MVP Dissected: What is it and what is it for?

From Origins to Insights: Understanding the Core of Minimum Viable Products in the Startup World.

MVP Dissected: What is it and what is it for?


In the bustling corridors of the tech and startup realm, buzzwords often flit in and out of fashion faster than you can say "blockchain." Yet, amidst this ever-changing lexicon, one term has clung to our collective consciousness with remarkable tenacity: the MVP. No, not the "Most Valuable Player" you'd cheer for in sports, but the "Minimum Viable Product." Its skyrocketing popularity isn't just because it's a trendy concept but because of its profound impact on how startups approach product development. As Haje Jan Kamps from Techcrunch says, “Startups are essentially machines that build MVPs (minimum viable products) that help answer questions and gradually de-risk the company's value proposition.”

Origins and Definition of MVP

The phrase "minimum viable product" was created by Frank Robinson and made well-known by Eric Ries, the man behind the Lean Startup approach. In Ries's opinion, an MVP is a new product iteration that enables the team to amass the most concrete consumer data with the least amount of work. But in essence, it comes down to this: Fail fast, learn faster.

The concept of an MVP is primarily unrelated to development in practice. Founders and many developers frequently conflate the terms MVP and technology prototype.

Breaking down the definition

Let's get right to it, then. MVPs. Everyone is talking about them, but definitions vary as much as Starbucks' coffee flavors. So why not sort through this MVP jungle ourselves?

  1. Research Deep Dive: We read countless publications, listened to leaders in the field, and even had a few late-night discussions. The objective? Recognize the core meaning of MVP.
  2. Experience Speaks: As knee-deep in product development, we compared these professional judgments to our actual observations. You must determine when theory and practice synchronize because they can occasionally dance.
  3. Purification of the Essence: From this deluge of knowledge and experience, we distilled the constants—the MVP truths that are widely acknowledged—into a manageable number.

The outcome? What are the absolute must-have qualities of an MVP? A sharper, more concrete definition, along with the insights it has to provide. Because at the end of the day, all it is is a machine with a few traits that provide us with information.

Distinctive Characteristics of an MVP:

  1. Rapid Development: We need to build it quickly and effectively.
  2. Feature Minimalism: Just enough features to solve the problem, nothing more.
  3. Niche Appeal: It focuses on a close-knit community of early adopters rather than the broader market.

Essential Data Insights from an MVP:

  1. User Value Assessment: Does the product even matter to our early birds? Does it solve a genuine pain point for them?
  2. Payment Intent Verification: It's one thing for users to nod in approval and another to punch in those credit card details.
  3. Behavioral Analysis: How are users interacting with the product? That is pure gold because many products pivot based on these initial interactions.

Breaking Down the Value of Each Insight Type with Big-Player Examples

Let's see how some of the most prominent players in the market used these insights with their MVPs.

User Value Evaluation - example: Buffer

When we discuss user value assessment, Buffer's MVP journey is standard fare. They made the brilliant choice to evaluate user interest using a straightforward landing page. It is the simplest way to ascertain user demand. And while you can get closer to determining payment intent with this method, it doesn't tell much about how users will behave when using the product. The real kicker, though, is that this "landing page MVP" is perfect for sectors or goods that, by nature, require a significant initial time investment due to complicated rules (like finance or insurance) or tech intensiveness (like rockets or biotech). It informs you if deep diving is even worthwhile.

Payment Intent Verification - example: Zappos

Online shoe purchasing was more of a fantasy in the late 1990s than a reality. Meet the creator of Zappos, Nick Swinmurn, who was so frustrated in 1999 that he couldn't find the shoes he wanted at a nearby mall. Swinmurn used a practical strategy rather than plunging straight in and developing an online collection with a huge budget. He went to his neighborhood mall, took pictures of the shoes, and displayed them on the website. When a person made a purchase, he'd rush back, buy the exact pair, and ship them out. That's quite the hustle, huh? What happens if you're not prepared for these transactions right now? Simple. Simulate the checkout procedure, then when it's time to make the payment, send customers to a page that says "Oops, not ready yet" and asks for their email. It's the intention that counts.

Behavioral Analysis - example: OnlyFans

OnlyFans began as a mere Patreon-esque platform. But here's where things got interesting. By observing how users interacted with their platform, they pivoted to the giant we recognize today. As Michael Seibel (the CEO and co-founder of Twitch) rightly points out, you can chat with potential users all you want, but you will only genuinely grasp if your product solves their problems once it's in their hands. Hand them the product and the feedback is almost instantaneous. Accurate insights stem from real-world interactions, not hypothetical discussions.

In the end, it's not just about having insights. It's about understanding them and, more crucially, acting on them. As we’ve seen, whether it's a landing page or a hands-on MVP, each approach has its merits. The key is choosing what fits your product and market scenario best.


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