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Non-HSR Reported

Acquisitions by

Select Technology

Platforms, 2010–2019:

An FTC Study

September 2021

NON-HSR REPORTED ACQUISITIONS BY SELECT TECHNOLOGY PLATFORMS,

2010-2019

A REPORT OF THE

FEDERAL TRADE COMMISSION

SEPTEMBER 15, 2021

Lina M Khan, Chair

Noah Joshua Phillips, Commissioner

Rohit Chopra, Commissioner

Rebecca Kelly Slaughter, Commissioner

Christine S. Wilson, Commissioner

Jen Howard

Erie Meyer

David Robbins

Holly Vedova

Samuel Levine

Marta Wosińska

Reilly Dolan

Randolph W. Tritell

Jeanne Bumpus

Sarah Mackey

Lindsay Kryzak

April Tabor

John Krebs

Chief of Staff

Chief Technologist

Executive Director

Acting Director, Bureau of Competition

Acting Director, Bureau of Consumer Protection

Director, Bureau of Economics

Acting General Counsel

Director, Office of International Affairs

Director, Office of Congressional Relations

Acting Director, Office of Policy Planning

Director, Office of Public Affairs

Secretary of the Commission

Chief Privacy Officer

Bilal Sayyed

Former Director, Office of Policy Planning*

Report Drafters and Contributors

Liad Wagman, Office of Policy Planning

Katherine Ambrogi, Office of Policy Planning

Jacob Hamburger, Bureau of Competition

Robin Moore, Acting Chief of Staff, Bureau of Consumer Protection

William Adkinson, Office of Policy Planning

Elizabeth Gillen, Bureau of Competition

Elizabeth Jex, Office of Policy Planning

Jaime Taronji, Office of Policy Planning

Casey Triggs, Office of Policy Planning (detail from Consumer Financial Protection Bureau)

Ruth Yodaiken, Office of Policy Planning

Jin-Hyuk Kim, Office of Policy Planning (contractor)

Adrian Cabrera, Office of Policy Planning (intern)

Henry Nolan, Office of Policy Planning (intern)

*Mr. Sayyed was director during parts of the report period.

Non-HSR Reported Acquisitions by Select Technology Platforms, 2010-2019:

An FTC Study

1. Introduction

In February 2020, the Federal Trade Commission (“FTC” or “Commission”) issued

Special Orders to five large technology firms that have made numerous acquisitions in recent

years, requiring them to provide information about prior acquisitions not reported to the federal

U.S. antitrust agencies under the Hart-Scott-Rodino (“HSR”) Act.1 The orders required Alphabet

Inc. (“Alphabet,” including Google), Amazon.com, Inc. (“Amazon”), Apple Inc. (“Apple”),

Facebook, Inc. (“Facebook”), and Microsoft Corp. (“Microsoft”) to provide information and

documents on the terms, scope, structure, and purpose of transactions that each company

consummated between January 1, 2010 and December 31, 2019 for which the company did not

file an HSR notification form. The Commission issued these orders under Section 6(b) of the

FTC Act, which authorizes the Commission to conduct wide-ranging studies that do not have a

specific law enforcement purpose.

The orders were designed to help the FTC deepen its understanding of large technology

firms’ acquisition activity including examining the trends in acquisitions and the structure of

deals. Various Commissioners have stated that mergers and acquisitions in the technology

industry are an area of significant importance to the agency.2 At the FTC’s 2018-2019 Hearings

on Competition and Consumer Protection in the 21st Century, participants also noted that major

technology firms made hundreds of acquisitions, with many occurring in the past five to ten

years.3 In addition to the Commission, the Antitrust Division of the U.S. Department of Justice4

Press Release, FTC, FTC to Examine Past Acquisitions by Large Technology Companies (Feb. 11, 2020),

https://www.ftc.gov/news-events/press-releases/2020/02/ftc-examine-past-acquisitions-large-technology-companies.

See, e.g., Rebecca Kelly Slaughter, Comm’r, Fed. Trade Comm’n, Keynote at 6th Bill Kovacic Antitrust Salon:

Where is Antitrust Policy Going? 2 (Sept. 24, 2018),

https://www.ftc.gov/system/files/documents/public_statements/1412806/slaughter__closing_remarks_for_6th_annual_bill_kovacic_antitrust_salon_9-24-18.pdf (“We are seeing more and more

mergers and conduct matters with technology-related issues such as data collection, intellectual property, and

network effects.”); Rohit Chopra, Comm’r, Fed. Trade Comm’n, Remarks at Silicon Flatirons Conference 2 (Feb.

10, 2019),

https://www.ftc.gov/system/files/documents/public_statements/1453633/remarks_of_commissioner_chopra_at_silic

on_flatirons.pdf (“[W]e need to ask ourselves whether certain business practices and merger activity are really

promoting innovation or simply allowing corporate royalty to hold on to their reign.”); Noah Joshua Phillips,

Comm’r, Opening Address at Chatham House Competition Policy 2020 Conference 2 (Nov. 10, 2020),

https://www.ftc.gov/system/files/documents/public_statements/1582986/phillips_remarks_chatham_house_11-1020.pdf (“Enforcers and policymakers should focus more on issues characteristic of technology markets: acquisitions

of nascent competitors, two-sided markets, zero price markets, and so forth.”).

