- •Introduction
- •And Cue the Lean Startup
- •Chapter 2
- •Vision, Values, and Culture
- •Vision and Values
- •Version 1
- •Version 2
- •Version 3
- •Over the Horizon: a Framework
- •Personas: Create a Fake Customer
- •If You Get Nothing Else from This Chapter
- •Chapter 4 Wading in the Value Stream
- •Value Assumed Before Deep Customer Interaction
- •Value Validated After Deep Customer Interaction
- •Value-Stream Discovery
- •Chapter 5 Diving In
- •Chapter 6
- •Viability Experiments
- •Crowd-Funding Test
- •Viability
- •Chapter 8 The Valley of Death
- •Minimum Viable Product
- •Your First mvp
- •Buggy Product
- •Unfinished Product
- •Stolen Product
- •Beginning of the End or End of the Beginning?
- •An mvp Takes Guts
- •Thinking Through Viability
- •Mvp Testing
- •Innovate the Funnel
- •Selling to Businesses
- •Marketing
- •Passionate
- •Satisfied
- •Hopeful
- •Convinced
- •Trusting
- •Intrigued
- •Brant cooper
- •Patrick vlaskovits
Chapter 8 The Valley of Death
The Valley of Death is where startups go to die.
You have a minimum viable product (MVP) and a little customer interest. Or you have an MVP you’ve been iterating for months and have customers, but no serious traction. Or you have a solid product some customers are passionate about but little organic growth. Or you have a pretty impressive number of paying customers, but can’t figure out how to find more. Or you’re growing and feel poised for a breakout, but your margins are virtually nonexistent and you are skating on the edge of insolvency.
Your viral coefficient is 0.42. You are officially a Minimum Viable Business (MVB).
If you’re on the disruptive side of the innovation spectrum, your death will be lonely, one of indifference as you wander aimlessly, unknown to your competition and customers. On the other hand, if your idea hews closer to the sustaining side of the innovation spectrum, your death will be instigated (and celebrated!) by your competition and perhaps even unknowingly facilitated by your anti-segments.
Nearly all startups can build product. This isn’t a problem. Founders fail to create enough value for customers; or they create value, but not for enough people; or they fail to truly understand the core value they provide and who might most benefit from it.
They don’t understand their must-have use case. Or they don’t understand how to translate the winning use case for one group of customers to use cases for other segments.
They have customers, but little passion. They have customers with passion, but they don’t know anything about those customers, so they don’t understand how to get more.
The typical entrepreneur’s response to all this? Build features or hire a PR agency. Neither is likely to work.
Getting out of the startup “Valley of Death,” as Eric Ries describes it, requires using the same principles we’ve already outlined—customer interaction, experimentation, and data—but how you use these must evolve. You’re likely no longer validating initial assumptions. You need new assumptions, new experiments.
To escape the Valley of Death you need to move beyond your minimum viable product, and you need an optimized conversion funnel and a customer acquisition strategy that’s ready to scale. The end of the MVB phase is product-market fit.
Way back in the day, we worked with an enterprise software company deploying their product for a leading U.S. financial-services company in a consumer-facing application. It took 50 seconds for customers to log in. The lifeblood of the software company was its professional services team, which had to customize and integrate complicated, buggy product into the huge, complex systems of early Fortune 500 customers, the revenue from which could not be recognized until customer sign-off.
The professional services team jumped in to solve the log-in problem, through a straightforward, analytical, and iterative process of eliminating bottlenecks. They didn’t search for the biggest bottleneck but rather for the first one between the user and the desired result. They didn’t perform workarounds; they fixed problems. When the core engineering team was required to fix APIs, they were forced to despite their complaining. Accumulated workarounds were likely the cause of the problem in the first place.
The team knocked off a five-second issue here, a three-second issue there, until discovering a full table scan that took 25 seconds on a large table! Issue resolved.
This is how to think of your startup endeavor, as well. What’s the next bottleneck? How do we remove it?
