The Evolution of Media: Visualizing a Data-Driven Future
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The Evolution of Media: Visualizing a Data-Driven Future

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The Evolution of Media: Visualizing a Data-Driven Future

In today’s highly-connected and instantaneous world, we have access to a massive amount of information at our fingertips.

Historically, however, this hasn’t always been the case.

Time travel back just 20 years ago to 2002, and you’d notice the vast majority of people were still waiting on the daily paper or the evening news to help fill the information void.

In fact, for most of 2002, Google was trailing in search engine market share behind Yahoo! and MSN. Meanwhile, early social media incarnations (MySpace, Friendster, etc.) were just starting to come online, and all of Facebook, YouTube, Twitter, and the iPhone did not yet exist.

The Waves of Media So Far

Every so often, the dominant form of communication is upended by new technological developments and changing societal preferences.

These transitions seem to be happening faster over time, aligning with the accelerated progress of technology.

  • Proto-Media (50,000+ years)
    Humans could only spread their message through human activity. Speech, oral tradition, and manually written text were most common mediums to pass on a message.
  • Analog and Early Digital Media (1430-2004)
    The invention of the printing press, and later the radio, television, and computer unlock powerful forms of one-way and cheap communication to the masses.
  • Connected Media (2004-current)
    The birth of Web 2.0 and social media enables participation and content creation for everyone. One tweet, blog post, or TikTok video by anyone can go viral, reaching the whole world.

Each new wave of media comes with its own pros and cons.

For example, Connected Media was a huge step forward in that it enabled everyone to be a part of the conversation. On the other hand, algorithms and the sheer amount of content to sift through has created a lot of downsides as well. To name just a few problems with media today: filter bubbles, sensationalism, clickbait, and so on.

Before we dive into what we think is the next wave of media, let’s first break down the common attributes and problems with prior waves.

Wave Zero: Proto-Media

Before the first wave of media, amplifying a message took devotion and a lifetime.

Add in the fact that even by the year 1500, only 4% of global citizens lived in cities, and you can see how hard it would be to communicate effectively with the masses during this era.

Or, to paint a more vivid picture of what proto-media was like: information could only travel as fast as the speed of a horse.

Wave 1: Analog and Early Digital Media

In this first wave, new technological advancements enabled widescale communication for the first time in history.

Newspapers, books, magazines, radios, televisions, movies, and early websites all fit within this framework, enabling the owners of these assets to broadcast their message at scale.

With large amounts of infrastructure required to print books or broadcast television news programs, it took capital or connections to gain access. For this reason, large corporations and governments were usually the gatekeepers, and ordinary citizens had limited influence.

AttributeDescription
📡 Information FlowOne-way
💰 Barriers to EntryVery high
📰 DistributionControlled by mass media companies and government
🏆 IncentiveTo cast a wide net, and to not alienate viewers or advertisers

Importantly, these mediums only allowed one-way communication—meaning that they could broadcast a message, but the general public was restricted in how they could respond (i.e. a letter to the editor, or a phone call to a radio station).

Wave 2: Connected Media

Innovations like Web 2.0 and social media changed the game.

Starting in the mid-2000s, barriers to entry began to drop, and it eventually became free and easy for anyone to broadcast their opinion online. As the internet exploded with content, sorting through it became the number one problem to solve.

For better or worse, algorithms began to feed people what they loved, so they could consume even more. The ripple effect of this was that everyone competing for eyeballs suddenly found themselves optimizing content to try and “win” the algorithm game to get virality.

AttributeDescription
📡 Information FlowTwo-way
💰 Barriers to EntryVery low
📰 DistributionControlled by technology companies and algorithms
🏆 IncentiveTo cast a narrow net, to engage and mobilize a specific audience

Viral content is often engaging and interesting, but it comes with tradeoffs. Content can be made artificially engaging by sensationalizing, using clickbait, or playing loose with the facts. It can be ultra-targeted to resonate emotionally within one particular filter bubble. It can be designed to enrage a certain group, and mobilize them towards action—even if it is extreme.

Despite the many benefits of Connected Media, we are seeing more polarization than ever before in society. Groups of people can’t relate to each other or discuss issues, because they can’t even agree on basic facts.

Perhaps most frustrating of all? Many people don’t know they are deep within their own bubble in which they are only fed information they agree with. They are unaware that other legitimate points of view exist. Everything is black and white, and grey thinking is rarer and rarer.

Wave 3: Data Media

Between 2015 and 2025, the amount of data captured, created, and replicated globally will increase by 1,600%.

For the first time ever, a significant quantity of data is becoming “open source” and available to anyone. There have been massive advancements in how to store and verify data, and even the ownership of information can now be tracked on the blockchain. Both media and the population are becoming more data literate, and they are also becoming aware of the societal drawbacks stemming from Connected Media.