See, e.g., Sally Hubbard, Remarks at FTC Hearings of Competition & Consumer Protection in the 21st Century,

Session #3, Tr. at 265 (Oct. 17, 2018),

https://www.ftc.gov/system/files/documents/public_events/1413712/ftc_hearings_session_3_transcript_day_3_1017-18fullupdated.pdf.

See e.g., Press Release, Dep’t of Justice, Justice Department Reviewing the Practices of Market-Leading Online

Platforms (July 23, 2019), https://www.justice.gov/opa/pr/justice-department-reviewing-practices-market-leadingonline-platforms.

and key Congressional leadership5 have all expressed concerns regarding the number of

acquisitions by major technology companies, as have other competition agencies around the

world.6

Following the issuance of the Special Orders, FTC staff collected and analyzed data and

documents from the respondents to learn more about the relevant transactions. Staff also crossreferenced the material obtained through the Special Orders with publicly available data sources

to analyze recipients’ transactions. This report publishes the results of that analysis on an

aggregated, and therefore anonymized, basis. To protect the confidentiality of the information

submitted to the Commission, this report does not publish any confidential information from the

recipients of the Special Orders.7

This report adds to existing empirical research on transactions by technology companies

by analyzing a number of trends and patterns identified in the data. In particular, the report

quantifies and categorizes the pace, the size distribution of transactions in dollar terms, the types

See, e.g., STAFF OF H. COMM. ON THE JUDICIARY, 116TH CONG., INVESTIGATION OF COMPETITION OF DIGITAL

MARKETS: MAJORITY STAFF REPORT AND RECOMMENDATIONS 44 (2020),

https://judiciary.house.gov/uploadedfiles/competition_in_digital_markets.pdf?utm_campaign=4493-519 (“Leading

economists and antitrust experts have expressed concern that serial acquisitions of nascent competitors by large

technology firms have stifled competition and innovation.”); KEN BUCK, ET AL., H. COMM. ON THE JUDICIARY, 116TH

CONG., THE THIRD WAY: ANTITRUST ENFORCEMENT IN BIG TECH 9 (2020),

https://buck.house.gov/sites/buck.house.gov/files/wysiwyg_uploaded/Buck%20Report.pdf.

Other competition agencies around the world have also expressed concerns. For example, the European

Commission has proposed the Digital Markets Act, containing a set of rules for “gatekeepers” and consequences for

non-compliance. Eur. Comm’n, The Digital Markets Act: ensuring fair and open digital markets,

https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital-age/digital-markets-act-ensuring-fair-andopen-digital-markets_en#new-rules-in-a-nutshell (last visited Sept. 2, 2021). Germany’s Commission on

Competition Law 4.0 proposed “monitoring and assessment of cases involving the early acquisition of innovative

start-ups” and evaluation of the current system of ex-ante merger control. FED. MINISTRY FOR ECON. AFFAIRS &

ENERGY, A NEW COMPETITION FRAMEWORK FOR THE DIGITAL ECONOMY: REPORT BY THE COMMISSION

‘COMPETITION LAW 4.0’ 7 (2019), https://www.bmwi.de/Redaktion/EN/Publikationen/Wirtschaft/a-newcompetition-framework-for-the-digital-economy.pdf?__blob=publicationFile&v=3. See also UNLOCKING DIGITAL

COMPETITION: REPORT OF THE DIGITAL COMPETITION EXPERT PANEL 12, 95 (2019),

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/785547/unlocking

_digital_competition_furman_review_web.pdf (last visited Sept. 2, 2021) (UK’s Digital Expert Panel

recommending that identified digital companies ought to make the U.K. Competition and Markets Authority aware

of every intended acquisition to assist it with monitoring and selecting digital cases for investigation.); KOREAN

FAIR TRADE COMMISSION (KFTC), CHAIRPERSON'S MESSAGE TO EXPLAIN THE PURPOSE AND DIRECTION OF THE “ACT

ON FAIR INTERMEDIATE TRANSACTIONS ON ONLINE PLATFORMS,” PROPOSED BY THE KFTC 1, (Sept. 28, 2020),

https://ftc.go.kr/solution/skin/doc.html?fn=a96717a996e790c90b01a7bc4c1f77d946be46d29989d2d5c23b7f464793

dfba&rs=/fileupload/data/result/BBSMSTR_000000002401/, (last visited Sept. 8, 2021) (stating that

“there are anti-competitive concerns that monopolistic platforms are preventing new entrants from entering the

market while removing potential competitors by acquiring them.”); AUSTRALIAN COMPETITION & CONSUMER

COMMISSION, DIGITAL ADVERTISING SERVICES INQUIRY: INTERIM REPORT 88, Dec. 2020,

https://files.lbr.cloud/public/2021-01/Digital%20Advertising%20Services%20Inquiry%20%20Interim%20report.pdf?qSKQBUcxWvgg8v7Xr8McY0FwxpXL1Pgw=, (last visited Sept. 8, 2021) (identifying

a “pattern of consolidation” in advertising technology services); COMPETITION COMMISSION SOUTH AFRICA, ONLINE

INTERMEDIATION PLATFORMS MARKET INQUIRY, TERMS OF REFERENCE, DRAFT FOR PUBLIC COMMENT 1, (Feb. 19,

2021), http://www.compcom.co.za/wp-content/uploads/2021/02/OIPMI-Draft-ToR-19-02-2021.pdf (last visited

Sept. 8, 2021) (identifying a possible “deliberate strategy to… acquire competitive threats”).

