Using the Product Discovery Canvas, Part 6: Validate if it is the right Product to build
Box 7 is based on the work of Alberto Savoia. In 2015 I read his early work, emailed him, and was lucky enough to engage him in a half-hour phone conversation.
If you’ve been following this blog series, you’ve probably noticed a pattern. We start with big ideas (vision, personas, goals & success measures), get more specific (user stories), and now we’re about to get really, really focused. Discovery Box 7 on the Product Discovery Canvas is all about validation: Validate if it is the right Product to build.
This is where we take all our user stories and personas and ask the uncomfortable question: “Do people actually want this?”
The Uncomfortable Truth About Product Failure
Let me share something that Alberto Savoia learned the hard way. As Google’s first Engineering Director and a serial entrepreneur, he knows a thing or two about building products. But he also knows about failing. Hard.
As he explains in his book The Right It: Why So Many Ideas Fail and How to Make Sure Yours Succeed, most new products fail in the market. Not because they’re poorly executed. Not because the technology doesn’t work. But because they’re the wrong thing to build in the first place.
Think about that for a moment. All the clean, well crafted, and flawlessly executed code in the world won’t save you if you’re building something nobody wants.
The Right “It” vs Building “It” Right
This brings us to Savoia’s core insight: make sure you’re building The Right It before you build It right. It’s a simple distinction that changes everything.
Most of us (myself included) are quick to jump into building it. We get excited about features and technologies and user interfaces. But Savoia forces us to step back and ask: “Should this thing exist at all?”
That’s what pretotyping, his methodology outlined at Pretotyping.org, is all about. It’s not prototyping (seeing if you can build it). It’s pretotyping (testing to see if you should build it).
Your Own Data (YODA) is What Matters
Here’s where Savoia gets really practical. He talks about the importance of YODa—Your Own Data. Not market research reports. Not what your competitor is doing. Not what some analyst thinks. Your own data from your own experiments with your own potential customers.
As he puts it, asking people “if we build it, will you buy” is just collecting promises and opinions. Instead, you need to say “if you buy, we will build” and see what happens.
Money talks. Behavior talks. Everything else is just noise.
Getting Specific: The Market Engagement Hypothesis
Before you can validate anything, you need to get crystal clear about what you believe. Savoia calls this your Market Engagement Hypothesis (MEH). It’s your specific belief about how the market will engage with your idea.
For the Card SafeZone app, a vague MEH might be: “People will love an app that prevents credit card fraud.”
A useful MEH is more like: “Urban millennials who shop frequently online and in-store will pay $2.99/month for real-time credit card safety alerts that prevent fraud before it happens.”
See the difference? The second one is testable.
The XYZ Framework: Making It Measurable
Savoia’s XYZ framework makes this even more precise: “At least X% of Y will Z.”
- X = The percentage of your target market
- Y = Your specific target segment
- Z = The specific action they’ll take
For Card SafeZone: “At least 15% of urban professionals aged 25-40 who have experienced card fraud will download and use our app within the first month of launch.”
Now you have something you can actually test.
Pretotyping Techniques That Actually Work
The beauty of Savoia’s approach is that you don’t need to build anything to test these hypotheses. Here are some of his pretotyping techniques that have been famously applied:
Fake Door: Create a landing page announcing that your product exists. See how many people try to sign up or buy.
For Card SafeZone, we created a “coming soon” landing page, used google ad words to capture traffic, and collected email addresses to track interest.
YouTube Pretotype: Make a video showing your product concept. If people won’t watch a 2-minute video about your solution, they probably won’t use the actual product.
This YouTube is an entertaining look at how to prototype a product concept. And now this is really easy to accomplish using AI to generate compelling video and audio (https://www.linkedin.com/posts/albertosavoia_great-example-of-a-youtube-pretotype-activity-7090015963105951744-6nai?utm_source=li_share&utm_content=feedcontent&utm_medium=g_dt_web&utm_campaign=copy).
One-Night Stand: Run a short-term experiment. Set up a booth at a mall, run a limited beta, or offer a “coming soon” pre-order. See what happens when you put yourself out there.
McDonald’s tests new menu items by adding them to a limited number of restaurants and tracking sales. They simulate the product’s existence without building a fully functional version, gathering data on customer demand before making a significant investment.
Prototyping Quick Reference Guide https://www.albertosavoia.com/uploads/1/4/0/9/14099067/pretotyping_quick_reference_for_stanford_ms_e_277.pdf
The key is to test the market engagement, not the technology.
Hyperzooming: Making It Actionable Right Now
One of Savoia’s most practical concepts is “hyperzooming.” Start with your massive target market and zoom in until you have a small, local, representative group you can test today.
Instead of “all credit card users,” zoom to “credit card users in downtown Chicago who buy morning coffee and lunch.” Instead of “small businesses,” zoom to “coffee shops within 5 miles of our office.”
This makes validation experiments feasible and affordable. We could test the Card SafeZone app by walking around the neighborhood, not by launching a national marketing campaign.
The TRI Meter: Understanding Your Results
After each experiment, Savoia suggests using what he calls the TRI meter to judge your results:
- Very Likely: Results significantly exceed your hypothesis
- Likely: Results meet or slightly exceed your hypothesis
- Unlikely: Results fall short of your hypothesis
The goal isn’t to prove your idea is brilliant. The goal is to learn whether there’s real market demand before you invest serious time and money.
When to Pivot, When to Persevere
Here’s something I love about Savoia’s approach: he doesn’t see failure as failure. He sees it as learning. If your first experiment doesn’t work, “tweak it and flip it before you quit it.”
Maybe your target market is wrong. Maybe your value proposition needs adjustment. Maybe your pricing is off. Run another experiment. Learn more.
The goal is to find the version of your idea that people actually want, not to prove that your original idea was perfect.
Making Validation Real for Card SafeZone
Let’s get practical. How would we validate Card SafeZone?
- Fake Door Test: We created a landing page advertising “Card SafeZone: Know Before You Swipe.” And tracked sign-ups.
- Coffee Shop Experiment: Partner with a local café to offer “fraud-safe” card reading. See if customers care.
- Bank Survey: Ask bank customers if they’d pay for real-time fraud prevention. But don’t just ask—ask them to put down a deposit.
Each experiment would teach us something about whether people actually want what we’re building. I regret not taking the time to implement and learn from validation options 2 and 3.
The Bottom Line
Validation isn’t about perfecting your idea. It’s about learning whether your idea is worth pursuing at all. As Savoia says, test a little before you invest a lot—or even better, test a lot before you invest a lot.
As a dojo coach/software coach, my experience with large organizations has been that they will embrace Agile/agile (not an echo, if you know you know), but they consistently fail to understand the benefits of pretotyping. Often the response is, “the business knows exactly what our customers want!” In contrast, startups and small businesses easily see the value of learning through pretotyping.
In the next blog, I will move to the final discovery box: Learn from the Product (Build-Measure-Learn). That’s where we take validated ideas and turn them into validated products.
Take time and try some pretotyping to validate your product ideas. Please, share your experiments with me—I’d love to hear about your experiences with validation in action.
References and Further Reading:
- Savoia, Alberto. The Right It: Why So Many Ideas Fail and How to Make Sure Yours Succeed. HarperBusiness, 2019.
- Savoia, Alberto. “Pretotyping.org.” https://www.pretotyping.org/
- Product Discovery Canvas: https://productdiscoverycanvas.com/