Many corporate leaders consider the largest digital companies to be regular suppliers. They believe that in a competitive environment, market competition typically protects enterprise buyers from abusive pricing by suppliers.
However, when you look behind the curtain at the ownership of core operating systems, cloud computing data center networks, and digital advertising auctions, this belief shatters.
Understanding What Is Big Tech in the Modern Economy
This guide exposes industry-wide false assumptions about the impact of corporate size on market behaviour. Using five firms as case studies, this article illustrates how they all monopolise and capture digital trade in the form of private standards and private tolls or fees placed on trading companies.
These companies replace the traditional narrative about technology firms with a cold, hard operational reality that portrays them as operating or functioning as tax collectors, similar to what might have been termed tax authorities in the global commercial economy.
Defining the Big Tech Companies
Most people refer to the Big Tech companies by their overall market value as determined by their stock price and market capitalisation. While this is the typical definition, it is simplistic and overly basic. The value of a company's stock is based on market speculation, while their real structural power is gained through owning and controlling the basic building blocks of the digital world or ground on which all competitors must compete.
The term Big Tech draws a direct parallel with other historical large corporations (e.g., Big Pharma, Big Oil, Big Tobacco). Each of these companies has gained significant influence over the way that consumers make choices about products, public policy, and laws governing those products.
Nevertheless, when a company reaches significant size and value, it no longer just participates in a marketplace. It becomes the marketplace itself, deciding what competitors will be visible, determining the price of all transactions that occur through its systems, and taking a percentage of each transaction that passes through its systems.
The five companies most often referred to as the Big Tech companies in English-language media coverage are Alphabet, Amazon, Apple, Meta, and Microsoft. From mobile phone operating systems and desktop software to search engines and social networking sites, e-commerce distribution networks, the five leading technology firms provide all the primary tools used in the digital lives of consumers.
While peripheral technology companies often emerge during certain cycles of the technology market, they are usually tied directly to very specific market dynamics. For example, Nvidia is the hardware layer for artificial intelligence (AI) accelerators. Tesla combines industrial manufacturing and proprietary software for the energy market.
Netflix has a commanding presence in media streaming, while Oracle and Salesforce have both established deep roots in corporate databases and sales operations. Additionally, companies based in Asia, such as Alibaba and Tencent, have similar closed infrastructure networks.
In contrast, these five core technology firms operate under a different business model. Unlike peripheral technology firms, the core five do not operate within a single vertical, but rather across several interconnected platforms that support one another. As a result, these five companies capture the attention of users and collect corporate data and transaction revenue from multiple industries at the same time.
How the Core Five Companies Generate Revenue
To answer what is big tech and understand how a firm achieves market dominance, one must look to the flow of money. Unlike most retail or service-based business models, the core five firms have developed business models that permit them to collect revenue through a structural dependence on their products.
As a result, they have effectively positioned themselves as toll collectors for digital commerce, and this structural dependence allows these firms to charge for the privilege of using their products.
How Alphabet Makes Money
Alphabet's business model is primarily based on the revenue derived from advertising and advertising-related activities as a byproduct of global information discovery.
Alphabet generated just over $403 billion in total revenue, with nearly $132 billion in net profit. Approximately 57% of Alphabet's total revenue, or approximately $224 billion-$228 billion, was generated through search engine results and related services.
The revenue generated through YouTube advertising is estimated between $40-42 billion and Google Network (the networking of display advertisements on millions of third-party websites through AdSense and AdMob) contributes approximately $30 billion as well.
In addition to the above revenues, subscriptions, hardware devices and platform services totalled nearly $48 billion in revenues. Google Cloud has replaced Search as Google's largest growth engine, producing $59 billion in revenues and accelerating rapidly into the current year. Google Cloud's 82% increase in revenues over the previous year provided $24.8 billion to Google showing that enterprise infrastructure spending is moving to Google Cloud.