As this new wave emerges, it’s worth examining some of its attributes and connecting concepts in more detail:

  • Transparency:
    Data literate users will begin to demand that data is transparent and originating from trustworthy, factual sources. Or if a source is not rock solid, users will demand that limitations of methodology or possible biases are openly revealed and discussed.
  • Verifiability and Trust:
    How do we know data shown is legitimate and bonafide? Platforms and media will increasingly want to prove to users that data has been verified, going all the way back to the original source.
  • Decentralization and Web3:
    Anyone can tap into large amounts of public data available today, which means that reporting, analysis, ideas, and insights can come from an increasingly growing set of actors. Web3 and decentralized ledgers will allow us to provide trust, attribution, accountability, and even ownership of content when necessary. This can remove the middleman, which is often large tech companies, and can allow users to monetize their content more directly.
  • Data Storytelling
    Growing data literacy, and the explosion of data storytelling is a key approach to making sense of vast amounts of data, by combining data visualization, narrative, and powerful insights.
  • Data Creator Economy:
    Democratized data and the rise of storytelling are intersecting to create a potential new ecosystem for data storytellers. This is increasingly what we are focused on at Visual Capitalist, and we encourage you to support our Kickstarter project on this (just 6 days left, as of publishing time)
  • Open-Ended Ecosystem:
    Just like open source has revolutionized the software industry, we will begin to see more and more data available broadly. Incentives may shift in some cases from keeping data proprietary, to getting it out in the open so that others can use, remix, and publish it, and attributing it back to the original source.
  • Data > Opinion:
    Data Media will have a bias towards facts over opinion. It’s less about punditry, bias, spin, and telling others what they should think, and more about allowing an increasingly data literate population to have access to the facts themselves, and to develop their own nuanced opinion on them.
  • Global Data Standards:
    As data continues to proliferate, it will be important to codify and unify it when possible. This will lead to global standards that will make communicating it even easier.

Early Pioneers of Data Media

The Data Media ecosystem is just beginning to emerge, but here are some early pioneers we like:

  • Our World in Data:
    Led by economist Max Roser, OWiD is doing an excellent job amalgamating global economic data in one place, and making it easy for others to remix and communicate those insights effectively.
  • USAFacts:
    Founded by Steve Ballmer of Microsoft fame to be a non-partisan source of U.S. government data.
  • FRED:
    This tool by the Federal Reserve Bank of St. Louis is just one example of many tools that have cropped up over the years to democratize data that were previously proprietary or hard to access. Other similar tools have been created by the IMF, World Bank, and so on.
  • FiveThirtyEight:
    FiveThirtyEight uses statistical analysis, data journalism, and predictions to cover politics, sports, and other topics in a unique way.
  • FlowingData:
    At FlowingData, data viz expert Nathan Yau explores a wide variety of data and visualization themes.
  • Data Journalists:
    There are incredible data journalists at publications like The Economist, The Washington Post, The New York Times, and Reuters that are tapping into the early beginnings of what is possible. Many of these publications also made their COVID-19 work freely available during the pandemic, which is certainly commendable.

Growth in data journalism and the emergence of these pioneers helps give you a sense of the beginnings of Data Media, but we believe they are only scratching the surface of what is possible.

What Data Media is Not

In a sense, it’s easier to define what Data Media isn’t.

Data Media is not partisan pundits arguing over each other on a newscast, and it’s not fake news, misinformation, or clickbait that is engineered to drive easy clicks. Data media is not an echo chamber that only reinforces existing biases. Because data is also less subjective, it’s less likely to be censored in the way we see today.

Data is not perfect, but it can help change the conversations we are having as a society to be more constructive and inclusive. We hope you agree!

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Technology

How Big Tech Revenue and Profit Breaks Down, by Company

How do the big tech giants make their money? This series of graphics shows a breakdown of big tech revenue, using Q2 2022 income statements.

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In the media and public discourse, companies like Alphabet, Apple, and Microsoft are often lumped together into the same “Big Tech” category. After all, they constitute the world’s largest companies by market capitalization.

And because of this, it’s easy to assume they’re in direct competition with each other, fiercely battling for a bigger piece of the “Big Tech” pie. But while there is certainly competition between the world’s tech giants, it’s a lot less drastic than you might imagine.

This is apparent when you look into their various revenue streams, and this series of graphics by Truman Du provides a revenue breakdown of Alphabet, Amazon, Apple, and Microsoft.

How Big Tech Companies Generate Revenue

So how does each big tech firm make money? Let’s explore using data from each company’s June 2022 quarterly income statements.

Alphabet

breakdown of Alphabet's revenue streams and profit

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In Q2 2022, about 72% of Alphabet’s revenue came from search advertising. This makes sense considering Google and YouTube get a lot of eyeballs. Google dominates the search market—about 90% of all internet searches are done on Google platforms.

Amazon

breakdown of amazon's revenue streams and profit

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Perhaps unsurprisingly, Amazon’s biggest revenue driver is e-commerce. However, as the graphic above shows, the costs of e-commerce are so steep, that it actually reported a net loss in Q2 2022.

