This article is inspired by a piece written by Gagan Biyani, the co-founder and CEO of Maven, a platform that empowers experts to offer cohort-based courses. Gagan, who was also an early team member at Udemy and Sprig, shares his unique insights on achieving early startup success through a method he calls Minimum Viable Testing.
The traditional startup dogma suggests that product success is unpredictable. Conventional wisdom encourages customer research, rapid MVP development, and a lot of hope. However, there’s another way to approach product-market fit, and it relies on a different acronym: MVT, or Minimum Viable Test.
The MVT method helped Gagan find early success with three out of four startups he worked with. The secret? It’s not about building a product first. It’s about testing the hypotheses that underpin the product’s existence. This article dives into why traditional MVPs often mislead founders and outlines a three-step framework for developing and running effective Minimum Viable Tests.
Beyond the Minimum Viable Product: A Case for Change
While the concept of a Minimum Viable Product has its merits, it often leads to overbuilding and a lack of focus. Here’s why:
Vision Overwhelms Insight: Founders get excited about changing the world and try to cram too many features into their MVPs. However, true success comes from laser-focusing on one core customer insight and building around that.
The Illusion of Customer Clarity: Customers don’t always know what they want, nor can they predict what solutions will truly solve their needs. They can tell you what they want to improve, but they can’t always envision a radically different solution.
Premature Company Building: It’s tempting to get caught up in company branding, hiring, and fundraising before achieving product-market fit. However, true validation comes from customers wanting your product, not from outward appearances.
Overbuilding the Initial Product: The very idea of an “MVP” can mislead founders into building more than necessary. They end up creating login systems, onboarding flows, and user interfaces before validating their core assumptions.
Technical Debt from Day One: Starting to code too early can lead to accumulating technical debt that can haunt the company later on. It’s better to validate core hypotheses without writing a single line of code if possible.
Integrating Minimum Viable Tests into Your Startup Journey
A more effective approach involves integrating Minimum Viable Tests (MVTs) into your startup process.
Here’s a step-by-step guide:
- Immerse Yourself: Deeply understand your chosen industry.
- Understand User Needs: Use customer development techniques to uncover your target audience’s jobs-to-be-done and how they’re currently addressing them.
- Define Your Promise: Articulate the value proposition your solution offers to help users with their jobs-to-be-done.
- Identify Risky Assumptions: Pinpoint the make-or-break assumptions that could determine your success or failure.
- Test Your Assumptions: Design and execute Minimum Viable Tests to validate or invalidate each crucial assumption.
Iterate through steps 4 and 5 until you’ve sufficiently de-risked your hypotheses. Once you have a high degree of confidence, proceed to the following:
- Build an Initial Product: Bring your insights to life in a tangible product that allows for user interaction and feedback.
- Iterate Towards Product-Market Fit: Continuously refine and improve your product based on user feedback and market analysis.
- Scale for Growth: With product-market fit secured, focus on scaling your operations to accommodate increased demand.
Decoding the Minimum Viable Test (MVT)
An MVT is a focused experiment designed to test a critical hypothesis, something that must hold true for your startup to succeed.
For instance, the team at Maven needed to prove that people would find enough value in a cohort-based course to justify a price point 10x higher than that of a self-paced online course. They weren’t concerned about the platform’s features or design; they needed to validate their core value proposition.
The beauty of the MVT approach is that it doesn’t require you to be technical. You can test assumptions and validate your idea before investing in a technical team or building a complex product.
The 3-Step MVT Framework: From Idea to Validation
Imagine you’ve identified an opportunity in a market you know well. You’ve talked to customers, understand their pain points, and have an idea for a solution. Now, it’s time to test your assumptions.
1. Define Your Value Proposition: The Promise You Make
Your value proposition is the core benefit you offer your customers. It’s the reason they’ll choose your solution over the alternatives.
- Focus on Actions, Not Words: Observe what your target users are doing to solve their problems. Their actions often reveal more than their words.
- Keep It Simple: The best value propositions are clear and easy to understand. Think about companies like Uber or Dropbox: their value propositions are straightforward, even if their underlying technology is complex.
2. Identify Risky Assumptions: The Potential Deal-Breakers
Every startup operates on a set of assumptions. Identify the ones that, if proven false, would undermine your entire business.
- Desirability Risk: Do people actually want what you’re building? This is a fundamental risk that often gets overlooked.
- Execution Risk: Is your idea technically and logistically feasible? Can you actually deliver on your promises?
- Marketing Risk: Can you reach your target audience effectively? Do you have a viable go-to-market strategy?