As it pertains to mobile distribution, the Google Play store has maintained a standard 20% commission rate on digital sales subsequent to legal settlements that require app developers to finance Alphabet's operational balance sheet.
How Meta Makes Money
Meta employs an advertising monetization model that's based solely upon tracking audiences and algorithmically distributing ads.
The company generated approximately $201 billion in revenue and a net profit of approximately $60 billion by monetizing an audience using Facebook, Instagram and WhatsApp. Meta, unlike traditional publishers, who pay for the creation of content, relies on user-generated content and invests in data tracking and automated ad optimization.
Within segments of digital advertising, Meta has expanded its market share from 28.2% in late 2022 to 34%.
By utilizing machine learning models to automate the targeting of ads, Meta made its advertising auction essentially mandatory for direct-to-consumer brands, thus ensuring that increased customer acquisition costs flow straight into the company's corporate treasury.
How Amazon Makes Money
Amazon's business model consists of a combination of two different kinds of business models, one from the low-margin retail side of their business and another from Amazon Web Services (AWS) which take advantage of the high-margin revenue opportunity.
Amazon reported that it had total revenue of approximately $717 billion and net income of $78 billion. While ecommerce revenues and expenses associated with logistics both contribute to Amazon's gross merchandise volume of several hundred billion dollars, retail profit margins are very thin.
Currently, the biggest source of revenue and profit for Amazon is AWS, which accounted for 28% of the total worldwide market for cloud infrastructure. Through AWS, Amazon is able to fund aggressive warehouse and logistics expansion and offer deep discounts to customers. This constant downward spiral has put tremendous pressure on the independent seller community.
Additionally, Amazon has developed an extensive advertising network within its own search results which forces independent sellers to pay for sponsored placements if they want to maintain the visibility earned through organic customer reviews.
How Apple Makes Money
Apple's primary model combines proprietary consumer electronic hardware products with very high-margin value-added digital services. Apple reported revenue of approximately $416 billion and nearly $112 billion in net income from the sale of iPhones, Macs, iPads, and wearables.
Once a consumer purchases and uses Apple products, the manufacturer will continue to generate revenue from that user through its service division which includes such things as iCloud storage, payment processing, subscription media, and App Store distribution.
The App Store serves as the only channel by which iOS developers can sell digital goods to mobile customers. As the owner of the mobile operating system, Apple establishes the terms under which software developers do business with Apple.
How Microsoft Makes Money
Enterprise software is dominated by Microsoft; they have a large share of the market due to their enterprise and cloud products. Microsoft earned $332 billion, with a profit of $134 billion, from integrating their enterprise systems under one sales organization.
Microsoft 365, Microsoft Office, Microsoft Windows, LinkedIn, and GitHub provide a steady income on subscription basis; Azure has approximately 20% of the world’s cloud infrastructure.
By bundling enterprise identity management, productivity tools, and cloud storage into one corporate enterprise agreement, Microsoft makes it challenging for independent software vendors to compete on the quality of individual products.
What Is Big Tech Dominance in the Digital Economy?
The overall level of the market influence can be demonstrated by breaking down the different sectors of the digital economy. Rather than equally dispersed among all sectors of the economy, power is concentrated within many different categories of the economy that serve as commercial communication bottlenecks.
Control of the Digital Advertising Market
Digital advertising has rapidly transitioned from an open-to-everyone market to that of a triopoly. The trio of Alphabet, Meta, and Amazon held 56% of the total advertising revenue in the USA, which was up from 53% in the prior year. Moving forward, projections state that this trio will control 58% of the total advertising dollars spent globally, excluding China.
The breakdown of Alphabet, Meta & Amazon in the domestic digital economy is that Alphabet holds approximately 29% of the domestic digital advertising market, Meta holds 19%, and Amazon holds 9%. In looking at only digital channels of advertising, research has demonstrated the triopoly holds a market share ranging from 62% – 72% of total digital marketing spending.
