Quora's CEO wades in (on Quora, obviously...)
In Summary: Machine learning can help curate a better product over time. Predicting user behavior helps shape your UX around how people will use your product.
Machine learning helps reduce the need for the user to make choices. If you have a search engine, the searches people perform (and the sites they go to) can predict what they'll want to search for next.
Almost all B2C products these days have interfaces that are driven by machine learning recommendations. These includes Quora, Netflix and Spotify. Netflix, one the one hand, gives users very little control over what it will recommend. Twitter, on the other hand, largely constrains your timeline to tweets from people you follow.
The full potential of voice UIs is still to be realized. For now, they remain little more than voice-controlled smartphones, says FastCo's Katherine Schwab.
In Summary: A recent study by Microsoft revealed that most people still don’t have a mental model of how VUIs are supposed to work. The biggest challenge is one of the simplest: it’s hard to understand what they can and can’t do.
Only 14.3% of respondents used their smart home device to shop. The reasons given were the lack of a screen and not knowing how to use the device to shop.
In the main, people use their voice devices to do relatively simple tasks they could also do using their smartphones. The most popular use cases are asking the device to play a song, control smart lights and set a timer. And asking the weather.
This indicates that voice is an auxiliary technology, not a primary one, undeserving of the hype it’s received so far.
To spot the next great product opportunity, focus on what doesn't change, says David Mattin.
In Summary: Consumer trends are made from two fundamental things: change and basic human needs. Most of the products we use today serve some basic human need. Security, value, distraction, convenience and fun are a fundamental part of our nature. They’re never going away.
Truly new ways to serve a basic human need are rare. The best way to spot new trends is simply to look at the new products entering the market and ask: does this serve a basic human need in a new way?
AI is a tech trend. The really powerful trends, that tell you something meaningful about the future, are trends in human behaviour and expectation.
Like it or not, habit-forming technology is already here, says Nir Eyal.
In Summary: As infinite distractions compete for our attention, companies are mastering new tactics to stay relevant in users’ minds and lives. We’re faced with a future where everything will become more addictive.
Companies increasingly find that their economic value is a function of the strength of the habits they create. Following the lead of tech giants like Facebook and Google, product teams everywhere are mastering the mechanics of habit formation to increase engagement with their products.
Habit-forming technology creates associations with 'internal triggers' which bring users back without the need for marketing or stimuli.
As a result, consumers need to understand how habit-forming technology works to prevent unwanted manipulation.
In a marketplace of distraction, products that save you time are going to win, says Gary Vaynerhchuk.
In Summary: Too many people focus on shipping a technical iteration or adding features to a product that only complicates the experience.
No one wants complexity layered upon their daily life. No one cares about specifications and numbers anymore. People literally want cars to drive themselves! They want freedom and simplicity and speed.
AI is an important technology because it saves you time. It can learn and automate processes which would have taken much longer. Virtual assistants save you time. Google Now and Siri save you time. Uber saves you time. It's why they've won.
The main thing product teams should ask themselves is: how does my product expedite a market experience that used to be tedious and tiresome for all?
Customers only care about how our products feel in their hands, nothing else, says Tinder's Jeff Morris Jr.
In Summary: We work in an industry that glorifies the process of everything we build.
We're obsessed with roadmaps, methodologies, acronyms, and productivity tools. But we need to remember that customers don’t care about how we build our products, or our process.
We spend our days writing specs, filing Jira tickets, and editing roadmaps. This is Process.
Our job is to delight customers through the projects we build. Process is important, but do not forget that customers judge us on one thing. This is the Product.
It’s well known that ‘helping is the new selling.’ Which is why delivering product value, measured by user engagement, is the most powerful sales tool you have.
In Summary: Some time ago, SaaS companies discovered they had created a new channel for lead generation. The new channel was the product itself and the new leads it produced became known as Product Qualified Leads, or PQLs. PQLs are users who reach pre-defined triggers that signify strong likelihood to become a paying customer.
The definition of a PQL will differ from product to product. What stays constant is that engagement strongly correlates to purchase propensity. So sales teams can efficiently invest time and energy communicating only with those that tip the scales.
Today, every high-performing SaaS company aligns their product, engineering, customer success and growth teams around a central goal (happy, engaged users) underpinned by robust data that provides measurable outcomes.
No one wants to use an unfinished product its creators are embarrassed by, says WP Engine's Jason Cohen.
In Summary: Product teams have been following the MVP dogma for years without re-evaluating whether it’s the right way to maximize learning while pleasing the customer. Customers want great products they can use now.
Products that do less, but are loved, are more successful than products which have more features, but that people dislike. Google Docs had just 3% of the features of Microsoft Word when it launched. It succeeded because it did a great job at what it was primarily designed for: simplicity and real-time collaboration.
Not every product has to become complex. Some products can (and should) remain simple, lovable and complete.