The Lean Product Playbook: How to Innovate with Minimum Viable Products and Rapid Customer Feedback

by Dan Olsen

When better solutions that deliver more customer value come out, the upper value on the right side of the scale gets redefined, shifting everything to the left. In contrast, the importance axis is more stable.

You might wonder why I used different rating scales for importance and satisfaction. Part of the reason is that there are two types of rating scales: unipolar and bipolar. A bipolar scale goes from negative to positive, whereas a unipolar scale goes from 0 to 100 percent of an attribute. It's usually best to measure satisfaction using a bipolar scale; since people can be satisfied or dissatisfied, a negative score makes sense. In contrast, importance is just a matter of degree—without any negative value—and therefore better measured with a unipolar scale.

For any bipolar scale, I recommend using an odd number of choices so that there is a neutral option in the middle.

The bigger the gap, the more underserved the need.

The strength of gap analysis is that it produces a single number that is very easy to calculate. However, its biggest shortcoming is that it treats all gaps of equal size the same.

With performance needs, more is better. As the need is more fully met, the resulting customer satisfaction increases.

Must-have needs don't create satisfaction by being met. Instead, the need not being met causes customer dissatisfaction.

Delighters provide unexpected benefits that exceed customer expectations, resulting in very high customer satisfaction. The absence of a delighter doesn't cause any dissatisfaction because customers aren't expecting

A good product is designed with focus on the set of needs that are important and that make sense to address together.

You also don't want to unnecessarily risk wasting resources with an initial product scope that is too large.

If you test your MVP and realize that your assumption was wrong, you will have to revisit your hypotheses about the relevant needs to address.

Strategy Means Saying “No”

Here's what Steve Jobs had to say about saying “no”: People think focus means saying yes to the thing you've got to focus on. But that's not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I'm actually as proud of the things we haven't done as the things I have done. Innovation is saying no to 1,000 things.

Your key differentiators are the performance benefits where you plan to outperform your competitors as well as your unique delighters.

A clear value proposition decreases the likelihood that you are just launching a “me too” product, focuses your resources on what's most important, and increases your chances of success.

For your MVP, you want to identify the minimum functionality required to validate that you are heading in the right direction. I call this an MVP candidate instead of an MVP because it is based on your hypotheses. You haven't yet validated with customers that they agree that it is, in fact, a viable product.

divergent thinking, which means trying to generate as many ideas as possible without any judgment or evaluation.

convergent thinking, where you evaluate the ideas and decide which ones you think are the most promising.

Wake created a set of guidelines for writing good user stories; to make them easier to remember, he uses the acronym INVEST:

Working in smaller batch sizes increases velocity because they enable faster feedback, which reduces risk and waste.

A good operating principle is that stories that are estimated to require a large number of points—above some maximum threshold value—need to be broken down into a set of smaller stories that are below the threshold value.

When you have two feature ideas with the same ROI, it's best to prioritize the smaller scope idea higher because it takes less time to implement.

You can create a preliminary product roadmap by continuing this process and creating columns for each future version with each column containing the feature chunks that you plan to add.

The pyramid on the left illustrates the misconception that an MVP is just a product with limited functionality, and that reliability, usability, and delight can be ignored. Instead, the pyramid on the right shows that while an MVP has limited functionality, it should be “complete” by addressing those three higher-level attributes.

Qualitative means that you are talking with customers directly, usually in small numbers that don't yield statistical significance. Here, you care about the detailed information you learn from each individual test. You may try to discern patterns across the results, but statistical significance isn't a primary concern.

Quantitative research involves conducting the test at scale with a large number of customers. You don't care as much about any individual result and are instead interested in the aggregate results.

Quantitative tests are good for learning “what” and “how many”: what actions customers took and how many customers took an action

In contrast, qualitative tests are good for learning “why”: the reasons behind different customers' decisions to take an action or not.

In general, when you are first starting to develop your product or marketing materials, it is most beneficial to start with qualitative tests to gain some initial understanding. If you jump straight into quantitative tests without doing any qualitative tests, they usually don't perform as well—and even if they do, you won't know why.

These types of tests involve showing customers your marketing materials and soliciting their feedback.

This test is an attempt to understand how compelling they find this marketing material and why.

The landing page describes the product you plan to build and asks customers to express some level of interest, which is usually a “sign up” button or a link to a “plans and pricing” page.

The key metric that these tests measure is the conversion rate: the percentage of visitors to your landing page that clicked on the button to convert from a prospect to a customer.

There are two fundamentally distinct times when you can conduct qualitative product tests: before you've built your product and after you've built it. Both are valuable.

You can test your product's design with customers before you build your product.

After you build your product, you can test it with users—which has the advantage that the fidelity of what you're testing is 100 percent.

The Wizard of Oz MVP appears to users as the real live product. The goal is to validate the manual steps that are required before making the investment to build out an automated solution.

The fake door or 404 page test is a good way to validate demand for a new feature that you are considering building. The idea is to include a link or button for the new feature and see what percentage of customers click on it. This lets you gauge whether customers actually want the feature before you spend the resources to build it.

You don't even notice the user interface and are able to focus on accomplishing the task at hand. The product may even be fun to use and convey emotional benefits such as confidence in your abilities or peace of mind. A great design may lead you to what psychologists call a state of “flow,” where you are completely immersed in using the product.

benefits. Poor UX gets in the way, preventing the user from realizing the benefits. Great UX makes it easy for the user to realize the benefits that the product's functionality offers. In addition to addressing benefits that customers find valuable, a great UX also achieves a high degree of usability and delight.

Usability focuses on the users' goals and the tasks they need to perform to achieve those goals.

Beyond the successful completion of tasks, usability also includes efficiency.

In addition to actual physical effort such as clicks and keystrokes, perceived effort is also important.

You can mentally overwhelm users by showing them too much information or giving them too many choices.

The likelihood of a user successfully completing a task is directly related to the amount of effort it takes.

The more user effort required to take an action, the lower the percentage of users who will take that action. The less user effort required, the higher the percentage of users who will take that action.