Since its release 21 years ago, Google Search has been a success story for product design excellence. With its superiority and ubiquity, Google sets unattainable standards for high-quality software products. Search is at the center of everything. This article shows the future of product design from three aspects: the core principles of Google search, adaptive design, automated testing and iteration, so let's take a look.
Since its release 21 years ago, Google Search has been a success story for product design excellence.
Over the past 20 years, Google has worked toward its ambitious goal of "organizing information around the world and making it universally accessible and useful." - Outperforming all competitors. It's not just search, but Google and its parent company Alphabet, which have achieved unique successes in almost every category of software. As of May 2019, YouTube had more than 2 billion monthly active users, 2.5 billion active Android devices, more than 1 billion monthly active users of Google Maps, and more than 1.5 billion monthly active users of Gmail.
With its superiority and ubiquity, Google sets unattainable standards for high-quality software products. Search is at the center of everything.
Larry Page summed up his vision for search in a 2012 interview with Fortune magazine: The perfect search engine will truly understand your needs. It will deeply understand everything in the world and give you exactly what you need.
Just by studying how that vision becomes a reality, you can gain insight into what users expect from a great product. By applying these insights, you can try to achieve the same usability and usefulness as the fine-tuned Google search device.
< h1 toutiao-origin="h2" > core principle</h1>
From day one, Google Search shows how powerful some simple product design rules can be.
<h2 toutiao-origin="h3" >1</h2>
The definitive design choice for Google Search (which made it stand out in the 1998 search environment) was related to search.
Google's original homepage was around 1998
In 2019, this may seem like an inevitable style for search engines, but take a look at some of Google's early competitors when it launched:
The first page of the four competing search engines, also around 1998
The difference is clear at a glance. Google's interface is transparent: its role is obvious. On the other hand, Google's early competitors were not transparent. Search is just a sidebar, a complementary feature, just one of hundreds of elements on the page.
There are two reasons for this:
Search is still a feature that is difficult to implement correctly. If you used the internet a lot in 1998, you probably won't forget how long it will take to find the right page, even for complex queries like "corgi OR dachshund NEAR "cute dog", finding the right page can take multiple attempts, and most search results have nothing to do with what you're looking for.
The most successful Internet companies of the 90s, such as AOL and Yahoo Yahoo, curated and aggregated the web. They provide users with personalized "start pages" including links to news, weather, financial markets, and online shopping. Content on the web is often of poor quality and low quantity; for a small number of website planners, it is easy to hand-pick and provide the best content the Internet has to offer.
Google's focus on "transparent" search — "tearing it down" from competitor aggregation-based approaches — has placed a big bet on the importance of search.
As the size and standards of the internet grew exponentially, this bet paid off. All along, google.com has always been just a search bar:
Google's 2019 search page
<h2 toutiao-origin="h3" >2. No experience required</h2>
In the past few years, the term "visibility" has begun to be used to describe the characteristics of software products. While there is no clear definition, I think it looks like this:
Visibility: Enables users to take full advantage of the interface quality of a feature without guidance.
If users can quickly learn how to get the most out of the feature, the feature has a high degree of visibility.
If inexperienced users are unable to use or benefit from the feature, the visibility of the feature is low.
Taking door handles as an example, some handles have high visibility:
If it is to be rotated, the handle will be round;
If it is necessary to press, it is leveraged.
Some have low visibility: for example, the door handles of vertical rods appear to be pushed or pulled when the door can only be pushed open. (Note: These low-visibility door handles belong to Norman doors and are named after Don Norman.) Norman coined the term "Affordance" to describe design elements that hint at how a thing should be used. ）。
Google Search is the gold standard for visibility. This is because the interface can be smoothly adapted to personal use cases and experience levels without having to configure any settings. Google is very confident that they have removed all traces of the Settings page:
"In 2017, Google got rid of 'advanced search.' Why? Because no one clicks on it.
Initially, when you want to do a geo-search, Google will help you jump to advanced search. Now they know you're doing a geo-search and show you the map."
To reiterate: needless to say, Google Search is one of the most advanced search engines. Want a picture of a cat? Enter "Cat Photo"; want to convert 23.45 parsecs to light years? Enter "23.45 parsecs to light-years". The Google search learning curve is a gentle line.
<h2 toutiao-origin="h3" >3</h2>
One of the ultimate principles google has always adhered to is that no matter what the user enters— search always works. It is resilient. this
It may seem trivial, but anyone who has built multiple types of input forms knows how challenging unpredictable user behavior can be.
Google Search does just that while processing large amounts of data: it proudly reports that searching for "dogs" generated about 5.48 billion (54 billion) in 0.89 seconds! results.
Meanwhile, a search for "zzzzzxx
The only mistake users see is if their search query is too complex to display logical results. Even so, it's a fact, and it's hard to think it's a mistake. It just gives users some advice:
Useful search error pages for Google
<h1 toutiao-origin="h2" > two, adaptive design</h1>
The core tenets of Google Search — the design philosophy that came up from the beginning — are just one part of its success story. Recently, Google Search has been designed to deliver information before the user clicks on a search result. To do this, Google has adopted an approach called adaptive design.
