From Concept to Reality: The Power of PoC, MVP, and MLP in Product Development

Focus groups, target audience research, and competitor analysis—none of these guarantee that your product is truly needed by users. These are just forecasts that may not come true. To find out for sure, you need to create and launch a Minimum Viable Product (MVP) on the market.

Hi, I’m Sergey Kulakov, SEO of UncaiSoft. In this article, I will explain the differences between PoC, MVP, and MLP and how they can help reduce risks when launching a new product.

What Are PoC, MVP, and MLP?

Let’s start with the definitions.

Proof of Concept (PoC) – A methodology used to verify the feasibility of an idea or concept before releasing an MVP.

Minimum Viable Product (MVP) – A version of an idea implemented with the minimum necessary feature set. It allows businesses to solve a problem, deliver value to customers, gather market feedback, and test business processes with minimal investment.

Minimum Lovable Product (MLP) – A product version designed not only to solve customer problems and create basic value but also to provide a pleasant and memorable user experience. The key difference between MLP and MVP is that MLP focuses on building an emotional connection with customers, which increases retention and loyalty.

Example from the IT Industry: Developing a Mobile Expense Management App

• PoC: A black-and-white prototype of the app screens, along with a video presentation demonstrating the app’s functionality and workflow. At this stage, not a single line of code has been written.

• MVP: A functional application with basic expense tracking features, including adding, editing, and deleting transactions, as well as simple charts for visualizing monthly expenses.

• MLP: All MVP features plus automatic text recognition from receipts, integration with bank accounts for automatic transaction updates, personalized expense-saving tips, and more.

Example from a Non-IT Industry: Opening a Sports Club

• PoC: A textual description of the training methodology, a design concept, and a floor plan of the gym, along with a video presentation. At this stage, the club has not yet opened, and no premises have been rented.

• MVP: A fully operational club in a chosen location, complete with renovations, equipment, trainers, a website, and active social media groups.

• MLP: All MVP features plus a dedicated mobile app, video surveillance with live streaming of children’s training sessions, a loyalty program, and more.

Why PoC, MVP, and MLP Are Essential

In today’s product development landscape, where speed and adaptability are highly valued, risk reduction becomes a key success factor. Product managers employ various methods to achieve this, including basic research (surveys, in-depth interviews, etc.), which help them understand users’ needs and pain points.

However, it’s crucial to recognize the limitations of these methods. Participants in research studies may not always be entirely honest or accurately describe their behavior. This introduces the risk of distorted data, which can lead to incorrect product decisions.

Additionally, during the design phase, it is impossible to foresee all the nuances of implementing an operational product model. Testing with MVP and MLP allows businesses to "learn the hard way"—identifying what works and what doesn’t, as well as refining the execution strategy based on real-world usage.

Therefore, PoC, MVP, and MLP are not just development stages but a philosophy of mitigating business risks when launching product-driven initiatives.

MVP can also be leveraged for quicker business impact. For example, if you plan to launch a large-scale infrastructure project that will take three years to complete, you can first develop an MVP to achieve measurable business results within six months while continuing its development.

When to Mitigate Business Risks: Product vs. Project Approach

In an environment of uncertainty, where goals, requirements, or technologies are unclear, reducing business risks becomes critical.

The product approach, with its short iterations and adaptive planning (limited to one iteration at a time), is ideal for such situations. It enables quick responses to changes and allows teams to detect failures early in the development cycle. Tech startups like Spotify and Netflix have successfully used this approach, testing new features on small user groups before rolling them out widely. This strategy helped them minimize risks and optimize their products based on market demand.

In contrast, the project approach, with its fixed resources, budget, and requirements defined upfront for the entire project duration, is suitable for tasks with clearly established goals. A prime example is infrastructure projects, such as building bridges or railways. In these cases, requirements and conditions are predetermined, and any changes can result in significant additional costs and delays.

PoC, MVP, and MLP act as risk-reduction formats through testing within the product approach. These methods can fall into qualitative or quantitative research categories, depending on their design. For instance, conducting a PoC test in a focus group is a qualitative research method, whereas an A/B test of an MVP is a quantitative research method.

