Validating Your Startup Idea with Minimum Viable Product (MVP) Experiment Canvas

 

By Omodiaogbe Samuel

Last Updated: December 5, 2023

Introduction

A Minimum Viable Product (MVP) is an early product version with limited features, which is targeted at collecting customer feedback for further product development. The MVP involves testing hypotheses, getting customer feedback and iterating the product until deciding whether to launch the product or not. The MVP Experiment Canvas is a single-page business plan template that was designed by Bram Kanstein. The canvas is a practical framework that offers you a structured approach for designing and launching Minimum Viable Products. The canvas is comprising of 12 blocks, and each of the blocks gives a comprehensive analysis with the goal of launching a product that meets the market need. The idea of MVP is to allow the potential customers to foresee the promise of the new product and identify what kind of value they perceive, in order to guide developers towards the ideal product. The Minimum Viable Product is, thus, the path to discovering if and how the solution will attract customers, by permitting the team to iterate incrementally or, if need be, abandon the idea based on customer’s feedback rather spending too much time and resources on an idea that nobody cares.

 

The key factors to consider when developing the minimum viable product are:

  • MVP is more about the process, not the product
  • MVP is not a product with the minimum number of elements, but rather has core features sufficient to implement an idea and retain early adopters
  • MVP is based on the lean startup philosophy and implies the iterative process of building-> measuring-> learning loop until the product meets the market need completely
  • Building an MVP implies finding the right balance between what the business is offering to users and what users actually need.
  • An MVP helps in collecting maximum quality feedback by targeting specific groups or user types.
  • MVP is not MVP until it sells; it must carry enough value to the users

Types of Minimum Viable Product

There are two main types of MVP, Low-Fidelity and High-Fidelity MVPs. The one you choose will depend on where you are on your journey. The term design fidelity refers to the amount of detail included in a prototype. Let’s take a deeper look at low and high fidelity.

 

Low-Fidelity MVPs

The main goal of Low-Fidelity MVP is to gain a better understanding of customers’ problems and find an apt solution to them.

Use Low-Fidelity MPV when you want to:

  • gain a better understanding of your customer’s problems
  • check how valuable a solution to this problem may be for customers
  • investigate as to whether or not the problem is worth solving
  • explore what kind of solution would be most effective for the customer

High-Fidelity MVPs

The main goal of High-Fidelity MVPs is help to determine whether customers are willing to pay for your solution.

Use High-Fidelity MPV when you want to:

  • find out how much customers are willing to pay for your product
  • find early adopters who will be your first customers and help spread the word about your product
  • help you define and optimize your marketing strategy, such as your value proposition, call to action and communication channels
  • identify the best potential growth strategies

There are a few things to consider when choosing which type of Minimum Viable Product to use, such as risk, timescale and cost. Therefore, before you start your MVP project, ask yourself these questions:

  1. What would be your biggest potential risk be, and how are you going to avoid it?
  2. How much time do you have to build your MVP and wait for reliable results?
  3. What can you afford? Remember you’re not trying to make your customer happy at this stage, your main goal is to learn
  1. What makes the most sense in your case? Which of the hypothesis validation strategies would bring your startup to the next level?

Essentially, categorizing MVP types into low versus high fidelity is always relative to the real product. It’s much more important to understand when it’s more practical to use low and high fidelity MPV regardless of their label.

 

Steps to Building Minimum Viable Product

The following are the steps you need to follow in developing your Minimum Viable Product:

  1. Formulate hypotheses for validation: The objective of MVP is to validate ideas on the market before launching it, therefore it’s important to create clear hypotheses from the start. A more robust way to write a hypothesis is by encapsulating the specific result you want to measure.
  2. Understand the market: You need to have a good knowledge of the market you’re operating in, including the potential customers. You need to have your persona clearly defined, and also have a good understanding of the competitive environment
  3. Set indicators and metrics: After the market insights, you chose which metrics and indicators you are going to employ to evaluate the performance of your MVP with your audience.
  4. Decide on the features of the MVP: You can prioritize your MVP features by first setting your product’s vision and strategy. Be clear why it is being created and for whom. Then, assess your competition and identify key differentiators that will set your product apart. Do not try to include all customer-requested features, but focus only on the necessary ones.
  5. Offer the solution: After elaborating on all those steps, it’s time to develop your MVP that stands for a solution to your customer. Remember you must invest as little time and capital as possible, but still having features that meet your customers’ expectations, in order to guarantee the best experience.
  6. Get feedback: Have a process to receive comments, criticism, and suggestions on your MVP. You may need interviews, surveys, polls, online reviews, social media, etc.
  7. Iterate: After collecting all the information and opinions, consider the changes you may apply to your product. Finding an MVP is, in fact, the result of many iterations and errors. Sometimes, it’s even necessary to work on different versions of a business model. But, once you are able to validate your hypotheses, it’ll worth it!
  8. Launch the final product! or not: After developing, iterating, getting feedback, analyzing metrics and investments, you will be able to decide if it’s sustainable to launch the real product on the market, or if it’s prudent to discard it and find another.