15 U.S.C. § 46(f).

of transactions, and the number of non-HSR reportable transactions collectively by the five

respondents. As far as the acquired companies, the report further examines the acquisition terms

regarding their debts or liabilities as of the time of their acquisition, any deferred or contingent

compensation offered to key employees and founders as part of the acquisition, the age of the

acquired companies as of the time of the consummation of their acquisition, and the number of

their full-time non-sales employees that went on to work for the acquiring respondent after the

acquisition. This study intends to provide background and findings from this data set, not to

provide a basis for evidence in an adjudicatory proceeding.

The report provides certain data on transactions that exceed the HSR Size of Transaction

(SOT) threshold. To be clear, however, transactions exceeding the SOT threshold may not have

been notified because the Size of Person (SOP) test was not met or one of the statutory or

regulatory exemptions applied. In general, unless an exemption applies, premerger notification is

required if the transaction meets three tests: (1) the Commerce Test (which is routinely met), (2)

the Size of Transaction Test, and (3) the Size of Person Test. To meet SOT, the transaction

value, as calculated in accordance with the HSR rules, must be over $50 million (as adjusted,

currently $92 million). There is no filing obligation for transactions with a value below SOT. If

the value of the transaction is more than $50 million (as adjusted) but $200 million (as adjusted,

currently $368 million) or less, SOP, which is a set of requirements about the value of the

parties’ revenues and/or assets, must also be met to make the transaction reportable.

Even if a transaction meets SOT and SOP (if necessary), it need not be reported if it is

exempt under one of the statutory or regulatory exemptions. For example, an acquisition of a

foreign issuer or foreign assets may not need to be reported if the buyer is not acquiring control

or if the issuer or assets have “insufficient nexus” to the United States, as determined on the basis

of the revenues generated by the issuer or by the assets from sales in or into the United States.

While this report does not make recommendations or conclusions regarding the HSR

thresholds, it does analyze the nonreportable transaction data of respondents and releases trends

and patterns relating to these transactions. The study intends to inform ongoing discussions

among policymakers, academics, and other stakeholders.

2. Overview

a. Respondents

The Special Order respondents—Alphabet/Google, Amazon, Apple, Facebook, and

Microsoft—are five of the largest public U.S. companies by market capitalization.8 These firms

are among the most significant technology companies operating in the world and publicly

available information indicates each firm has engaged in a high volume of acquisitions.

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

i. Alphabet/Google

Alphabet is a multinational internet technology company headquartered in Mountain

View, California and founded in 1998.9 At publication of this report, Alphabet was the thirdlargest U.S. company by market capitalization.10 Alphabet’s core business lines are organized

under its Google subsidiary, which offers a variety of services and products that enable users to

obtain access to websites, photos, videos, and other sources of information across the internet. It

primarily generates revenues from these businesses through the sale of online advertising.11

Some of these services and products include:



Search, an internet search engine;

YouTube, a video sharing service;

Google Drive, a cloud storage service;

Google Maps, a location information application;

Gmail, an email service;

Android, a mobile operating system; and

Chrome, an internet browser.

Google also operates enterprise-ready cloud services, which includes Google Cloud

Platform and Google Workspace. It generates revenues from these services primarily through

fees received from customers.12

Alphabet reported revenues of $182.5 billion in 2020, over $181 billion of which came

from its Google segments. Google sales of advertising accounted for approximately 80% of

Alphabet’s total revenues.13 It reported revenues of about $29.3 billion in 2010, with

approximately two-thirds coming from Google website advertising revenue and 30% coming

from Google Network members’ website advertising revenue.14 At the end of 2020, Alphabet

employed over 135,000 individuals, up from nearly 24,400 in 2010.15

ii. Amazon

Amazon is a multinational e-commerce company headquartered in Seattle, Washington

and was founded in 1994. At publication of this report, Amazon was the fourth-largest U.S.

company by market capitalization.16 A key component of Amazon’s business is its online retail

platform for goods and services, selling private-label products and products Amazon has

In 2015, Google restructured itself and Alphabet became the successor parent organization. Before then, Google

was the parent organization. Alphabet, Annual Report (Form 10-K) 25-26 (Feb. 2, 2021).

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

Alphabet, Annual Report (Form 10-K) 6, 33 (Feb. 2, 2021).

Id. at 6-7.

Id. at 32-33.

Alphabet, Annual Report (Form 10-K) 53 (Feb. 11, 2011).

Alphabet, Annual Report (Form 10-K) 9 (Feb. 2, 2021); Alphabet, Annual Report (Form 10-K) 8 (Feb. 11, 2011).