Adaptive Design: The practice of creating a user experience by designing small, independent components, and how to display the rules for these components according to the needs of individual users.
Adaptive design means that for each user's search, a custom interface is created that shapes itself into the information it displays. Consider the following example: How to change the search results page for different use cases.
The first way Google Search adapts to the needs of users is to rearrange the navigation to fit the results.
In the "lizzo" example, the navigation under the search box is: (in order) Images, Videos, News, Shopping, More.
In the "tel aviv" example, the navigation is: news, pictures, maps, videos, more; search for "aapl" (Apple's stock code), the navigation shows: finance, news, books, shopping, more; Google has 362,880 unique ways to arrange the navigation to fit the search query.
However, the biggest example of adaptive design is the layout of the search results themselves. The results page is completely modular: depending on the search results, different elements appear in different configurations.
For example, the search results for musician Lizzo focus on media: a set of modules that display videos, pictures, and songs in native format. It also shows recent news, tweets and upcoming events, as well as links to Lizzo's profiles on YouTube, Twitter, Facebook, Instagram and SoundCloud. It's not until the bottom of the page that we see elements that look like traditional search results.
Search results in the Israeli city of Tel Aviv, on the other hand, provide travelers with priority information.
Pictures, maps, local weather, and travel-related questions ("Is Tel Aviv safe for tourists?"). "What is Tel Aviv famous for?" ") takes precedence over traditional search results. The module promotes activities in Tel Aviv as well as recommendations for other nearby cities.
Thousands of different modules can appear on search results pages, from simple layout-driven modules to completely separate applications. For example, on the search results page for "aapl", the ticker symbol module displays the current price and an interactive historical price chart.
With adaptive design, all decisions about content, format, and order are algorithmic. The role of the designer is no longer to create a clear external layout. Today, designers of cutting-edge products, as well as designers of everyday products of the future, are making decisions about the rules that generate these layouts.
<h1 toutiao-origin="h2" > three, automated testing and iteration</h1>
The driving force behind the transition from explicit static design to implicit adaptive design is scale. For the first time since 2000, nearly 4.2 billion people have used the Internet. There's reason to believe that most of these people use Google searches. Without advanced testing and automation, no design team could meet the needs of so many users.
A chart from a 2010 paper describing Google's testing method
Google was the first to apply automated testing to product design. The first A/B test of the search was held on February 27, 2000.
Despite a technical glitch that ruined the test, Google doubled it:
By 2011, they were conducting nearly 20 A/B tests on search algorithms a day. Six years later, that number increased fivefold;
In 2017 alone, Google conducted 31,584 tests on its study participants. This is a new test every 20 minutes throughout the year. These tests resulted in 2453 changes in the user experience, about 7 times a day.
These staggering numbers give us a glimpse into the future of product design:
As software products grow to billions of new users, the opportunities to learn and improve the product go far beyond the capabilities of traditional screen design tools such as Sketch, Invision Studio, or AdobeXD.
These traditional design tools are suitable for designers who work on a relatively simple and minimally varied user experience. Feedback on these designs often comes from stakeholders, and using data to enhance the design is a manual process. The speed of the design progress is limited by the number of designers on the team.
Companies like Google, on the other hand, are developing entirely new tools that enable researchers to experiment quickly and immediately deploy what they've learned. For example, Uber built a platform that runs more than 1,000 experiments simultaneously. The speed of improvement is no longer limited by the ability of designers to create models and prototypes.
To keep up with the scale of the internet, product designers must be familiar with the language of statistics and machine learning. Product design is not about creating the right experience, but about defining a set of experiments that generate the best insights.
<h1 toutiao-origin="h2" > IV. Epilogue</h1>
The future of product design is not for everyone. Doug Bowman, one of the first designers Google hired, publicly denounced the quick trial when he left the company in 2009:
Yes, it's true that Google's team can't choose between two shades of blue, so they're testing 41 hues between each blue to see which one performs better.
Recently, I debated whether the border should be 3, 4 or 5 pixels and was asked to prove my example. I can't work in such an environment. I'm tired of arguing about such tiny design decisions. There are many more exciting design problems in the world that need to be solved.
But Google and other industry leaders such as Amazon, Netflix, Facebook, and Airbnb have demonstrated the potential of designers who can work in a fine-tuned, adaptive environment. After Bowman left, they continued to innovate: like it or hate it, and Google succeeded in large part because of their commitment to superior product design. This couldn't be more obvious in Google searches.
Original link: https://www.uxbooth.com/articles/what-google-search-shows-us-about-future-of-product-design/
This article is translated by @Hitomi and published by Everyone is a product manager, and reproduction without the permission of the author is prohibited
The title image is from Pexels, based on the CC0 protocol