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Riskiest Assumption Test vs. MVP: What's the Difference?

April 2, 2019

by Reuben Hall

CEO, MindSea

For a long time, product developers have turned to the MVP as a method of measuring progress toward an acceptable market prototype. Now, however, the Riskiest Assumption Test is here, and it’s becoming a much better way to prove your product’s viability to your users.

Updated March 4, 2022

The Riskiest Assumption Test, also referred to as RAT, is a new take on the well-known Minimum Viable Product (MVP) method in the product development world.

In this post, you’ll learn about the Riskiest Assumption Test and why startups are beginning to embrace this method over an MVP.

The Riskiest Assumption Test validates the riskiest assumptions of a startup. To truly understand the Riskiest Assumption Test, let’s first revisit the Minimum Viable Product.

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What Is an MVP?

The MVP normally begins by developing a marketable product with the minimum possible characteristics.

Eric Ries, a Silicon Valley entrepreneur and author of the book “The Lean Startup,” famously quoted:

“MVP, despite the name, is not about creating minimal products. If your goal is simply to scratch a clear itch or build something for a quick flip, you really don’t need the MVP. In fact, MVP is quite annoying because it imposes extra overhead.

We have to manage to learn something from our first product iteration. In a lot of cases, this requires a lot of energy invested in talking to customers or metrics and analytics.”

An MVP, showcasing the minimum required features for your product to provide the insights you’re looking for, should not be confused with building a subpar product.

Ries’ Lean Startup MVP is based on the “build-measure-learn” feedback loop:

MVP feedback loop

Using the “build-measure-learn” feedback loop, the fundamental goal of the startup is to turn ideas into products, measure how customers (or users, in the case of a mobile app) respond, learn, and iterate based on those learnings.

This process requires a lot of time, effort, and energy (and money).

Additional reading, 'How to Build an MVP.'

MVP Case Study: Instagram

To better illustrate the MVP and its process, let’s look at Instagram.

Instagram released its first product in 2010 as a community focused on helping users collect, organize, and share the images of their life from their mobile phone. Its MVP allowed users to apply filters to photos and share images with other users on the mobile app.

Here’s a snapshot of the app and its “filters” when it first launched in 2010:

Riskiest assumption test instagram


Instagram co-founders Kevin York Systrom and Mike Krieger had 10,000 users within hours of its launch. It wasn’t long before Facebook acquired Instagram. The company is now worth an estimated $100 billion

Instagram’s approach to building a well-developed MVP, gathering data from its users, and rolling out new features over the years has been immensely successful largely due to its product-market fit and, luckily for the founders, an MVP that validated their business assumptions (people wanting an easy-to-use photo-sharing app).

The MVP Is Falling Short

Although the above case study is great, the reality is that most startups don’t have the success stories of Instagram, Twitter, or Dropbox to boast about.

Oftentimes, the term “minimum” in the MVP method loses its meaning as new startups race to the finish line before validating their riskiest assumptions. This sees them ending in failure as, again, a minimum viable product does not equate to nor excuse a subpar product.

“Companies large and small, established corporate giants as well as brand-new startups, fail in 9 out of 10 attempts to launch their new products,'' states well-known author Steve Blank in his revolutionary lean startup book “The Four Steps to the Epiphany.”

In fact, CB Insights looked at the post-mortem of 100+ failed startups and found that lack of market fit was the top reason why startups fail. In fact, in more than 42% of cases, people attempted to solve problems that served no market need.

Most startups that use MVP do not nail the product-market fit and end up building a product that the market didn’t ask for or that customers are not willing to pay for.

What Is The Riskiest Assumption Test?

Unlike the MVP, the Riskiest Assumption Test can determine whether consumers have an interest in the product before developing anything.

Startups can use the Riskiest Assumption Test to address their biggest assumptions regarding their business model, market type, users, strategy, and measures of success. In this way, startups can test their idea viability without having to develop the whole product and waste unnecessary time, energy, and money in the process.

What Are Project Assumptions?

In product development, assumptions are notions that need to be true or resolved in order for your idea to work. These are easier to identify once you’ve shaped your initial idea with the Business Model (we’ll show you a quick step-by-step riskiest assumption test example below).