Components of the MVP Experience Canvas

  1. Your Customer Segment
  2. Value Proposition
  3. Channel(s)
  4. Customer Engagement
  5. Riskiest Assumption(s)
  6. Experiment Format
  7. Experiment Scenario/Workflow
  8. Matrices
  9. Success Criteria
  10. Results
  11. Learnings & Insights
  12. Next Steps

 

Your Customer Segment

Here you pick a segment from the larger group you’re targeting with your big idea and think about who will experience the most value from your MVP. Try to narrow down the candidate pool to the early adopters. You can always reach new audiences later on when your undertaking gets on its feet. Identifying early adopters is extremely important because these are the ones that are going to be your first customers and the first version of the business is going to be crafted around them.

 

You need to ask the following questions on this segment:

  • Whose problem are you solving?
  • What are their needs / what do they want to achieve?
  • What pains are preventing them from fulfilling this need?
  • Which gains would make it easier for them to achieve what they want?

Value Proposition

If you want to stand out in your market, your company must have something notable that sets it apart. An effective value proposition can be derived by focusing on the benefits when the problems are solved.

A Value Proposition should:

  • Be easy to understand in about five seconds.
  • Communicate the benefit a customer receives from using your products and/or services.
  • Explain how your offering is different from and better than competitors’

Channel(s)

Channel is where you list the possible methods of marketing the offering to the target customer. The initial goal of your startup is to learn, not to scale. The channel that works best depends on the segment you chose. Pick one that does not cost too much time or money to get you results.

The most common channels for an MVP Experiment are:

  • Your Network (direct or referral)
  • Online Forums & social media
  • Meeting IRL (in stores, conferences, door-to-door, etc.)
  • Cold emailing
  • Aggregator websites or blogs
  • Business directories and job boards and freelancer sites

Customer Engagement

Once you have delivered your value proposition it’s time to learn from their experience, gather feedback and establish a relationship to help you in the validation of your idea. The focus here is how to engage with the people who use your MVP.   Because an MVP Experiment is small and contained, there are only a few ways to do this in qualitatively:

  • A follow-up meeting, phone or face-to-face (interview or open conversation)
  • A follow-up email with a Call-to-Action (send a reply, fill out a survey, etc.)

 

Riskiest Assumption(s)

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. Essentially, for most startups the riskiest assumption is the existence of a market. That’s also why almost all MVP’s revolve around: is this something people want? Therefore, which assumptions if invalidated, will kill your idea?

 

Assumptions can revolve around 3 subjects:

The Problem (Assumption about your market or customers):
“For the problem to be important enough / solved, it is necessary that ….”

The Solution (Assumption about the value of your proposition):
“For the solution to solve the problem / succeed it is necessary that ….”

The Implementation (Assumption about technical aspects of your solution)
“For the implementation to work/succeed it is necessary that ….”

Experiment Format

MPV range in the level of detail provided. Some MPVs provide very basic layouts and limited interactivity, and we call those “low-fidelity”. Others are highly detailed and interactive, showing a nearly seamless representation of what the final product might look like. We call these “high-fidelity.” Each has its pros and cons, and your decision to use one over the other should be rooted in your project’s unique demands. Choosing low or high fidelity depends on where you are on your journey

 

Experiment Scenario / Workflow

This applies the set of standardized steps you use to create, test, and deploy your MPV product or service. How will your experiment work? What are the steps your customer and you have to take? Describe them from beginning to end.

 

Metrics

Depending on the type of experiment you choose to run, you also have to decide what metrics you will measure. Decide what metrics you will measure. They have to be Specific, Understandable, Comparative and Actionable.