Based on the US total ad revenues report, digital advertising is dominated by the following:
Google (Alphabet): 29%
Facebook (Meta): 19%
Amazon: 9%
All Other Channels: 44%
The concentration of revenue among the three largest players in digital advertising has placed tremendous financial pressure on commercial brands and the publishing industry.
For example, programmatic ad auctions are often conducted using a broker called Google AdX which has historically taken around 20% as its fee simply to connect advertisers to media owners. Since these companies own both ad inventory and the tools used by advertisers to buy ads, they also have the ability to create the auction rules, establish metrics for measurement, and take margins on both sides of the transaction.
The Cloud Computing Infrastructure Triopoly
The migration of enterprise computing from private corporate server rooms to centralized facilities owned by three hyperscale providers has resulted in the following global cloud infrastructure market shares:
Amazon Web Services (AWS): 28% of global cloud infrastructure market share with an annualized run rate of nearly $169B, even with a small decrease from historical peaks.
Microsoft Azure: 20% of the global cloud infrastructure market share with a $157B annualized commercial cloud run rate.
Google Cloud: 15% of the global cloud infrastructure market with an annualized run rate of around $99B, after growing from 13% in the past quarters.
Collectively, these three hyperscale providers account for 63% of global cloud computing infrastructure. The global cloud infrastructure market share illustrates this dominance:
Amazon Web Services (AWS): 28%
Microsoft Azure: 20%
Google Cloud: 15%
All Other Independent/Regional Cloud Providers: 37%
The concentration of the cloud infrastructure market poses potential long-term operational risk for corporate IT departments.
While the adoption of cloud-based business applications has allowed companies to no longer be constrained by physical infrastructures, the associated capital investments needed to maintain and evolve the infrastructure (such as construction of state-of-the-art data centers, purchase of specialized artificial intelligence processors, etc.) has resulted in capital costs of tens of billions of dollars per year.
Such large capital expenditures make it virtually impossible for new infrastructure firms to arise that can compete with the current three firms (Microsoft, Google, Amazon) in price or performance.
Search and Mobile Operating System Control
In addition to advertising and storage services, platform power is derived from controlling the default settings on users’ interaction points (such as devices and apps) with their customers daily.
For example, Google supports the distribution of its search engine (which acts as the primary means for connecting to the internet) through default written agreements with both hardware manufacturers and web browsers. Google spends billions each year to ensure that its search engine remains the primary means of accessing the web on both Apple Safari and Android devices.
Within the realm of mobile computing, there are essentially two companies that dominate the global mobile operating system market: Apple’s iOS and Google’s Android. These two companies control all software distribution through operating systems.
In other words, every software application must go through a review process (including the use of either Apple’s or Google’s billing system). As a result, both companies make ongoing revenue streams from commissions on any apps sold through their operating systems while at the same time maintain control over which features developers can include within their applications.
Ecommerce Default Search Engines
In terms of ecommerce, Amazon serves as the default product search engine for most consumers. For independent sellers that wish to sell on Amazon, they must choose between listing their products on Amazon’s Marketplace (and therefore paying for fulfillment, storage, and advertising fees) or independently selling their products (and thus needing to generate traffic to their websites).
On average, independent sellers spend between 30%-50% of their gross sales revenue on fees/advertising related to being an Amazon Marketplace member, which places tremendous pressure on sellers to maintain their status as an Amazon Marketplace seller.
The Truth About Enterprise Migration and Lock-In
One of the major myths circulating among corporations is that switching providers (due to service pricing and/or service quality) will be easily accomplished. Unfortunately, in the enterprise sector, that assumption isn't based on actual technical realities.
Hidden Transition Costs and Dependencies
The way that enterprise technology vendors design their platforms is purposely done to create a great deal of complexity when it comes time for corporate customers to switch vendors. Once an organization's technology platform relies upon proprietary databases, proprietary identity systems, and proprietary automation solutions, switching to an alternate vendor's platform requires significant engineering effort to migrate those systems.