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

purchased for retail sale, as well as third-party products for which Amazon offers an e-commerce

platform. As part of its online platform business, it offers Amazon Prime, a fee-based

membership program that provides users with services such as shipping, streaming movies and

TV shows, music, and books. Amazon’s primary source of revenue is the sale of a wide range of

products and services to customers.17 In 2017, Amazon bought Whole Foods, a specialty grocery

with locations throughout the country. The company also sells its own electronic devices and

produces media content.18 Amazon has also opened physical retail stores, including grocery

stores under the banner Amazon Fresh.

Amazon also operates Amazon Web Services (AWS), which offers a suite of enterprise

cloud computing services, “including comput[ing], storage, database, analytics, and machine

learning, and other services.”19 In 2020, Amazon reported net sales of $386 billion. Net sales

from its AWS business accounted for $45.4 billion, while all other segments accounted for

$340.7 billion.20 In 2010, Amazon’s net sales were $34.2 billion; it did not report net sales

figures for AWS separately in 2010.21 At the end of 2020, Amazon had approximately 1,298,000

full-time and part-time employees, not including independent contractors or temporary

personnel.22 At the end of 2010, Amazon had approximately 33,700 full-time and part-time

employees.23

iii. Apple

Apple is a multinational consumer electronics company headquartered in Cupertino,

California and founded in 1977. At publication of this report, Apple was the largest U.S.

company by market capitalization.24 The company “designs, manufactures and markets

smartphones, personal computers, tablets, wearables and accessories, and sells a variety of

related services.”25 Apple sells its products through its retail and online stores, direct sales force,

and indirect distribution channels. These products include:



The iPhone line of smartphones;

The Mac line of personal computers;

The iPad line of multi-purpose tablets; and

A Wearables, Home, and Accessories group of products, which includes AirPods

wireless headphones and Apple Watch.

Apple also offers a variety of consumer-facing services, including:

Amazon, Annual Report (Form 10-K) 19, 25 (Feb. 2, 2021).

Id. at 3.

Id.

Id. at 25.

Amazon, Annual Report (Form 10-K) 18 (Jan. 27, 2011).

Amazon, Annual Report (Form 10-K) 4 (Feb. 2, 2021).

Amazon, Annual Report (Form 10-K) 4 (Jan. 27, 2011).

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

Apple, Annual Report (Form 10-K) 1 (Oct. 29, 2020).



Various platforms that allow customers to discover and download applications and digital

content, such as the App Store;

Digital content streaming services, such as Apple Music and Apple TV+;

Cloud computing services; and

Payment services.

The company reported total net sales of $274.5 billion in 2020, about half of which is

attributable to iPhone net sales.26 In 2010, Apple had $65.2 billion in total net sales, of which

$25.2 billion is attributable to the iPhone.27 In 2020, Apple generated $53.8 billion in net sales

from its services category, a 16% increase over 2019 net sales ($46.3 billion), which also

represented a 16% increase over 2018 net sales ($39.8 billion).28 The company had

approximately 147,000 full-time equivalent employees, up from the 46,600 full-time equivalent

employees and 2,800 full-time equivalent temporary employees and contractors it had in 2010.29

iv. Facebook

Facebook is a multinational social media company headquartered in Menlo Park,

California and founded in 2004. At publication of this report, Facebook was the fifth-largest U.S.

company by market capitalization.30 According to Facebook, the company builds social media

products that operate on mobile devices, personal computers, virtual reality headsets, and inhome devices.31 These social media products enable individuals to share information about

themselves and their activities (including pictures and videos), connect with other individuals,

and communicate news and other information. Substantially all of the company’s revenues

derive from advertising placement sales.32 Facebook’s products and services include:



Facebook, a personal social networking service;

Instagram, a photo-based personal social networking service;

Messenger, a mobile messaging service;

WhatsApp, a mobile messaging service; and

Facebook Reality Labs, offering augmented and virtual reality products.33

As of December 31, 2020, Facebook had 2.8 billion monthly active users (“MAUs”),

compared to 845 million MAUs on December 31, 2011.34

Id. at 21.

Apple, Annual Report (Form 10-K) 33 (Oct. 27, 2010).

Apple, Annual Report (Form 10-K) 21 (Oct. 29, 2020).

Apple, Annual Report (Form 10-K) 4 (Oct. 29, 2020); Apple, Annual Report (Form 10-K) 10 (Oct. 27, 2010).

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

Facebook, Annual Report (Form 10-K) 7 (Jan. 27, 2021).

Id.

Facebook, Annual Report (Form 10-K) 52 (Jan. 27, 2021); Facebook, Annual Report (Form 10-K) 5 (Feb. 1,

2013).