When to Mitigate Business Risks: Product vs. Project Approach

In an environment of uncertainty, where goals, requirements, or technologies are unclear, mitigating business risks becomes critically important.

The product approach, with its short iterations and adaptive resource planning (limited to a single iteration), is ideal for such situations. It allows teams to quickly respond to changes and identify losses at early stages of development. For example, tech startups like Spotify and Netflix have used this approach to test new features on small user groups before launching them broadly. This strategy helped them minimize risks and optimize their products based on market demand.

In contrast, the project approach, with its fixed resources, budget, and predefined requirements for the entire duration, is better suited for tasks with well-defined objectives. A prime example is infrastructure projects such as building bridges or railways. In these cases, project requirements and conditions are established upfront, and any changes can lead to significant additional costs and delays.

PoC, MVP, and MLP serve as risk-reduction tools within the product approach. These testing formats can be categorized as qualitative or quantitative research methods, depending on their design. For instance:

PoC testing in a focus group is a qualitative research method.

A/B testing an MVP is a quantitative research method.

How to Decide Whether to Develop an MVP or MLP

The Total Product Concept is an approach that considers a product as a combination of multiple levels:

Core Product – Defines the fundamental function a product must perform. For example, a car must be able to drive.

Expected Product – Includes attributes and conditions that consumers typically expect. For example, a car must not only drive but also have air conditioning.

Augmented Product – Offers additional features and benefits that differentiate it in the market. For example, a car should not only drive and have air conditioning but also offer self-parking functionality.

Potential Product – Encompasses future innovations that may be introduced to maintain a competitive edge. For example, autonomous driving technology in cars.

Within the Total Product Concept, MVP (Minimum Viable Product) corresponds to the Core Product, while MLP (Minimum Lovable Product) aligns with the Expected Product.

Choosing Between MVP and MLP

The decision depends on the maturity of the market you are entering. There are two possible scenarios:

A market where no similar solutions exist

Example: Generative AI in 2023 or the food market in 1990s Russia.

In such a market, customers have no expectations because they have never encountered similar products.

If there is no sausage available—bring any sausage. If there is no expense-tracking app—create any app, even with minimal functionality.

In this case, an MVP is sufficient.

A market where similar solutions already exist

Example: The modern automobile or expense-tracking app markets.

Here, consumers already have expectations set by competitors.

If the market is full of sausages or expense-tracking apps, consumers will compare and expect certain features.

In this case, an MLP is necessary.

For example, if you plan to launch a new car brand today, simply offering a car that drives (MVP) is not enough. To compete, your vehicle must include most of the features already offered by competitors, meaning you need to develop an MLP—an expected product that meets market standards.

Stages of Creating MVP and MLP

Testing an MVP/MLP is essentially a research project. Therefore, it's crucial to design this research properly.

Step 1: Defining the Business Objective

This step answers the question: 👉 "What measurable outcome should this initiative achieve?"

The objective must always align with business goals, for example:

Capture 10% market share

Increase revenue by 20%

Reduce hiring costs by 15%

Lower customer churn risk to a safe level

Step 2: Defining Research Questions

Since MVP/MLP testing is a research project, you need a structured list of questions to guide the testing process. These questions should focus on functionality and business processes, such as:

What will the conversion rate to purchase be?

What business process gaps did we overlook?

Which features are most and least important to customers?

What bugs have we not accounted for?

Does the product create the expected impact?

MVP's primary goals are to validate customer insights from prior qualitative research or to quickly generate business value. These goals will shape the key research questions.

Step 3: Defining Feature Scope

To decide which features or properties to include in the MVP/MLP, you must thoroughly understand user needs and prioritize features based on importance. Effective methods for this include Kano analysis and card sorting.

💡 Kano analysis is preferable, but if resources are limited, card sorting can be a simpler alternative.

⚠️ These methods are applicable beyond IT products—they can help define car features, yogurt properties, or café services as well.

Kano Analysis: Prioritizing Features Based on User Perception The Kano method classifies product features based on how they impact customer satisfaction. It identifies which features significantly enhance user experience and differentiate the product in the market.