Data from corporate surveys indicate the major concerns corporations experience during infrastructure migration analysis:
Seventy-five percent of IT leaders have expressed concern regarding the complexity of performing a technical migration because the complexities associated with performing deep changes to an organization's system structure pose a significant risk to the continuity of their organization.
Sixty-four percent of executives fear that there will be substantial drops in productivity among their employees, as their internal IT team members will need to spend several months learning the processes and tools of the newly implemented system.
Sixty-three percent of companies face the risk of system downtime, as unintentional interruptions in service delivery can disrupt daily operations and decrease customer trust.
The economic cost associated with switching technology platforms is high, as mid-market corporations need to budget between $500,000 and $2 million for the cost of implementing a migration plan for their core cloud and/or SaaS technology stacks, while Fortune 500 corporations will frequently budget between $5 million and $15 million for a migration plan.
Furthermore, the cost of moving out of an existing vendor platform will be approximately double that of the original implementation cost. When a major corporate IT transformation attempt fails because of a failure to integrate the newly implemented systems appropriately, the average cost associated with that failure will often exceed $20 million per annum.
As such, enterprise technology vendors have designed their pricing to retain customers by ensuring that their ongoing operational costs remain at levels below the point that would provide justification for a complete migration.
Artificial Intelligence and New Moats
When people ask what is big tech doing to trap buyers, the rise in the uptake of generative artificial intelligence (AI) provides the perfect example, as it has increased enterprise vendor lock-in. Today, most software development is performed using proprietary machine learning models which are hosted within specific cloud environments.
When an engineering team designs a workflow that is built around a proprietary API, the team is then locked into that vendor's identity protocols, document storage formats and monitoring systems. In order to migrate to a different model, the team would be required to re-build the data pipeline, altering code prompts and verifying the accuracy of the output data.
Startups and mid-market companies who are building directly off of the AI stack of one hyperscaler have switching costs that are 19 to 34% higher than teams which are using open and portable code. As more publishers continue to apply the proprietary machine learning models of platform vendors into their core office tool sets, the difficulty of moving away from these models becomes essentially insurmountable for an enterprise buyer.
Regulatory Outcomes and the Antitrust Scorecard
For years government regulators have been conducting investigations into platform dominance and pursuing large lawsuits aimed at challenging monopolistic conduct. However, the legal outcomes achieved indicate that winning court cases does not necessarily lead to lower prices for businesses.
For example, Google received a landmark antitrust judgement from the federal government regarding its advertising technology, in which the courts found Google guilty of anticompetitive behaviour in publisher ad servers and ad exchanges, but they did not order the forced breakup of Google AdX.
Meta achieved a clear trial victory against the Federal Trade Commission (FTC) in the FTC's efforts to unwind the historic acquisitions of Instagram and WhatsApp by Meta, although the FTC has since filed an appeal.
Antitrust lawsuits against Amazon will continue because federal courts are now ready to listen to evidence regarding self-preferencing on its marketplace as well as punishing third-party sellers for selling lower priced products on other websites.
Understanding what is big tech helps clarify why antitrust cases demonstrate the differences between legally liable platforms and actual commercial solutions. Judges are very hesitant to establish structural remedies on the side of platform companies if they are found to be in violation of antitrust laws.
Generally, when companies enter into settlements and remedies with the courts, they receive a money judgment or pay cash fines, commit to adhere to a set of behavioral rules, or make very small modifications to contract language.
Companies that generate tens of billions of dollars annually from their business activities treat monetary penalties as just another regular business expense. In addition, monetary fines do not result in creating new, genuine competition in the market or lowering the overall cost of doing business for dependent brands.
Surveillance and Data Exposure Risks
Aside from monetary losses, utilizing centralized platforms creates the potential for both businesses and consumers to experience data security problems and government surveillance. Large centralized databases hold considerable amounts of data, creating a tempting target for both cybercriminals and law enforcement.