Facebook had about $86 billion in revenue in 2020, up from about $2 billion in 2010.35 It

employed 58,604 people globally as of December 31, 2020, compared to the 2,661 people it

employed full-time as of June 30, 2011.36

v. Microsoft

Microsoft is a multinational software company headquartered in Redmond, Washington

and founded in 1975. At publication of this report, Microsoft was the second-largest U.S.

company by market capitalization.37 The company develops and supports “software, services,

devices, and solutions,” and offers “an array of services, including cloud-based solutions that

provide customers with software, services, platforms, and content.”38 Microsoft generates

“revenue by offering a wide range of cloud-based and other services to people and businesses;

licensing and supporting an array of software products; designing, manufacturing, and selling

devices; and delivering relevant online advertising to a global audience.”39 Some of the key

products and services it offers include:



Office, a suite of productivity applications;

LinkedIn, a social networking service for professionals;

Dynamics, a line of business applications;

Cloud computing services, including Azure;

Windows, a personal computing operating system;

Personal computing devices, including Surface;

Xbox, a video game platform; and

Bing, a search engine.40

Microsoft reported $168 billion in revenue in 2021, compared to $62.5 billion in revenue

in 2010.41 As of June 30, 2021, it had approximately 181,000 full-time employees, including

103,000 in the United States.42 As of June 30, 2010, it had approximately 89,000 full-time

employees, including 54,000 in the United States.43

Facebook, Annual Report (Form 10-K) 50 (Jan. 27, 2021); Facebook, Annual Report (Form 10-K) 34 (Feb. 1,

2013).

Facebook, Annual Report (Form 10-K) 10 (Jan. 27, 2021); Facebook, Quarterly Report (Form 10-Q) 48 (July 31,

2012). Facebook completed its initial public offering in May 2012, so earlier headcount reports are not publicly

available. Facebook, Quarterly Report (Form 10-Q) 8 (July 31, 2012).

U.S. Companies by Market Capitalization, https://companiesmarketcap.com/usa/largest-companies-in-the-usa-bymarket-cap/ (last visited Sept. 2, 2021).

Microsoft, Annual Report (Form 10-K) 3 (July 29, 2021).

Id. at 39.

Id. at 10-15.

Microsoft, Annual Report (Form 10-K) 34 (July 29, 2021); Microsoft, Annual Report (Form 10-K) 21 (July 30,

2010).

Microsoft, Annual Report (Form 10-K) 8 (July 29, 2021).

Microsoft, Annual Report (Form 10-K) 14 (July 30, 2010).

b. Special Orders

The Special Orders required each respondent to identify transactions not reported to the

FTC and the U.S. Department of Justice under the HSR Act, and to provide information similar

to that requested on the HSR notification and report form.44 The Orders also required companies

to provide other data and documents on their corporate acquisitions, including information on

non-compete provisions and deferred or contingent compensation. FTC staff met with the

respondents regularly throughout the data collection and provision period and reviewed

responses as they arrived on a rolling basis. Staff then processed and analyzed the material from

those responses. This report reflects components of that analysis and identifies several patterns,

on an aggregated basis, in the parties’ combined transaction history.

3. Analysis

The below section describes the aggregate analysis of data produced, revealing a number

of patterns regarding the total number of transactions, transaction types, and sizes. It also

quantifies the prevalence of a number of common practices found in the merger agreements,

including the use of non-compete provisions and deferred or contingent compensation for the

acquired firms’ founders and key employees. The analysis also revealed a significant amount of

information about each acquired firm, including its country of origin, debts and liabilities, the

number of employees joining the acquirer after the transaction, and its age. Finally, staff

categorized the transactions by sector to show the relationship between the number of

transactions made and industry developments.

Sections 6(f) and 21(d)(1)(B) of the FTC Act prohibit the Commission from disclosing

trade secrets or commercial or financial information that is privileged or confidential. Because of

this statutory prohibition, the Commission does not have discretion to disclose this type of

information.45 As a result, this report publishes data from all five respondents on an aggregated

basis. We share below the information that we can report publicly within these confidentiality

limitations.

a. Methodology

As part of its review, staff collected information from the respondents on several key data

points requested in the Special Order. This included, but was not limited to, information on:



The acquired entities (e.g., whether a target entity had any debts or liabilities at the time

of its acquisition);

The acquirers;

Parameters specific to each acquisition, such as the consummation date of the acquisition,

whether the merger agreements included non-compete clauses, whether the merger

Order to File a Special Report, FTC Matter No. P201201 (Feb. 10, 2020) [hereinafter Special Order],

https://www.ftc.gov/system/files/documents/reports/6b-orders-file-special-reports-technology-platformcompanies/6b_platform_study_sample_order.pdf.

15 U.S.C. § 46(f), 15 U.S.C. § 57b-2(d)(1)(B).



agreement stipulated deferred or contingent compensation for the target entity’s

employees and/or shareholders, as well as the type of the acquisition:

o Voting Security (Control)

o Voting Security (Minority)

o Asset

o Patent Acquisition

o Hiring Event

o Non-Corporate Interest (Control)

o Non-Corporate Interest (Minority)

o License

o Economic Interest; and

Post-acquisition outcomes (e.g., the number of employees from the target entity who

joined the acquirer after the acquisition).