How It Works: Survey Creation:

Each feature is assessed with two questions:

A functional question (if the feature is present).

A dysfunctional question (if the feature is absent).

User Survey & Response Analysis:

Potential customers are surveyed, and their answers classify features into five categories:

1️⃣ Must-have (Basic) features

Features that users expect by default.

Their absence causes dissatisfaction, but their presence doesn’t excite users.

Example: A car must have seat belts.

2️⃣ Performance features

Features directly linked to satisfaction: the better they are, the more satisfied users feel.

Example: The fuel efficiency of a car.

3️⃣ Attractive (Delightful) features

Unexpected features that, when present, greatly enhance user satisfaction (but their absence isn’t a deal-breaker).

Example: Autonomous parking in a car.

4️⃣ Indifferent features

Features that do not influence customer satisfaction.

Example: The shape of the key fob in a car.

5️⃣ Reverse features

Features that may cause dissatisfaction if included.

Example: Overly complex digital dashboards that frustrate drivers.

Using the Kano Model, teams can prioritize MVP/MLP features effectively, focusing on Must-have and Performance features first while reserving Delightful ones for competitive differentiation.

Card Sorting Method Card sorting is a technique used to understand how customers perceive and categorize different product features. It helps prioritize features based on user expectations and preferences.

How It Works: Create Feature Cards

Each card represents a potential feature or attribute of the product.

The card should include a concise description of the feature.

Conduct a User Survey

Potential customers are given the cards and asked to group them into categories:

Must-have (Basic) – Essential features; their absence causes dissatisfaction.

Performance – Features that increase satisfaction the better they perform.

Attractive (Delightful) – Unexpected features that significantly enhance satisfaction.

Indifferent – Features that do not affect user satisfaction.

Reverse – Features that may annoy users if included.

Analyze the Results

Identify which features should be prioritized in MVP/MLP development based on customer expectations.

Ensure that Must-have and Performance features are included in the initial product release, while Attractive features can be added later for differentiation.

💡 Card sorting is a quick and effective way to validate feature prioritization before investing in development.

Step 4: Selecting the Form and Creating MVP/MLP

The format of your PoC, MVP, or MLP depends on the nature of the product and the resources available. Here are the possible forms:

Forms of PoC (Proof of Concept) ✅ Online Prototype – Clickable mockups (e.g., Figma, Adobe XD). ✅ Physical Prototype – A rough, tangible version of the product. ✅ Text Description – A detailed document explaining the concept. ✅ Presentation – A visual pitch deck to showcase the idea. ✅ Video – A conceptual demonstration of the product’s use case. ✅ Tasting/Demo – Product samples for market feedback. ✅ Test Stand – Experimental setup for functional validation.

Forms of MVP (Minimum Viable Product) ✅ Landing Page – A simple website to validate demand. ✅ Excel-Based Tools – Early automation before full development. ✅ Basic App/Software – A minimal feature set for core functionality. ✅ No-Code Platforms – MVP built using platforms like Bubble, Webflow, or Glide. ✅ Manual Labor Instead of Code – Human-driven operations behind a digital interface (concierge MVP). ✅ Offline Store with Limited Offerings – Small-scale physical presence. ✅ Limited-Service Projects – A smaller version of the full service. ✅ Time-Limited Service – A short-term version to test viability. ✅ At-Home Services Instead of Physical Location – Testing demand before committing to a permanent space.

Forms of MLP (Minimum Lovable Product) 📌 All MVP forms with added features that meet market expectations. 📌 Includes UX/UI enhancements, stronger branding, and emotional appeal.

💡 Selecting the right format depends on market readiness, budget, and time constraints.

Step 5: Launch Testing, Collect Data, and Make Business Decisions

The core idea of MVP/MLP is to launch it into real-world conditions, observe its performance, collect data, and make business decisions based on those insights. There are four main methods to collect data:

1. A/B Testing This method involves running two versions of the product or process simultaneously to evaluate their effectiveness. For example, two production lines can be set up—one with a human detecting defects and the other with a robot. By comparing the results from both lines, you can evaluate how many defects were missed by the robot and how many by the human operator.