According to independent studies on cybersecurity, a single year will see approximately 3,300 breaches and 278 million victims as a result of breaches.
Centralizing global corporate data on a handful of cloud or advertising platforms means that if there is one configuration error, sensitive company records could be exposed to entire industrial sectors.
Requests for private customer data have grown significantly from government agencies over the last ten years. A review of public records has indicated that there has been a 770 percent increase in the number of police and other governmental agencies requesting information from corporate platform owners over the past decade.
From the end of 2014 until recently, over 3.5 million users’ personal information was provided to the U.S. government by Google, Meta, and Apple.
In the first half of a recent year, these platforms provided record data on over 282,000 users in the U.S., and European Union requests for information from platforms increased by 40% year-over-year.
This increase has resulted in an erosion of consumer trust; surveys conducted by the industry show that 59% of users will not share financial information with a platform and 20% will not upload pictures of themselves or their family and friends. Additionally, 19% of users routinely turn off location services for their mobile devices to have better personal privacy.
For-profit companies cannot wait for regulators to take action to protect their profits, employees, and corporate information. They must take steps to decrease their reliance on centralized digital platforms.
Decreasing Reliance on Centralized Platforms
Privacy is an important factor for businesses and companies are using third-party privacy-centric communication services.
Privacy-Centric Communication Services
For example, Proton provides private email, secure file storage, and encrypted calendar services that are outside of major ad tracking networks. Additionally, web browsers, such as Brave, and search engines, such as DuckDuckGo, allow employees to search for competitors and gather market research without putting internal search terms into the ad targeting systems of their employers.
Secure communication for internal use is available through apps such as Signal, which allow mobile communication without tracking of metadata and provide secure mobile communication without collecting corporate contact lists.
Open-Source Technology and Neutral Servers
Companies are not only using privacy as a means of protection, but are also investing in open-source technology that is hosted on neutral servers. Nextcloud allows companies to manage their documents internally, collaborate with team members, and store their files without exposing them to the terms of service of major cloud providers.
Secure Federated Communications
With the open Matrix protocol and Element client, companies can create their own federated messaging systems that are not affected by vendor changes in service terms or conditions.
Ownership of the Customer Relationship
Brands can maintain their ownership of their customer relationships through the use of open systems such as WordPress. This model is advantageous to brands because they do not face the risk of sudden drops in distribution that often occur on social networks.
The use of open source software also provides organizations with a significant amount of leverage when faced with increased prices from their hosting suppliers. Organizations can move the underlying software and database files to a private server without having to rewrite the custom code.
Action Plans for Business Leaders
To escape from the platform concentration, organizations need to establish a framework for operational rules relating to marketing, technical architecture and company finance. Platforms should be treated as hostile utilities that can be utilized for their reach when necessary, while protecting the organization's core business assets.
Marketing leaders should limit the percentage of their total media budget that goes to the triopoly (Facebook, Google and Amazon) to a defined fixed percentage. The remaining funds should be reinvested into first-party data capture, direct email lists and contextual advertising.
Technical leaders should require that all software is portable by using standard container systems, avoiding proprietary database features and conducting annual audits of the costs associated with exiting the cloud.
Company founders should include mobile app store commissions in their product pricing plan. Where possible, they should use web-based billing systems to maintain independence of their customer payment records.
Constructing a Resilient Business
Successful construction of a commercially and technically resilient business requires consistent execution. By planning for the cost of migration from the outset, organizations can negotiate from a position of strength and avoid being forced to accept every price increase imposed by the platform monopolies.
Rethinking How We Use Technology
Big Tech, once thought of as ordinary commercial partners and responsible for sharing the financial results of doing business with them fairly, is now nothing more than digital toll collectors. They utilize their control of the digital economy via search, advertising, cloud based business hosting, and digital app distribution to strip value from the entirety of the economy.