After collecting the responsive material, staff processed and analyzed the data at both the

individual respondent level and collectively for the five respondents.46 As part of this analysis,

staff grouped acquisitions along various aspects of the transactions, including by:



respondent;

acquisition type;

transaction size;

calendar year;

whether the acquired firm was a domestic or foreign entity; and

nesting these various aspects (e.g., all Voting Security (Control) acquisitions within a

certain transaction size range, the number of employees who joined the acquiring firm

after an acquisition within a certain transaction size range) and determining the

correlation between certain aspects (e.g., were larger transactions more likely to include

non-compete clauses in their merger agreements and/or stipulate deferred or contingent

compensation for the founders and key employees of the acquired entities).

As part of the analysis, staff also collected additional data on the acquisitions from four

proprietary databases (PitchBook, S&P Global Market Intelligence 451 Research, Crunchbase,

and Refinitiv). Staff used the information collected to identify and advise respondents of any

potentially missing transactions to ensure the completeness of the information received. Staff

also used the information to determine the age of each acquired entity as of the time of its

acquisition, and to approximate an industry categorization of the target entities.47 Combined, this

additional information verified the universe of transactions reported as well as provided a basis

for additional groupings of transactions (e.g., by acquired entity age, by approximate industry

category) for analysis.

The percentages in this report’s figures may not necessarily add up to 100% due to decimal point rounding.

While some of this information would typically be available using HSR filings, none of the responsive

transactions were filed under HSR.

b. Transaction Types

The five respondents reported 819 total non-HSR reportable transactions over the 10-year period

for an average of approximately 164 transactions per respondent.48 Each transaction was

categorized according to a primary type: Voting Security (Control), Voting Security (Minority),

Asset, Patent Acquisition, Hiring Event, Non-Corporate Interest (Control), Non-Corporate

Interest (Minority), License, and Economic Interest.49 Of the 819 transactions, the largest

category was Voting Security (Control) at 382 acquisitions, followed by 150 Asset acquisitions,

101 Hiring Events, and 91 Patent Acquisitions. In the charts that follow, the standard deviations

provide a measure of the amount of variation or dispersion across respondents. A lower standard

deviation indicates that the values from the five respondents tend to be close to the respective

average, while a higher standard deviation indicates that the individual values are spread out over

a wider range.

Figure 1: Transaction Types

Type of Transaction

Total

Voting Security (Control)

Asset

Hiring Events

Patent Acquisitions

Voting Security (Minority)

382

150

101

Average Per

Respondent

76.4

20.2

18.2

Standard

Deviation

32.7

9.5

16.9

16.2

9.7

The 819 transactions omit approximately 50 additional smaller transactions below $1 million, 160 financial

investments, and Patent Acquisitions below $2.5 million.

As defined within the Special Order, see supra note 44. Voting securities (control) is defined under the meaning

of 16 C.F.R. § 801.1 et seq., which described that voting securities means any securities which at present or upon

conversion entitle the owner or holder thereof to vote for the election of directors of the issuer, or of an entity

included within the same person as the issuer. Control is described as either holding 50 percent or more of the

outstanding voting securities of the issuer or, in the case of an unincorporated entity, having the right to 50 percent

or more of the profits of the entity, or having the right in the event of a dissolution to 50 percent or more of the

assets of the entity. An alternative definition of control involves having the contractual power to designate 50

percent or more of the directors of a for-profit or not-for-profit corporation, or 50 percent or more of the trustees in

the case of trusts that are irrevocable and/or in which the settlor does not retain a reversionary interest. Voting

Securities (Minority) are Voting Securities that are not control Voting Securities. Asset acquisition is holding, in the

aggregate, any of the assets of another Entity that, at the time of acquisition, represented any of: (1) 10% or more of

the assets of the acquired Entity, or of a division, subsidiary, office or product, research or development group; or

(2) assets sufficient to constitute a business or operating unit. Patent acquisition is the purchase of one or more

patents that is not otherwise defined as another category of acquisition. Hiring Event means any instances where,

within a one-year period, the company hired 25 percent or more non-sales employees of an Entity, division, office,

or subsidiary of an Entity, or product, research or development group of an Entity. Non-Corporate Interest means an

interest in a Non-Corporate Entity, with control and minority having the same meaning as under Voting Securities.

License is obtaining exclusive agreements to intangible property that is not an acquisition. Economic Interest means

the right to receive profits or assets upon their distribution, either directly or indirectly, or upon dissolution of the

Issuer or Entity; or the right to receive the gains from the appreciation in the value of any interest, including Voting

Security or interest, held in, or of, the Entity; or the responsibility for the losses associated with the change in value

of the Entity or value of any interest, including Voting Security or interest, in the Entity.

Non-Corporate Interest

(Control)

Non-Corporate Interest

(Minority)

License

Economic Interest

Total # of Transactions

5.4

2.8

2.4

3.2

819

1.6

0.6

163.8

3.2

1.2

70.2

Voting Security (Control) acquisitions, Asset acquisitions, and Hiring Events were the three most

common categories, comprising a combined 77.2% of the 819 total transactions.

