By: Jordan McNea
For over a century the United States has debated what constitutes noncompetitive practices and who should be considered a monopoly. Even as the monopolized industries that first caused antitrust laws to be written have died out and newer industries have surfaced, many of the original talking points haven’t changed. As far back as the 1930’s, Supreme Court Justice Louis Brandeis argued that, “large companies would inevitably exploit their workers, convert their profits into political influence, and corrode both the market and the machinations of government.” Brandeis’ worries have materialized over these last 90 years with a combination of governmental lack of interest in holding large corporations accountable and new technologies that make it easier for incumbents to keep their positions as market leaders. The main technological advancement that I will be focusing on for this blog post is the capability for companies to create, store, and analyze increasingly large troves of customer generated data that allows established companies the opportunity to increase their network effect. This ultimately create a flywheel effect that leads to an exponential increase in profits and the ability to wipe out their competition, and in some cases, whole industries.
History of Antitrust
Antitrust laws came into existence in the 1800s after a few companies, most notable being John D. Rockefeller’s U.S. Steel and Standard Oil, became so large that they controlled entire industries. With no competition, they were able to increase prices as much as they wanted without having to worry about quality. This culminated in Congress passing the 1890 Sherman Act that outlawed price-fixing. Over the next few decades President Theodore Roosevelt would begin breaking up monopolies to promote competition and the Federal Trade Commission was created to monitor and investigate any unfair business practices. These laws remained relatively strong and effective until in the 1970s when conservatives began to argue that protecting markets for the sake of competition led to bad companies being protected and higher prices for consumers. The FTC and antitrust laws would continue to erode over the next 40 years, culminating in the 2010 Citizens United v. FEC Supreme Court case that ruled corporations can spend unlimited money on elections which has allowed corporations, as Justice Brandeis worried, to convert their profits into political influence.
A network effect is defined as a phenomenon where a product or service gains additional value as more people use it. For tech companies, network effects are imperative to build their business since the more people they attract to their platform means the better the platform becomes to its users. Creating a chicken-or-egg situation where newer companies aim to build a network effect to grow but need to attract a minimum number of users for the effects to start. This is where data-enabled network effects have made it possible for incumbents to monopolize their area of the technology space. As Andrei Hagiu and Julian Wright argued in their 2010 Harvard Business Review paper, “When Data Creates Competitive Advantaged,” data-enabled network effects have lessened the competitive advantage because newcomers can buy data to create a user experience that only incumbents once had, which allows them to bypass the cold-start problem. They’ve also argued that constant insights need to be garnered from their customers’ data for any advantage to maintain. These arguments may ring true in some cases, but for areas like social media and online retail, the combination of data and anti-competitive practices have allowed incumbents to become so large that they are able to gain such a competitive advantage that they crush any competition from gaining market share.
Currently, six social media sites that have over one billion monthly users, and Facebook owns four of them. With 2.5 billion users on Facebook, advertisers are sold access to a large range of users who willingly share their interests, friends, relationship status, likes and dislikes, which has created the greatest customer profile dataset in the history of marketing. Combining this with Facebook’s targeted marketing capabilities, advertisers can narrow in with such precision that only a handful of people who are most likely to be interested in their products or services see the ad.
Facebook’s Growth Story
A network effect drew exponential growth to the company for its first eight years in business, from one million users in 2004 to one billion by 2012, but when data-enabled network effects were supposed to begin leveling the playing field by allowing new entrants to bypass the chicken-or-egg problem and have Facebook’s innovative insights from the beginning, we’ve instead seen Facebook become the behemoth it is today. The reason for this, I believe, is that the combination of anti-competitive practices with data-enabled learning is an undefeatable combination for large enough incumbents. Once Facebook reached one billion users, they started buying competition, such as Instagram for $1 billion and WhatsApp for $20 billion, as well as stealing competitors’ innovations, examples being Snapchat’s story and filter features and adding a video option to Instagram posts after the brief rise in the Twitter owned Vine’s short form video app. Both of these have stifled competition, yet the FTC and congress have done little to stop Facebook. After announcing they were setting aside $3 billion for an expected FTC fine for the Cambridge Analytica scandal (the fine ended up being $5 billion) in an April 24, 2019 earnings call, Facebook’s market cap raised $40 billion that night in after-hours trading. To put that in perspective, the combined valuation of Reddit, Snap, and Twitter is around $53 billion. If Congress remains ineffective and the FTC unable to hold monopolies accountable, companies like Facebook will keep engaging in illegal practices and view FTC fines as slaps on the wrist and the cost of doing business.