Use case:

Comparing two different marketing approaches to see which results in more conversions.

Evaluating two versions of a product feature to determine which one is more successful.

2. "Before-After" Analysis In this method, you don’t need to create two versions of something. You analyze the past and current experiences. For example, if previously a human inspected defects on the production line and now a robot is handling the task, you analyze how well the new system performs compared to the old one.

Use case:

Analyzing the performance improvements after switching to an automated system.

Evaluating business metrics before and after introducing a new feature or process.

3. Observation Method This method involves collecting data without using software tools. An observer manually watches how the MVP operates and records the necessary information.

Use case:

Directly observing customer interactions with a product in a real environment.

Monitoring how a team uses a new internal tool during the trial period.

4. Diary Studies Participants who are interacting with the product maintain a diary of their observations. They record their experiences and provide insights into how the product performs and is used in real-world conditions.

Use case:

Understanding how customers use a product over an extended period.

Gathering feedback on a beta version from real users over time.

After Collecting Data Once the data is collected using testing methods, you can answer the research questions you set earlier and evaluate whether the MVP/MLP is meeting its objectives.

Step 6: Scaling the Initiative

After the MVP/MLP successfully passes the testing phase, the next step is scaling or moving the product into full production. There are two perspectives on this:

Management Perspective:

The MVP/MLP should be scaled when it demonstrates clear business value or effect.

Technical Perspective:

Scaling happens when the existing MVP/MLP can no longer support the required level of operations or performance. This may involve refactoring the code or developing more robust infrastructure.

The decision to move into full production should be formalized and clearly communicated within the team.

Mistakes in Creating MVP/MLP

1. Mistakes in Assessing the Need for MVP/MLP Not every project requires an MVP/MLP. It’s crucial to evaluate whether the creation of an MVP/MLP will effectively mitigate business risks and whether it is justified in terms of resources and expected outcomes.

2. Lack of Clear Success Criteria Before testing an MVP, you must define business and research goals clearly, along with data collection methods. This will allow you to assess the testing results objectively and draw meaningful conclusions about the viability of the initiative.

3. Inadequate Market Research Ignoring the target audience and feedback early on can result in a product that doesn’t meet real market needs. It's essential to distinguish between basic and expected functionality, as well as understand whether you need to build an MVP or an MLP.

4. Feature Overload Stick to the features and functions that are absolutely necessary for testing the core hypothesis. Preliminary market and audience research will help identify the key features that should be included in the MVP/MLP.

5. Misinterpreting Data When analyzing results, avoid subjective interpretation of data. If you are working with quantitative data, ensure statistical significance and use proper analysis methods to make informed decisions.

Brief Guide for Application

1. Choosing the Approach Assess the level of uncertainty in your project:

   If you know exactly what needs to be implemented and the requirements are stable, choose the project-based approach.

   If there is uncertainty and requirements may change, it's better to use the product-based approach and apply PoC, MVP, and MLP.

2. Market Analysis Determine how mature your market is:

   On saturated markets, where users have high expectations, it is more appropriate to develop an MLP to create a unique user experience and stand out among competitors.

   On new or less saturated markets, an MVP is sufficient.

3. Defining the Business Objective Clearly define what business goals the initiative should achieve within the testing framework. This will help focus on key functions and identify which risks need to be minimized through MVP/MLP.

4. Customer Research Conduct research to identify which functions are most important for your target audience. Use card sorting or Kano method analysis.

5. Choosing the Form and Creation Choose the cheapest form to implement PoC, MVP, or MLP, minimizing costs while testing the key assumptions. This may involve creating prototypes, a test stand, a landing page, or a minimal version of the product using no-code platforms.

6. Testing and Data Collection Select the testing method (A/B testing, "before-after" analysis, observational method, diary studies) and conduct the product in an experimental phase to collect data and analyze the business impact.

7.Analyzing Results and Scaling Analyze the collected data and make informed decisions about whether to scale the initiative or modify it. If the results are positive, transition the initiative to industrial-scale deployment to maximize the business impact.

Conclusion

This approach will help you get answers to your business questions while reducing the risk of wasting resources on products and projects that are unlikely to deliver positive business results.