  • Specific: a conversion is what exactly?
  • Understandable: everyone should be able to understand them
  • Comparative: a ratio or a rate that you can compare over time
  • Actionable: Vanity vs. Real metrics

When running your experiment, you can measure more than one metric. This is important as measuring more than one can help you find surprising evidence about your riskiest assumption(s).

 

Success Criteria

A true MVP success is based on uncovering long-term product potential, and being able to develop a roadmap to unlock that potential. As a result, how would you know if your MVP was a success or failure? You can measure more than one metric but you can only select one metric that defines your experiment’s success. Focus on a metric that has a big impact on your assumption(s). Therefore, you need to ask:

  • How will I qualify and/or quantify a successful outcome?
  • What are my criteria to validate the assumption(s)?
  • What would successful validation be based on?

Results

When your experiment has ended it is time to gather its qualitative and/or quantitative results.

  • How many customers did you test with?
  • Describe what happened?
  • What data did you collect? (Refer back to your metrics)
  • What user feedback did you receive?

Learnings & Insights

With the results gathered it’s time to analyze them:

  • What are your key learnings? (what are the insights you got?)
  • What are your key surprises? (did anything happen you did not expect?)
  • Did you get enough results? Can you work with them?
  • What do the results tell you about your Riskiest Assumption(s)?
  • Was what happened also what you expected?
  • If not, what happened and what does that tell you about your Riskiest Assumption(s)?
  • Did you discover new things you need to investigate or test?
  • Did you Validate or Invalidate your assumption(s)?
  • Or do you need more data to draw a conclusion?

 

Next steps

What do the results tell you to do next? Are you going to Pivot, Pursue, or Stop?

  • Pivot: This is where you change directions and design new experiments to test your assumptions for a new customer segment, problem or value proposition.
  • Pursue: Were you able to lower the uncertainty around the Desirability of your Value Proposition? If so, what Assumption(s) should you test next?
  • Stop: If you can conclude there is no long-term product potential (without exploring a pivot), write down your learnings and move on to the next idea.

Case Study

EasyLoan

EasyLoan is a startup Fintech Company established to provide solution to loan challenges of Small and Medium Enterprises (SMEs) in Nigeria. Commercial banks in Nigeria avoid offering smaller loan to SMEs primarily because of the low profits they can generate, and that is further exacerbated by high processing and recovery costs. In some situations where loans are offered, they come with steep interest rates, a lengthy application process, stringent collateral and guarantor requirements. Additionally, a traditional bank takes weeks or months for loan to be approved, and such loan could come with interest rate as high as 30%, coupled with onerous documentation requirements and hidden charges.  All these challenges make it difficult or practically impossible for SMEs and micro businesses to access loan in the country. It’s worthy to note that SMEs and micro businesses accounts for more than 60% of industries in the country. As a result, without access to loan, their progress is hampered. The only way out for them is to rely on equity from friends and family. Relying solely on organic growth means that they might not be able to scale to their desired level 

 

EasyLoan is Fintech company that is out to make SMEs and micro businesses to have access to loan in cost effective and efficient way. By offering loans on an App, we tend to save operational costs such as rentals, human resources, and administrative expenses.  And such saving would be transferred to the customers in form of lower interest rates than the commercial banks. Also, being a Fintech company, our operation will be data-driven. In Nigeria, where credit history and other traditional data sources are limited, we will deploy technology to pool and mine unconventional data to create a scoring and evaluation algorithms. Such predictive analytics will help us to create a paradigm shift in risk management. Apart from offering loans, we will equally provide saving services to the customers. Higher saving would enable them to have access to higher loan opportunities. The saving account will be interest bearing, a higher interest rate than what they could receive in the conventional commercial bank. EasyLoan primary goal is to provide its consumers an easy and hassle-free access to loan without paper documentation, collateral or guarantor. With App on their smartphones, they can have access to great services on the go.

 

At EasyLoan, we recognize that one of the biggest mistakes that startups make is launching products without having experimented and validated their idea before doing so. The result is that, many times, they waste time and money investing in a product that nobody actually wants. To overcome that, we have decided to develop Minimum Viable Product (MVP) to avoid the risk of committing time and resources to a project that might not be desirable.  The MPV is about a first version of the product, with minimum features to be presented to target potential users in order get feedback on the product. That way, the company can verify the interest of the customers on the idea. At EasyLoan, for us to have a systematic model of analyzing the MPV, we have decided to use the MPV Experiment Canvas. The MVP Experiment Canvas is a practical framework that provides a structured approach for designing and launching an MVP. Essentially, the MVP Experiment Canvas brings together elements of lean startup, design thinking and business directions. By analyzing the 12 blocks of the model, we would be able to develop insights of whether the product is accepted by the market or not.