Relying on government filed lawsuits or antitrust fines to help bring your organization’s operational expenses down is a failing strategy for any company. Court cases can take years to make their way through the judicial system, and the remedies that were supposed to change how businesses operate or create new markets seldom change how daily commerce takes place.
The only organizations with a sustainable competitive advantage in operating within this new digital age are those businesses that have been able to adapt their use of the digital economy's big three companies (Alphabet, Meta, and Amazon) as dangerous power companies. They still utilize their networks to acquire new customers, and then as rapidly as possible, migrate that new relationship off of the big three's digital systems and onto their own systems.
The most effective way to protect their customer data, create new competitive advantages, and compete in the digital economy, is to develop and deploy an open standards based software architecture. They must never allow a single outside service provider to gain control of any aspect of their company’s access to their target markets.
How to Mitigate Financial Impact and Create a Competitive Advantage
There are several critical areas business leaders need to consider when planning their mitigation strategies against platform monopolies.
Marketing Protection from Advertising Auctions
Marketing departments have a responsibility to stop using the advertising auctions offered by the triopoly as their sole source for revenue growth. Relying solely on the advertising auction model to create future customers results in continually increasing customer acquisition costs over time. Currently, Alphabet, Meta, and Amazon are capturing 56% of total advertising expenditures in the United States, making any future reliance on only advertising auctions a fool's errand for every company that's trying to grow their business.
Companies should develop direct communication channels (such as email lists and SMS text messaging) whenever possible by redirecting any potential savings toward building these channels, as there is nothing to charge for sending a message via email or SMS text messaging on these types of lists.
Companies should also evaluate whether their retail media networks and contextual advertising on independent trade sites are working as well as they could be. It’s important that those companies use paid platform ads as a last resort for acquiring customers (when the need arises) and are not used as the primary means by which to operate their business.
Identifying Exposure to Technical Lock-In
Before companies commit workloads to a specific hyperscaler backend, technology leaders should be auditing the following four areas of operations:
Mapping the architecture of corporate data storage and determining whether the files are stored in open-source formats or the proprietary formats of the vendor, which would require high-priced charges for transferring data.
Documenting which proprietary software interfaces rely on and quantifying how many lines of code from various systems rely on proprietary APIs designed for a specific vendor’s cloud service.
Estimating the actual costs to transfer corporate data between the organization’s database and the external data center.
Assessing the skill level of IT staff in relation to the use of open-source software products (e.g. UNIX operating systems) versus relying only on certified training relating to a specific vendor’s products.
Antitrust Decisions and Operating Costs
Antitrust rulings have not resulted in the breaking up of monopoly power or the creation of real competition in the price of subscriptions. For example, a number of court decisions found that Google abused its dominant position in the ad tech marketplace; however, no judge has issued any order to the company regarding changes to their structure, such as to sell their ad exchange systems.
Similarly, the lawsuits surrounding mobile app stores have mostly resulted in minor changes to policies, such as allowing developers to set up external billing links, but retaining the core pricing structure for app stores.
Since the duopolies of operating systems and web browsers have not been affected, platform owners continue to implement new requirements and service fees while replacing outdated ones. Consequently, for software developers, participation in a platform is still a non-negotiable cost to them.
Maintaining Core Data Sovereignty with AI
Software teams need to segregate their proprietary corporate data from third-party artificial intelligence technologies by constructing an abstraction layer between any internal applications and third party AI systems.
Whenever possible, organizations should execute their training and fine-tuning processes of AI models on private server clusters or neutral cloud environments, and only transfer the fine-tuning data back to the internal application after the training has been completed.
Companies contracting with third parties for the AI model should insist upon a prohibition of using their corporate data to train any future models. Furthermore, maintaining a portable software interface will allow the engineering team to switch between different AI providers if and when their prices change. This minimizes their technical dependency on a single vendor’s cloud service.