- Market Size Risk: Is the market large enough to support a sustainable business?
- Profitability Risk: Can you generate profits with your chosen business model?
3. Test the Atomic Unit: Validating Your Core Value
The “atomic unit” is the smallest element of your solution that delivers value. It’s the core interaction between your product and your customer.
- Test One Assumption at a Time: While you might address multiple assumptions with a single test, prioritize clarity.
- Design Targeted Tests: Don’t overbuild. Focus on isolating and testing the specific assumption you’ve prioritized.
- Don’t Build for Every Test: You often don’t need a fully functional product for your initial tests. Get creative and find ways to test your hypotheses with minimal investment.
- Get Specific with Your Atomic Unit: The more specific your test, the more insightful your results will be. Focus on the core value you’re offering.
MVTs in Action: Real-World Examples
Let’s see how Gagan used the MVT process at his companies:
Maven: Validating the Value of Cohort-Based Courses
- Value Proposition: Maven aimed to deliver significantly better online education through cohort-based courses.
- Risky Assumption: Would people pay a premium price (10x higher) for a cohort-based course compared to a self-paced alternative?
- Atomic Unit Test: The test needed to center around a cohort-based course, but how do you test a marketplace model, a tech platform, and a new educational format all at once?
Instead of building a complex platform, Gagan focused on the riskiest assumption: pricing. He wanted to validate whether the value proposition of cohort-based learning justified a premium price.
The Solution: Partner with an established brand to run a single cohort-based course.
Gagan partnered with Sam Parr from The Hustle to co-teach a course leveraging Sam’s existing audience. This approach allowed him to test the core hypothesis without building a product or audience from scratch.
The Results: The course generated over $150,000 in revenue and received a 9/10 rating from students. More importantly, Gagan uncovered valuable insights:
- Community is Key: Building a strong community is crucial but challenging.
- Pricing Power: The premium price point was readily accepted.
- Instructor Access: Students valued direct access to the instructors.
- Variable Engagement: Student engagement varied significantly, requiring tailored approaches.
These insights informed Maven’s product development. Instead of focusing on building a feature-rich platform, the team prioritized attracting high-quality instructors and refining the community aspect of their courses.
Sprig: De-Risking On-Demand Food Delivery
- Value Proposition: Sprig aimed to provide fast, healthy food delivery that outperformed existing services.
- Risky Assumption: The operational complexities of food delivery could easily become a logistical nightmare.
- Atomic Unit Test: The core element was a delivered meal. The test needed to validate the efficiency of their delivery system.
The Solution: Simulate the delivery process using a private chef and a manual dispatch system.
Gagan hired a chef, created a one-night-only menu, and used Eventbrite for orders. They used a map and text messages to coordinate drivers (friends and TaskRabbit workers).
The Results: In a single night, they delivered over 40 meals with minimal technology.
- Operational Feasibility: They proved that efficient food delivery was achievable, even with a low-tech setup.
- Logistical Challenges: They gained firsthand experience with the complexities of routing, timing, and customer communication.
The test didn’t address every potential question, but it validated their core operational assumption and allowed them to move forward with greater confidence.
When an MVT Leads to Saying “No”
Not all ideas are worth pursuing. Sometimes, the most valuable insight is realizing that your initial assumptions were flawed.
Gagan had an idea for a travel planning service that connected travelers with local advisors. He tested the concept by hiring an advisor to plan a trip to Southeast Asia.
While the trip was fantastic, Gagan observed the challenges the advisor faced in managing logistics and dealing with varying customer expectations.
Ultimately, he concluded that the business model was:
- Operationally challenging: Matching advisors with customers at scale seemed difficult.
- Not personally fulfilling: The business didn’t align with his passions.
- Limited in market size: The pool of qualified advisors was smaller than anticipated.
Despite its potential, Gagan decided to abandon the idea. The MVT process helped him avoid investing time and resources into a venture that wasn’t a good fit.
The Art of Minimum Viable Testing: Embracing Uncertainty and Learning
The MVT framework provides a structured approach to navigating uncertainty, but it’s essential to remember:
- There are no guarantees. Even with rigorous testing, startups face inherent risks and market dynamics can shift unexpectedly.
- Embrace iteration. The MVT process is about continuous learning and adapting your approach based on feedback.
- Prioritize long-term vision. Don’t get caught in the “traction treadmill” of chasing short-term growth at the expense of your core goals.
Minimum Viable Tests won’t eliminate the possibility of failure, but they can significantly increase your odds of success. By validating your riskiest assumptions early and iterating rapidly, you can build a company that delivers genuine value to your target market.