One of the most prevalent mistakes I see in identifying people’s needs is the assumption that attitude predicts action. Just because someone says they need a certain product feature does not necessarily indicate that they would need or use it.
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the first major redesign of its popular News Feed … was the culmination of one long year of work by 70 engineers and designers.
[…]The social network surveyed hundreds of thousands of users, and many responded with the same request.
Jane Justice Leibrock and her team of researchers also conducted dozens of face to face interviews on the Facebook campus to get feedback from users.
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The more sustaining your innovation, the more the market is understood or, at least, understandable. The problem and solution are knowable. Why? Your customers are smart. They understand the problem and solution and so are believable. The features they ask for likely represent their true needs.
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The Twitter User Research team is looking for Twitter users to participate in an upcoming research study.
Details of the study:
* The study will take place in January via phone and web screen sharing
* The duration of the study session is about 1 hour
* You’ll receive a $100 Amazon.com gift card as a token of our appreciation— Twitter’s User Research Team Launches Survey And Pays $100 For Your Participation
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What is really confusing to the world is that engineers, and most product people and actually most people in business get trained on the development half of things. We actually don’t know a thing about research; we do it completely wrong. Development is all about narrow and deep; I want to be as efficient as possible with the resources that I have to build a specific thing in the shortest time possible. Let’s not waste a bunch of time. Research is the opposite. It’s broad and shallow. And if you go narrow and deep too early, you’re effectively wasting time.
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Most of the processes that we learn as product managers are actually pretty detrimental to the research side of things. So if you want to make a breakthrough, you need to create a space for something like this.
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People think they can learn what to build from our customers, but of course, you can’t, in technology especially. Number one, because customers don’t know what’s possible because technology moves so fast. […] Number two, and this is more profound, because it applies to all of us: none of us know what we want until after we see it. […]
That’s not to say we don’t talk to our customers; just the opposite. The way we overcome this is by talking to a lot of customers. Most teams I work with are talking to more customers in a week than some do in a year. But unlike the marketing mindset where you ask the customers questions, we’re testing on them; we’re seeing if our ideas actually work.
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In most Agile teams, when you mention commitments (like knowing what you’re going to launch and when it will happen), you get reactions ranging from squirming to denial… the root cause of all this grief about commitments is when these commitments are made. They are made too early. They are made before we know if we can actually deliver on this obligation, and even more important, if what we deliver will actually solve the problem for the customer.
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In a Dual-Track Agile environment, the Discovery Track is all about answering these questions before we spend the time and money to build production quality products… So the compromise is simple. The product team asks for a little time to do product discovery before commitments are made, and then after discovery we are willing to commit to dates and deliverables
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Don’t listen to users
Observe behavior…
I don’t listen to users because of the psychology of attitude & behavior
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Many studies found no relationship between attitude and behavior
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Don’t ask what people need
Instead observe what they doDon’t ask for feedback
Instead watch them use it— GA class: High-Quality, Impactful, Fast UX Research for Engineers
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Human beings have two systems in their brains — an empathetic social system that allows us to simulate other people’s experiences, and an analytical system that allows them to solve logical problems.
In an experiment at Case Western Reserve, it turns out you can’t run both systems at the same time. After watching test subjects alternate between empathetic and analytical problems in an fMRI, they noticed that one would turn off when the other turned on.
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We wanted to know which pieces of information about an app users most commonly employed to make a decision about installing an app regardless of the App Store used. The three most frequently reported items were:
- Rating
- Screenshot
- Review
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In a startup UX researchers are toxic, but UX research is essential.
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Sometimes we do user research. Sometimes we build prototypes and see how they feel. Often, however, we’re working on products that have no analog for comparison in research and whose merits are difficult to gauge in the abstract or at small scale.
[…]Every day, we run hundreds of tests on Facebook, most of which are rolled out to a random sample of people to test their impact.
Other products might require network effects to be properly tested, so in those cases we launch to everyone in a specific market, like a whole country.
That’s why we’ve developed a sophisticated and flexible tool called gatekeeper to make sure tests don’t collide with each another and that they provide statistically meaningful results. -
If the product discovery team is truly doing product discovery, … they’ll typically find that at least half of what is on the roadmap is simply not worth doing (usually because the customer doesn’t value it as much as we had hoped
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When you talk about data-driven decision making it’s not necessarily about the everyday metrics. It’s about trying to figure out behavior in the data. And that can come through looking at actual data in your databases, or it can come through interviewing users and trying to figure out, “This person’s a really engaged user of my product…. Why?”
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