As it often is, Amazon Web Services (AWS) was the company’s main profit-earner this quarter.

Apple

breakdown of Apple's revenue streams and profit

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Apple’s biggest revenue driver is consumer electronics sales, particularly from the iPhone which accounts for nearly half of overall revenue. iPhones are particularly popular in the U.S., where they make up around 50% of smartphone sales across the country.

Besides devices, services like Apple Music, Apple Pay, and Apple TV+ also generate revenue for the company. But in Q2 2022, Apple’s services branch accounted for only 24% of the company’s overall revenue.

Microsoft

breakdown of Microsoft's revenue streams and profit

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Microsoft has a fairly even split between its various revenue sources, but similarly to Amazon its biggest revenue driver is its cloud services platform, Azure.

After AWS, Azure is the second largest cloud server in the world, capturing 21% of the global cloud infrastructure market.

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Animation: The Most Popular Websites by Web Traffic (1993-2022)

This video shows the evolution of the internet, highlighting the most popular websites from 1993 until 2022.

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ranking websites by page views 1993-2022

The Most Popular Websites Since 1993

Over the last three decades, the internet has grown at a mind-bending pace.

In 1993, there were fewer than 200 websites available on the World Wide Web. Fast forward to 2022, and that figure has grown to 2 billion.

This animated graphic by James Eagle provides a historical look at the evolution of the internet, showing the most popular websites over the years from 1993 to 2022.

The 90s to Early 2000s: Dial-Up Internet

It was possible to go on the proto-internet as early as the 1970s, but the more user-centric and widely accessible version we think of today didn’t really materialize until the early 1990s using dial-up modems.

Dial-up gave users access to the web through a modem that was connected to an active telephone line. There were several different portals in the 1990s for internet use, such as Prodigy and CompuServe, but AOL quickly became the most popular.

AOL held its top spot as the most visited website for nearly a decade. By June 2000, the online portal was getting over 400 million monthly visits. For context, there were about 413 million internet users around the world at that time.

RankWebsiteMonthly Visits (May 2000)
1AOL400,891,812
2Yahoo387,573,587
3MSN354,239,803
4eBay116,101,785
5Lycos116,064,930

But when broadband internet hit the market and made dial-up obsolete, AOL lost its footing, and a new website took the top spot—Yahoo.

The Mid 2000s: Yahoo vs. Google

Founded in 1994, Yahoo started off as a web directory that was originally called “Jerry and David’s Guide to the World Wide Web.”

When the company started to pick up steam, its name changed to Yahoo, which became a backronym that stands for “Yet Another Hierarchical Officious Oracle.”

Yahoo grew fast and by the early 2000s, it became the most popular website on the internet. It held its top spot for several years—by April 2004, Yahoo was receiving 5.6 billion monthly visits.

RankWebsiteMonthly Visits (April 2004)
1Yahoo5,658,032,268
2MSN1,838,700,057
3Google1,318,276,780
4AOL905,009,947
5eBay805,474,705

But Google was close on its heels. Founded in 1998, Google started out as a simpler and more efficient search engine, and the website quickly gained traction.

Funny enough, Google was actually Yahoo’s default search engine in the early 2000s until Yahoo dropped Google so it could use its own search engine technology in 2004.

For the next few years, Google and Yahoo competed fiercely, and both names took turns at the top of the most popular websites list. Then, in the 2010s, Yahoo’s trajectory started to head south after a series of missed opportunities and unsuccessful moves.

This cemented Google’s place at the top, and the website is still the most popular website as of January 2022.

The Late 2000s, Early 2010s: Social Media Enters the Chat

While Google has held its spot at the top for nearly two decades, it’s worth highlighting the emergence of social media platforms like YouTube and Facebook.

YouTube and Facebook certainly weren’t the first social media platforms to gain traction. MySpace had a successful run back in 2007—at one point, it was the third most popular website on the World Wide Web.

RankWebsiteMonthly Visits (Jan 2007)
1Google7,349,521,929
2Yahoo5,169,762,311
3MySpace1,276,515,128
4MSN1,259,467,102
5eBay957,928,554

But YouTube and Facebook marked a new era for social media platforms, partly because of their ​​impeccable timing. Both platforms entered the scene around the same time that smartphone innovations were turning the mobile phone industry on its head. The iPhone’s design, and the introduction of the App store in 2008, made it easier than ever to access the internet via your mobile device.

As of January 2022, YouTube and Facebook are still the second and third most visited websites on the internet.

The 2020s: Google is Now Synonymous With the Internet

Google is the leading search engine by far, making up about 90% of all web, mobile, and in-app searches.

What will the most popular websites be in a few years? Will Google continue to hold the top spot? There are no signs of the internet giant slowing down anytime soon, but if history has taught us anything, it’s that things change. And no one should get too comfortable at the top.

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