Amazon’s Massive Growth
Amazon is another company that has used data-enabled network effects to help create a monopoly in their industry. They have used data in truly revolutionary ways, one example being the implementation of dynamic pricing where they use insights from data from various sources, such as competitor pricing and available inventory, to constantly change prices. Amazon also uses customer data to personalize recommendations in order to get customers to buy more and they run productivity statistics in their fulfillment centers to warn employees if they are being too slow. These data-driven business decisions, particularly dynamic pricing and personalized recommendations have led to a network effect that has continuously driven consumers to buy more and more from the online retail giant. As more customers shop at Amazon, the more they can lower their profit margins, which has created a flywheel effect that has squashed their competition. Over the last decade, Amazon has seen massive growth in various ways. Since 2010 they’ve increased their revenue by 20-30% year-over-year, from $34.2 billion in 2010 to $279.1 billion in 2019. In the same time period, their market capitalization has grown from $53 billion to over $1 trillion, while some of their biggest competitors (Walmart, Target, Kroger, Macy’s, and JCPenney) have seen their combined market capitalization go from $265 billion to just $421 billion. In other words, in just ten years, Amazon has gone from being worth less than a quarter of those five companies, to more than double. This meteoric rise has caused retailers to start closing shops and retail jobs are ever decreasing, with non-store retail jobs such as Amazon fulfillment center employment taking their place.
Amazon’s eCommerce Monopoly
Brick-and-mortar shops aren’t the only ones feeling the size of Amazon’s market influence hurting their profits. Online retailers, too, are subjected to Amazon’s anti-competitive practices. With 66% of consumers starting their search for new products on Amazon, and 89% of consumers saying they are more likely to buy products on Amazon than from other e-commerce sites, online retailers have little to no choice of whether to sell their products on Amazon’s marketplace. Amazon knows this and has implemented fees through high commissions, advertising buys, account management and more that totals up to about 30-35 cents for ever dollar a shopper spends on a product going back to Amazon. Other expenses, such as a $5,000 per month fee just to be part of a program that allows sellers to talk to a real person when seeking customer service, and a system where only those who pay get exposure, contribute to furthering the problem. Other e-commerce marketplaces like eBay and Walmart offer much lower fees for selling on their platforms, but because they are dwarfed in comparison to Amazon’s customer base, these lower fees do little to spur on competition. It has become nearly tantamount to U.S. Steel and Standard Oil being able to price-fix without improving quality, which lead to the original antitrust laws.
Amazon’s Political Influence
Supreme Court Justice Louis Brandeis’ worst fears about unregulated monopolies have proved incredibly prescient when it comes to Amazon. In addition to the corrosion of market dynamics, we’ve also seen Amazon exploit their employees and use their power to sway politics. Using productivity statistics from data generated by fulfillment center employees, Amazon is able to ensure their workers are constantly working, often times enticing them to forego bathroom breaks and in one case employees were forced to immediately go back to work as one of their co-workers laid on the ground, dead from a heart attack. Even though Amazon has a trillion-dollar market cap and CEO Jeff Bezos is the richest man in the world, thousands of Amazon employees rely on government assistance due to their low wages. Some in Seattle believe Amazon is holding the city hostage and has way too much influence on local politics. After city council passed a tax that would have cost Amazon a $275-per-employee head tax to create affordable housing and address the homeless problem, the local company went on the offensive and within a month of passing the tax, city council voted to repeal it. Highly paid Amazon employees (those that work at the headquarters, not in fulfillment centers) have contributed to the unaffordable housing situation for most in Seattle and this tax was meant to alleviate that. This influence was at the local level, but if the company keeps growing at its current rate, that influence is likely to be felt at the federal government pass/repeal on their behalf.