Figure 2: Transaction Types

NCI,

Minority

License

NCI, Control

Economic Interest

<1%

Voting Security,

Minority

Voting Security,

Control

47%

Patent Acquisitions

11%

Hiring Events

12%

Asset

18%

Excluding Hiring Events and Patent Acquisitions (which staff considered separately), for a

remaining total of 627 transactions, Voting Security (Control) and Asset acquisitions comprised

85% of the transactions, or 89% when including Non-Corporate Interest (Control) acquisitions.

c. Transactions by Year

Excluding Hiring Events and Patent Acquisitions, the total number of transactions per calendar

year across the five respondents ranged from 43 (in 2012) to 79 (in 2014), with corresponding

annual averages per respondent ranging from 8.6 (in 2012) to 15.8 (in 2014).

Figure 3: Number of Transactions Per Year (Total and Average Per Respondent)

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Total (5

Respondents)

Average Per

Respondent

10.4

10.6

8.6

12.6

15.8

14.8

12.6

13.2

12.8

Standard

Deviation

7.9

9.9

3.6

5.5

8.1

7.3

4.1

4.7

5.5

5.8

The number of transactions per calendar year per individual respondent ranged from 2 to 31,

with the average annual number of transactions across respondents peaking in 2014 and

remaining relatively higher in 2015-2019 than in 2010-2013.

Figure 4: Total Number of Transactions Per Year

2010

2011

2012

2013

2014

2015

Total (5 Respondents)

2016

2017

2018

2019

d. Transaction Values

Focusing on transactions (excluding Hiring Events and Patent Acquisitions) above $1 million,

the following table reports information on the number of transactions in each transaction range,

where the HSR Size of Transaction (SOT) threshold is determined for each transaction

individually based on its consummation date (the HSR SOT threshold has increased annually

over the 2010-2019 time period).

Figure 5: Transactions by Transaction Range

Transaction Range

≥ $1 Million & < $5 Million

≥ $5 Million & < $10 Million

≥ $10 Million & < $25 Million

≥ $25 Million & < $50 Million

≥ $50 Million & < $HSR SOT

Threshold

≥ $HSR SOT Threshold

All Transactions

Total

Average

145

162

18.6

32.4

16.8

7.6

616

18.8

123.2

Standard

Deviation

13.9

8.3

8.0

8.4

4.8

10.8

48.4

Cumulative

23.54%

15.10%

26.30%

13.64%

23.54%

38.64%

64.94%

78.57%

6.17%

15.26%

84.74%

100.00%

Transactions in the $1-5 million range were more common than in the $5-10 million range, and

transactions in the $10-25 million range were more common than in the $25-50 million range. Of

all transactions (above $1 million, excluding Hiring Events and Patent Acquisitions), 65% were

between $1 million and $25 million.

Figure 6: Total Percent of Transactions by Transaction Range

100%

90%

80%

70%

≥ $HSR SoT Threshold

60%

≥ $50 Million & < $HSR SoT Threshold

≥ $25 Million & < $50 Million

162

50%

≥ $10 Million & < $25 Million

≥ $5 Million & < $10 Million

40%

≥ $1 Million & < $5 Million

30%

20%

145

10%

The number of acquisitions in each transaction range fluctuated during 2010-2019, with

somewhat pronounced increases in the number of transactions in the $10-$25 million range and

the $50 million to the HSR SOT threshold range in later years relative to earlier years.

Figure 7: Number of Transactions Per Year by Transaction Size

Range

Number of Transactions

≥ $HSR SoT Threshold

≥ $50 Million & < $HSR SoT Threshold

≥ $25 Million & < $50 Million

≥ $10 Million & < $25 Million

≥ $5 Million & < $10 Million

≥ $1 Million & < $5 Million

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Asset and Control transactions (including Voting Security Control and Non-Corporate Interest

Control transactions) were the most common in each transaction range. For transactions

exceeding $5 million, the majority were Control transactions. Moreover, the share of Control

transactions consistently increases in the range of the transactions, comprising 90.4% of

transactions in the highest range (transaction sizes above the HSR SOT threshold). The Pearson

correlation50 between the logarithm of acquisition values and transactions being of Control

(either in Voting Security or Non-Corporate Interest), on a range of -1 to 1, with positive values

indicating positive correlation and vice versa, is 0.38 (with statistical significance at < 1%); that

is, transactions with higher purchase amounts are more likely to be Control acquisitions.

Figure 8: Transaction Type by Range

≥ $5 Million & < $10 Million

31.2%

61.3%

≥ $10 Million & < $25 Million

20.4%

71.0%

0.6%

2.5%

5.6%

≥ $25 Million & < $50 Million

21.4%

72.6%

1.2%

2.4%

≥ $50 Million & < $HSR SOT Threshold

5.3%

84.2%

2.6%

5.3%

2.6%

≥ $HSR SOT Threshold

5.3%

90.4%

2.1%

Voting Security

Minority

37.9%

Non-Corporate

Interest Minority

39.3%

License

Control Transactions

(Voting Security + NCI)

≥ $1 Million & < $5 Million

Transaction Range

Economic Interest

Asset

Transaction Type

5.5%

1.4%

15.9%

7.5%

Correlation measures a statistical relationship between two variables, where 1 indicates the strongest movement in

the same direction, -1 in the opposite directions, and 0 being no relation. The Pearson (point-biserial) correlation is a

special case of the correlation measure in which one variable is continuous (log of transaction size) and the other

variable is binary (0 or 1 indicator variable – in this case, of Control-type transactions).

e. Transactions, Domestic/Foreign

The majority of transactions in each transaction range (excluding Hiring Events and Patent

Acquisitions) were domestic.

