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How to Build the Right Product with Alberto Savoia (ex-Innovator at Google)
Market Research, Skin-in-the-Game, Your Own Data, XYZ Hypothesis, Pretotyping, Flirting With Ideas.
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How to Build the Right Product with Alberto Savoia (ex-Innovator at Google)
I decided to start a video podcast. My guest is Alberto Savoia, the first Engineering Director at Google.
He's currently a lecturer at Stanford University. Alberto is also the author of the international bestseller The Right It: Why So Many Ideas Fail and How to Make Sure Yours Succeed.
Here you can listen to our conversation:
Here are the top 9 actionable tips with additional information and resources:
1. Market Research: Ask for Skin-in-the-Game
Over 80% of new products fail. Alberto Savoia calls it “the law of market failure:”
”Most new products will fail in the market, even if competently executed.” - Alberto Savoia, The Right It
The primary reason is that people build something nobody needs. Meanwhile, many of these failures can be avoided.
It’s essential to understand that it’s much easier to open your mouth than to open your wallet.
When it comes to market validation, opinions (“It’s awesome”), encouragements (“Go for it!”), comments and likes on social media, and surveys are useless.
Your market research must include “Skin-in-the-Game Points,” which in “The Right It,” Alberto defines as:
Paweł’s comment: In the book, Alberto mentions that you can adjust those points to your local currency. While doing so, don’t be too precise (e.g., €0.73).
2. Collect Your Own Data (YODA)
In your market research, don’t rely on data collected by others (Other People's Data, or ODP for short).
The fact that others succeeded with similar ideas doesn't mean you will also succeed. Similarly, the fact that others failed with similar ideas doesn't mean you will fail, too.
They had different products and might have experimented in different conditions.
A good example is what Tesla did with the Tesla Model 3.
Before 2016, Honda, Ford, and Toyota failed. If Elon Musk relied on their data, he would have never built the Tesla Model 3. But he decided to collect his own data (Your Own Data, YODA for short).
On April 1, 2016, Elon proposed a mass-market, affordable electric car and started collecting orders. In 24 hours, he received more than 115,000 orders. In October 2016, Tesla held close to $700 million in customer deposits.
That’s a lot of skin in the game. $35 billion Skin-in-the-Game points, to be precise. Now, they could go forward with building the first gigafactory.
Ignore Other People’s Data (ODP) completely, and collect Your Own Data (YODA) with Skin-in-the-Game.
3. Say It With Numbers: The XYZ Hypothesis
Many formulate a Market Engagement Hypothesis (MEH), which combines the fundamental premise behind their idea and how the market will engage with it.
Unfortunately, many of those hypotheses look like this: “Many people will build a fast, electric car at a reasonable price.”
To test the idea, we must “say it with numbers,” for example: “At least 5% of mid-size luxury sedan buyers will buy a Tesla Model 3 in 2019 for $40K or more.”
The basic form of the XYZ hypothesis is “At least X% of Y will do Z,” where:
X% represents the percentage of your target market.
Y represents your target market (e.g., “mid-size luxury sedan buyers”).
Z represents how they will engage with your product.
You can learn more about the XYZ Hypothesis from this video:
Paweł’s comment: Alberto focuses on market engagement. Other hypotheses, like hypotheses related to feasibility or specific features, might have a different form. I see no contradiction.
We also discussed that it’s okay to have multiple hypotheses related to market engagement as long as every hypothesis is grounded in data. But as Alberto explained, it’s essential to start with one and then progress in iterations.
Next, you want to test your idea. How to do it? The way you don’t want to do it is by building a product.
4. Test Your Ideas by Pretotyping
Alberto Savoia uses the term “pretotyping” to emphasize the importance of validating an idea without building a product, as opposed to building working “prototypes.”
Here, you can download a free PDF with nine basic prototyping techniques:
Paweł’s comment: In the past, I have been using the term “MVP prototype,” proposed by Dan Olsen, to highlight the same principle. Given how much confusion the term “MVP” involves and that people are unwilling to adjust the wording, I feel more and more convinced about the term proposed by Alberto.
5. Remember That Prototyping Is the Most Ethical Thing to Do
Many people are concerned by the Fake Door technique, in which people are unaware they are looking at a non-existing product.
I loved Alberto’s insight that the most unethical thing to do is to waste time and money, often borrowed from others, knowing that most products will fail in the market.
While every tool can be misused, pretotyping, when done in good faith, is the most ethical thing to do. Fake Door experiment included.
6. Collect Enough Evidence
Your investment should be proportional to the evidence you get.
Alberto explains it in detail in his “The Math of Success” video series.
In the first introduction video, he introduces the concept of "Probability of Success."
Using buckets to quantify the likelihood of success can make product managers more effective and data-driven.
More information (the first video):
7. Interview Customers Only to Explore the Problem Space
While the book doesn’t mention interviewing customers, we confirmed it’s perfectly okay to do it in order to understand their needs and ideate.
The problem is when people’s opinions are used when validating an idea (market engagement).
Interview customers to understand their needs, desires, and problems in depth. At the same time, when validating a market engagement, formulate the XYZ Hypothesis and rely only on Your Own Data (YODA) with Skin-in-the-Game, not opinions.
8. Fall in Love With the Problem but Flirt With the Idea
The first idea rarely works. The good news is that each experiment provides you with more data (YODA).
Return to the ideation phase, adjust the idea, and try again.
Fall in love with the problem but flirt with the idea. Keep exploring the solution space. Only after you exhaust possible options, consider abandoning the idea completely.
9. Build a Culture of Experimentation
There are three reasons people don’t apply the knowledge in practice:
They don’t know about it: According to Alberto, all people in higher positions exposed to those ideas buy them. It’s essential to focus on data. Ask them how many products they launch, being 100% certain they will succeed, yet they didn’t work. This should resonate. They often say they can't believe they don't teach those techniques during an MBA!
Entrepreneurs fall in love with ideas: Some people are passionate and want to build the thing, whether or not it will succeed. It's okay as long as you invest your own money and time. When you take money from others (e.g., VC), the ethical thing to do is experiment to validate your assumptions.
Fear of rejection: Market rejection hurts like romantic rejection. People keep postponing the validation, trying to make it perfect. It’s essential to realize that you can only make your problem worse by delaying the validation.
Paweł’s comment: The leadership must understand and promote a culture of experimentation. Expose them to those ideas using data.
Not all failures are avoidable. But you don’t want to be the person who fails and says, “If I only did this experiment!”
A good failure is when the value of the lesson is greater than the cost of the lesson. A bad failure is when the value of the lesson is much less than the cost of the lesson.
If you have to fail, make sure it's a good failure.
Books and resources:
“The Right It” on Amazon - this is the best book I read in 2023
Where to find Alberto?
Web & contact: https://www.albertosavoia.com/
YouTube channel: https://www.youtube.com/@AlbertoSavoiaVideos
🤖 AI-berto: https://pretobooks.onrender.com/
The Product Compass Podcast:
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Take care, Paweł