 

                                    MVP Experiment Canvas of EasyLoan
                      Analysis of the MVP Experiment Canvas of EasyLoan

The MPV Experiment Canvas is a framework to help EasyLoan to determine the desirability, viability, and feasibility of its business idea. The 12 building blocks helps us to systematically analyze our idea from defining the targeted customers, to experimenting with the model, and to making strategic decisions with the results of the analysis conducted. We sequentially filled the 12 blocks by determining what is most desirable to achieve the goal of our experiment. The first 4 blocks are connected and are centered on the customer. Blocks 5-9 is focused on the MVP Experiment conducted. Lastly, blocks 10-12 is on post experiment and the decisions we have to take. On the Learning & Insight block, we have three options: validate, invalidate, and inconclusive. EasyLoan could have chosen invalidate or inconclusive, but it decided to settle for “validate.” The reason we choose validate was that we have sufficient base to further conduct more experiment(s). We realize the fact the MVP Experiment Canvas is all about iteration and pivoting, if necessary, therefore, we decided to validate the experiment despite it not been perfect. As a result, subsequent experiment(s) will determine out conclusion at the end of the day

The Benefits of MVP

The main benefit of an MVP is that you can understand your customers’ needs and interests without fully developing a product. This enables you to build a product that the customers truly care about, and increase your chance for overall success. The sooner you get feedback on your idea the less is the chance to waste your money and time.

Essentially, the MVP has the following benefits:

  • Accelerate your learning on what customers need and how to iterate to deliver on that
  • Ability to test a product hypothesis with minimal resources
  • Avoidance of the bigger failures and high expenses
  • Checking real-life market tendencies
  • Possibility to attract investors early
  • Reduction of potentially wasted engineering hours
  • Validate your business idea early on and help you adjust your strategy in response to the feedback you receive,
  • Find early adopters and build up a potential client base,
  • Save your time and resources by helping you make better-informed decisions.
  • Feedback-based development
  • Validate the business model
  • Gather customers’ insights

Common Mistakes of Developing MPV

The following are the common mistakes of MVP development

  • Ignoring the analyses and research 
  • Lack of product strategy
  • An overengineered MVP
  • Too much feedback
  • Too many features
  • Chasing the minimalism
  • Wrong development method
  • Too many developers involved
  • Over-complicating the MVP
  • Selecting the wrong development team
  • Not preparing for the scaling phase
  • Not prototyping
  • Ignoring user feedback

                                    Summary

Minimum Viable Product is the simplest version of a product with just enough features to validate the value proposition. A good MVP puts the user in the center of the project. MPV provides efficient mechanisms to measure the engagement and get feedback in order to determine the product’s overall performance. It gives the team opportunity to make business and technical decisions based on facts rather than assumptions. The MVP Experiment Canvas is a practical framework that offers you a structured approach to designing and launching your MVP. By working through the 12 blocks of the model, you should have been able to determine whether your product has the desired potentials or not. MPV Experiment Canvas has a lot of benefits as it provides deep insights in determining whether to go ahead with a project or not. However, despite the robustness of the model, it still has some shortfalls. Therefore, combining it with other startup analysis tool will produce a much more effective result

Omodiaogbe Samuel, MSc. CMC, ChMC, FIMC

Omodiaogbe is a Strategic Management Consultant, and he the Principal Consultant/CEO at Vast Thinking Consults Ltd where he help organizations and business leaders to create superior value. Omodiaogbe holds BSc. and MSc. in Economics. Also, he is a Certified Management Consultant (CMC), a Chartered Management Consultant (ChMC), and a Fellow, Institute of Management Consultants, Nigeria. He is an Instructor on Coursera, where he teaches 25 courses in Strategic Management. Omodiaogbe is one of the world’s leading learners on Coursera and Edx with over 500 Certificates from top-ranked Universities, Business Schools, and Organizations.

Contact him:
Email; somodiaogbe@vastthinking.com.ng
Visit: www.vastthinking.com.ng

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