The Minimum Lovable Product (MLP) Framework

Everyone raves about the MVP (aka the minimum viable product), brought to fame by Eric Ries' The Lean Startup. Ironically, the MLP (aka the minimum lovable product) doesn't get enough love. Inspired by Zhang's post on the topic and my own experience in building 0 to 1 products at more established companies, I want to start raving about the MVP's more lovable cousin, the MLP.


Types of Product <> Market Fit Work


There's a few types of product<>market fit work (expanded on from Brian Balfour's post on product market fit) that are important to understand in order to determine whether you should focus on an MLP or an MVP:


Same market, new product - Keeping the market the same, but launching adjacent products.

  • Lyft expanding to Bikes & Scooters

  • Netflix streaming platform → production company & TV network

  • HubSpot going from a Marketing Product for mid-market companies to adding Sales and Customer Support Products for mid-market companies

Same market, new platform - Keeping the market and product value prop the same, but enabling it on a new platform.

  • Bank of America launching mobile banking

  • New York Times launching a digital presence (both online & mobile

  • Netflix DVD delivery → streaming service

New market, same product - Keeping the product value prop the same but enabling it for a new adjacent market.

  • Slack launching Slack Enterprise

  • Roman expanding from men’s health products to women’s health products

  • Almost any product launching international markets

New market, new product - Launching a completely new product to a completely new market.

  • Uber launching Uber Freight or Uber Eats

  • Ro expanding into at-home vaccine delivery

  • Intuit launching Turbotax (adjacent to Quickbooks)

New market, new platform - Launching a completely new product to a completely new market on a new platform.

  • Amazon launching AWS

  • Facebook & Google launching AR glasses

  • Airbnb initial launch

  • Uber initial launch


When to use the MLP vs. MVP?


Ultimately, most new product work is about validating, or invalidating, assumptions we have about the problem, the solution or the market in order to minimize risk.


Types of risks in building out new products

  • Problem risk = is there a problem?

  • Solution risk = is this the right way to solve it?

  • Market risk = can we sell it?

  • Implementation risk = can we build and sell it with the resources we have within a reasonable timeline?

Some of these risks might already be minimized depending on the type of product<>market fit we're pursuing.

So how we approach building a 0 to 1 product depends on the cost associated with what we're building and our level of confidence in the solution:


More known, lower cost = less risk = MLP

Less known, higher cost = more risk = MVP


Put simply: the MLP needs to do a few things very well in order to convince users to adopt and engage with it over however they're solving their problem today. The MVP, on the other hand, needs to help the team learn as quickly as possible.


Let's take some of our examples earlier and see how they fit into the framework.

More known, lower cost = less risk = MLP = HubSpot went from a Marketing Product for mid-market companies to adding Sales and Customer Support Products for mid-market companies. We built an MLP when we launched the Service Hub because we felt confident in the market needs and we got a lot "for free" by nature of our platform.

Less known, higher cost = more risk = MVP = Airbnb launched a new marketplace for booking affordable accommodations. The founders initially tested the concept by setting up their living room during a conference in the local area. This was the right approach because it enabled them to quickly validate and a new concept without spending a lot of time or money.

Put simply: the MLP needs to do a few things very well in order to convince users to adopt and engage with it over however they're solving their problem today. The MVP, on the other hand, needs to help the team learn as quickly as possible.

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