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"Scalepath was able to quickly understand our market and help develop a TAM model that we felt confident putting in front of investors for the Series B fundraise at Alyce."
Headshot - Emily Glass
- Emily Glass, COO, Alyce

Frequently Asked Questions

What's a market model?

A market model is a view into a market: the customers, products, and revenue structure for a specific business.

Most companies use a single market model if they sell similar products to similar customers. As businesses become more complex, additional market models are useful.

Do you offer free trials?

We can provide access to a non-editable sample market model in our free Sanbox plan.

We take a 'software+expert' approach, so custom TAM models are only available on a paid plan.

What's the price?

It's free to get started with a Sandbox account. Paid plans currently start at $4,900. You can view full pricing information here.

Can I upgrade my plan after signing up?

Yes - you can upgrade any time. Just get in touch with our customer support team and they'll help you with the process.

What happens if I want to cancel?

You can cancel your subscription any time. You'll have access to the platform for the remainder of your subscription period.

Do you allow agencies or consultants?

Yes - we love agencies and consultants! Contact us for pricing and ways to work together.

Do you offer discounts to non-profits?

We offer discounts to non-profits, social enterprises, educators and accelerators. If that describes you, please contact us.

Where do you source your data?

Often, TAM analysis starts in a sales database, but we think that's the wrong approach. These databases double-count many companies and, depending on industry, misses even more.

We source primary data from national agencies, such as the US Census Bureau and Stats Canada, or global organizations such as the UN—organizations tasked with counting and categorizing every business annually. We then apply proprietary machine learning models to build forecasts, generate insights across geos, and apply it to our users' contexts.