In the example we provided earlier, Instagram’s riskiest assumption before launching was that people would be willing to download and use a mobile photo-sharing app. However, had there not been real appetite or need for photo sharing in the market, Instagram as we know it would not exist.

The "Learn, Measure, Build" Feedback Loop

Riskiest Assumption Test can also be defined as the “build-measure-learn” feedback loop in reverse:

Riskiest assumption test feedback loop

In other words, startups have an idea, they learn all that they can from their customers and the market, gather this data, measure it, and then build their “MVP.”

The Riskiest Assumption Test puts more emphasis on the “learning” aspect of the process versus the “building” aspect of MVP.

The sole purpose of the Riskiest Assumption Test is to validate the riskiest assumptions of the startup.

Why Are Startups Embracing the Riskiest Assumption Test?

The Riskiest Assumption Test can prevent startups from spending years on the wrong product or problem.

As Hacker Noon states in its famous 2016 “The MVP is dead. Long live the RAT” article, “there is no need to build more than what’s required to test your largest unknown” using RAT. There is no need to launch an Instagram or Twitter-like “MVP” with the expectation of perfect code or design.

Startups are embracing Riskiest Assumption Test to validate their riskiest assumptions and gradually building confidence in the viability of their idea.

Here’s a quick step-by-step approach that you can take to conduct your own RAT:

1. Fill Out the Business Model Canvas

Start by mapping out the vital aspects of the business model, such as:

  • Who will be our users/customers?
  • Who are our competitors?
  • What problem are we solving?
  • What are the key features and benefits of our product?

Here is the Strategyzer Business Model Canvas:

Strategyzer Business Model Canvas

A business model helps businesses figure out the product they should create or the problem they should solve.

2. Craft a Good Hypothesis

The hypothesis helps you determine whether your problem is big enough, whether your product is the right way to solve it, and whether you can build it and sell it without running out of money.

To create a valid hypothesis, consider what your riskiest assumptions would be for the business to be successful in a measurable way.

  • How many users will we need to be profitable?
  • In what time frame?
  • Is my problem big enough?
  • Will customers be willing to pay for my product?
  • Are we selling to the right customers?
  • How many beta users can we get before even building our product?
  • How many people can we get to our landing page to sign up for our product?

Here is a template you can start with when forming your own hypothesis:

For [product] to succeed, it is necessary that ____________. (E.g., for Dropbox: “People have multiple devices where they can share their files.”)

3. Run the Experiment and Evaluate Your Results

Once you’ve written down the hypothesis, you’re ready to start testing.

Tactics such as interviews, paper prototypes, and simple landing pages are easy methods that startups can use to quickly evaluate if they have a problem worth solving.

From there, you’ll know if you need to adjust your initial hypothesis and plan.

Riskiest Assumption Test Case Study: Airbnb

Riskiest Assumption test case study

With the significant reduction in risk, it’s no surprise that many startups are using the Riskiest Assumption Test method.

Airbnb is a great case study for the RAT. It started out when co-founders Brian Chesky, Nathan Blecharcyzk, and Joe Gebbia decided to rent air beds out of their San Francisco apartment for $80 a night.

This sparked an idea of converting living rooms into rooms for guests with breakfast included. To run their experiment, the co-founders created a site called “airbedandbreakfast.com.”

Here’s a screenshot of “AirBed & Breakfast” from 2008:

AirBed & Breakfast 2008


Their hypothesis – that people would actually pay money to sleep in strangers’ homes – was true. Today, Airbnb is worth roughly $38 billion.

The Riskiest Assumption Test Works

Many startups fail because their assumptions are wrong.

The Riskiest Assumption Test allows startups to test their idea and validate whether their product will solve their customers’ problems, whether it’s a big enough problem to solve, and whether it’s a viable business model.

This spin on the MVP has helped companies such as Airbnb, Zappos, and Buffer validate their ideas before building their products – and their efforts proved to be quite successful.

So, what are you waiting for? It’s time to embrace the Riskiest Assumption Test.

Additional Resources: 


About the Author

Headshot of Reuben HallReuben Hall is CEO at the mobile design and development studio, MindSea, where he helps startups and innovative companies envision and build the next generation of mobile apps.

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