The two companies, Facebook and Amazon, took the path of developing an innovative service, which created a network effect before data really allowed for data-enabled learning. They then used insights from data to make a data-enabled network effect which lead to such a competitive advantage that they were able to monopolize their industries before competitors were able to use data-enabled network effects to challenge them. From there, Facebook and Amazon have, at varying degrees, started exploiting their workers, challenging our democracy through political influence, and controlling markets. If the laws that were created to break up the railroad and oil companies of the late-1800’s were still as powerful today, these two companies would never have gained the power they currently have. In turn, this would have resulted in their respective industries having greater competition, more innovation, and we would have a better functioning democracy because of it.
Feedvisor. “Most U.S. Consumers Would Purchase on Amazon before Other e-Commerce Sites, Feedvisor Study Finds.” GlobeNewswire News Room, “GlobeNewswire”, 19 Mar. 2019, www.globenewswire.com/news-release/2019/03/19/1757273/0/en/Most-U-S-consumers-would-purchase-on-Amazon-before-other-e-commerce-sites-Feedvisor-study-finds.html.
Galloway, Scott. “Facebook & Tyranny: No Mercy / No Malice.” No Mercy / No Malice | Professor Scott Galloway, www.profgalloway.com/facebook-tyranny.
Galloway, Scott. “LAnd of the Undead: No Mercy / No Malice.” No Mercy / No Malice | Professor Scott Galloway, http://www.profgalloway.com/land-of-the-undead.
Green, Dennis. “Data from States Shows Thousands of Amazon Employees Are on Food Stamps.” Business Insider, Business Insider, 25 Aug. 2018, www.businessinsider.com/amazon-employees-on-food-stamps-2018-8.
Greene, Jay. “Amazon Sellers Say Online Retail Giant Is Trying to Help Itself, Not Consumers.” The Washington Post, WP Company, 1 Oct. 2019, www.washingtonpost.com/technology/2019/10/01/amazon-sellers-say-online-retail-giant-is-trying-help-itself-not-consumers/?arc404=true.
Hagiu, Andrei, and Julian Wright. “When Data Creates Competitive Advantage.” Harvard Business Review, 2020.
“How Amazon Used Big Data to Rule E-Commerce.” InsideBIGDATA, 2 Dec. 2019, insidebigdata.com/2019/11/30/how-amazon-used-big-data-to-rule-e-commerce/.
Kim, Eugene. “25 Charts That Show Amazon’s Explosive Growth over the Past Decade.” Business Insider, Business Insider, 30 Dec. 2019, www.businessinsider.com/amazon-charts-show-explosive-growth-over-past-decade-2019-12#amazons-revenue-consistently-grew-at-a-20-to-30-clip-every-year-over-the-past-decade-an-unusually-high-rate-of-growth-for-a-company-of-its-size-this-year-amazon-is-expected-to-record-2791-billion-in-total-revenue-2.
Masters, Kiri. “89% Of Consumers Are More Likely To Buy Products From Amazon Than Other E-Commerce Sites: Study.” Forbes, Forbes Magazine, 20 Mar. 2019, www.forbes.com/sites/kirimasters/2019/03/20/study-89-of-consumers-are-more-likely-to-buy-products-from-amazon-than-other-e-commerce-sites/#18d8e6984af1.
Pulkkinen, Levi. “Seattle Leaders Repeal Amazon ‘Head Tax’ Passed One Month Ago.” The Guardian, Guardian News and Media, 12 June 2018, www.theguardian.com/technology/2018/jun/12/seattle-amazon-head-tax-repealed-one-month.
Schuster, Dana. “Amazon Workers ‘Forced to Go Back to Work’ after Fellow Employee Dies on Shift.” New York Post, New York Post, 21 Oct. 2019, nypost.com/2019/10/19/amazon-workers-forced-to-go-back-to-work-after-fellow-employee-dies-on-shift/.
Thompson, Derek. “America’s Monopoly Problem.” The Atlantic, Atlantic Media Company, 11 Sept. 2016, http://www.theatlantic.com/magazine/archive/2016/10/americas-monopoly-problem/497549/.
“Social Media Users – DataReportal – Global Digital Insights.” DataReportal, datareportal.com/social-media-users.
179. “Citizens United Explained.” Brennan Center for Justice, 21 Jan. 2020, www.brennancenter.org/our-work/research-reports/citizens-united-explained.
, 6 “When Data Creates Competitive Advantage.” Harvard Business Review, 2020.