The Product Discovery Valley of Death
Many Product teams only listen to users in the beginning of the product development process.
They gather data from a variety of sources such as customer support calls, quantitative studies and more.
After this initial research, they build their solution but don’t test it as they create it…missing out on customer-led innovation and quick pivots to improve the product.
They use Product Discovery incorrectly to only validate problems.
The next time these teams talk to users might be a usability test just before engineering starts or after the product is launched. At this point, it's too late to pivot the solution if you find out it’s not working with users..
This gap in interacting with users (sometimes lasting months) is the Product Discovery Valley of Death.
A team might have entered the Valley of Death if:
No solution testing happens
No iteration based on user feedback occurs
Only a single solution is created (which leaves little room for experimentation or innovation)
The solution is only vetted by internal stakeholders
They task an entire engineering team for 4-6 weeks to build, test and launch an untested idea potentially wasting $100,000 or more
With prototype-friendly design tools like Figma and self-serve recruiting sites like UserInterviews.com, there’s no excuse to skip solution testing.
Validating an idea by solution testing in the design phase costs much less money since it uses so few engineering resources. It also saves time because iteration in design is much faster than iteration in code.
Just preparing for a user solution test makes your solution better
When you prepare a concept for someone outside of your team, you tend to think deeper about it.
You explore edge cases.
You start thinking like a user.
You visualize continuous flows rather than snapshot-in-time mockups.
Just preparing for a user solution test will improve your approach.
Early solution testing answers significant product questions
After some amount of discussion and debate on early concepts, it’s better to go to users with what you have rather than to continue until you have a “finished” product.
Early testing answers these questions:
Are you targeting the right user?
Does this user have the pain point you’re trying to solve?
Is the user eligible for the opportunity you’re offering?
Are your solutions going in the right direction for these target users?
Early testing reveals user preferences better than additional team meetings (and better than extensive persona development).
Early testing will expose assumptions that the team has made.
Early testing will avoid wasted work if you need to make a pivot.
“Realistic enough” is good enough
Teams are often uncomfortable allowing users to interact with early solutions.
They spend too much time on creating one “pixel perfect” solution when they could expand the solution space by creating multiple “realistic enough” solutions.
Users don't need a pixel perfect prototype to give actionable feedback.
The solution doesn’t even need to be fully fleshed out. It doesn’t need to have all the possible flows. Just create calls to action that lead to possible flows and see which flows you SHOULD build after the users indicate their preferences.
If you are testing regularly, then there will be a next time to explore more depth.
And increased interactions with users shifts the team’s world view to be more inclusive of the customer throughout development.
Summary
By continuously testing solutions and iterating in the design phase, teams can avoid the Product Discovery Valley of Death where good intentions go to die.
Jim is a coach for Product Management leaders and teams in early stage startups, tech companies and Fortune 100 corporations.
Previously, Jim was an engineer, product manager and leader at startups where he developed raw ideas into successful products several times. He co-founded PowerReviews which grew to 1,200+ clients and sold for $168 million. He product-managed and architected one of the first ecommerce systems at Fogdog.com which had a $450 million IPO.
Jim is based in San Francisco and helps clients engage their customers to test and validate ideas in ecommerce, machine learning, reporting/analysis, API development, computer vision, online payments, digital health, marketplaces, and more.
He graduated from Stanford University with a BS in Computer Science.
