure. Great!

But what about the supply side? You’re also adding properties over time, and as you do it will increase traveler conversion rate and bookings per year. And as demand goes up, that will make it easier to acquire even more properties. I’ve seen many models that try to capture this flywheel dynamic between demand and supply, and they are almost always junk.

If you’re working on a business with this level of complexity, break your business into its component parts and model them separately. In the Airbnb example, at a minimum you will want distinct models for the supply and demand sides of the business. 

Pitfall #4: Choosing the wrong person to own the model

One of the hardest things about building a growth model is that it requires two skills that are rarely found in the same person. 

They must have excellent business judgment and an intuitive sense for the company’s strategy. But they also have to understand the business on a molecular level, and be able to get the right data on each individual input. If no one fits this profile, you can pair a few people to bridge the gap. But in my experience the closer you are to a single person owning the process end to end, the better.

To add a further constraint, it is usually better if this person is an “unbiased observer”. In other words, they don’t have an ingoing preference for what the model predicts you should work on. You will be shocked to find out that when someone who owns a particular growth channel or part of the product builds a growth model, they often find that their part of the business is very important!

Given these requirements, the person with the highest chance of success is usually one of the very strongest people on a team that is one step removed from operating, like analytics or strategic finance. 

Pitfall #5: Pitching the model for the model’s sake

Despite what LinkedIn and Twitter posts may indicate, no one cares that you built a fancy spreadsheet. The only thing they care about is growing the business.

So instead of telling people at your company about why growth models are great, or all of their different use cases, or how you’re going to build and maintain it, just pitch them on one thing they should do differently as a result of your interpretation of the model. That’s what is going to get attention. 

Growth model template

What does this look like in practice? Here is a very simple growth model for a transactional business (e.g. an e-commerce company or the demand side of a marketplace). There are three things to call out which reinforce the lessons above:

1. The first thing you see is a long list of assumptions

This is a good place to start, because the whole point of the model is to make relative trade-off decisions, and these inputs each represent something unique that you could invest in. Starting by laying them out will help you make sure you’re covering your option set. 

2. The core output is a comparison of scenarios

This is the basis for making those relative trade-off decisions. A good place to start is playing with one input (like conversion rate) or a small set of closely related inputs (like paid marketing spend growth and cost per click) to get a sense for how sensitive the model is to these changes. As you can see in this case, we’ve tweaked one assumption around referral rate, and it produces quite different outcomes, which become more and more different over time.

Just remember: the key output is the difference between the scenarios, not the absolute values they produce.

3. The model has very few “looping” assumptions

The model doesn’t include compounding assumptions which are typically very hard to capture accurately, e.g.:

• How changes in supply might impact demand (as in the Airbnb example above)

• How a growing customer base could increase awareness and accelerate the growth rate in Direct signups 

There are a few places where assumptions do explicitly compound, which are limited to those that are more reliable to model, such as how a larger customer base creates more and more viral referrals to the product:

Conclusion

There is a through-line in all of the advice above: don’t overplay your hand.

Growth models are a helpful tool alongside the other ways that you understand your business, like talking to customers, understanding the market, and bottoms-up goal setting. They aren’t a magic solution that invalidates your need for those other things.

All models are wrong, some are useful. Focus on making yours useful.

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Credits

Thank you to David Weinstein, Lenny Rachitsky, and Zach Grannis for their contributions to this essay.

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