Figure 9: Domestic and Foreign Transactions by Range

Transactions

≥ $1 Million & < $5 Million

≥ $5 Million & < $10 Million

≥ $10 Million & < $25 Million

≥ $25 Million & < $50 Million

≥ $50 Million & < $HSR SOT

Threshold

≥ $HSR SOT Threshold

Overall

Domestic Foreign

400

216

% Domestic

68.3%

68.8%

58.6%

66.7%

60.5%

% Foreign

31.7%

31.2%

41.4%

33.3%

39.5%

67.0%

64.9%

33.0%

35.1%

The share of domestic transactions in each transaction range were somewhat similar across the

different transaction ranges, ranging from 58.6% (for the $10-25 million range) to 68.8% (for the

$5-10 million range).

Figure 10: Percent of Domestic and Foreign Transactions by

Range

100.0%

90.0%

80.0%

31.7%

31.2%

68.3%

68.8%

33.3%

41.4%

39.5%

33.0%

70.0%

60.0%

50.0%

40.0%

30.0%

66.7%

58.6%

60.5%

67.0%

20.0%

10.0%

0.0%

≥ $1 Million

& < $5 Million

≥ $5 Million

≥ $10 Million

≥ $25 Million

≥ $50 Million

& < $10 Million & < $25 Million & < $50 Million & < $HSR Filing

Threshold

Domestic

Foreign

≥ $HSR Filing

Threshold

The higher number of transactions in the $1-5 million range than in the $5-10 million range, and

transactions in the $10-25 million range than in the $25-50 million range, extended to the

number of both domestic and foreign transactions. In addition, the highest numbers of domestic

transactions were in the $1 to $5 million and $10 to $25 million ranges, whereas the highest

number of foreign transactions was in the $10 to $25 million range.

Figure 11: Number of Domestic and Foreign Transactions by

Range

Domestic

Foreign

≥ $1 Million & < $5 Million

≥ $5 Million & < $10 Million

≥ $10 Million & < $25 Million

≥ $25 Million & < $50 Million

≥ $50 Million & < $HSR SoT Threshold

≥ $HSR SoT Threshold

100

120

f. Transactions with Debts/Liabilities

In 36% of the transactions (excluding Hiring Events and Patent Acquisitions), the acquirer

assumed some amount of debt or liabilities that the acquired entity had on its balance sheet. On

average, for each of the five respondents, 25.7% of the target entities they acquired had debts or

liabilities as of the time of the consummation of the transaction.

Figure 12: Percent of Transactions with

Debts/Liabilities

40.0%

36.0%

35.0%

28.8%

30.0%

25.7%

25.0%

20.0%

15.0%

10.0%

5.0%

0.0%

Total Across Respondents

Average Per Respondent

Standard Deviation

Of the transactions reported, three additional transactions would have exceeded the HSR SOT

threshold (i.e., in addition to the 94 transactions already above the HSR SOT threshold) at the

time of their consummation when adding the debts or liabilities to their purchase price (to

provide a measure of what the purchase price would have been with no debts or liabilities on the

acquired entity’s balance sheet). At the respondent level, this amounts to an additional 0.6

transactions per respondent on average, with a standard deviation of 1.2.

g. Transactions with Deferred/Contingent Compensation

A majority of transactions also used deferred or contingent compensation to founders and key

employees, with relatively small variation across the five respondents.

Figure 13: Percentage of Transactions with

Deferred/Contingent Payments

100.0%

90.0%

80.0%

79.1%

79.7%

70.0%

60.0%

50.0%

40.0%

30.0%

20.0%

12.2%

10.0%

0.0%

Total Across Respondents

Average Per Respondent

Standard Deviation

The Pearson correlation between the logarithm of the acquisition value and the acquisition

including deferred or contingent compensation is 0.28 (statistically significant at < 1%); that is,

higher value transactions were more likely to use deferred or contingent compensation.

Figure 14: Percentage of Transactions with Deferred/Contingent

Compensation by Transaction Range

100.00%

90.12%

90.00%

78.49%

80.00%

89.47%

87.23%

≥ $50 Million

& < $HSR SoT

Threshold

≥ $HSR SoT

Threshold

83.33%

70.00%

60.00%

56.55%

50.00%

40.00%

30.00%

20.00%

10.00%

0.00%

≥ $1 Million

& < $5 Million

≥ $5 Million

≥ $10 Million

& < $10 Million & < $25 Million

≥ $25 Million

& < $50 Million

Of the transactions reported, nine additional transactions would have exceeded the HSR SOT

threshold (i.e., in addition to the 94 transactions already above the HSR SOT threshold) at the

time of their consummation when adding the deferred or contingent compensation (that is

separate, and in addition to their purchase price) to their purchase price. At the respondent level,

this amounts to an additional 1.8 transactions per respondent on average, with a standard

deviation of 2.7.

h. Transactions with Non-Compete Clauses

A majority of transactions, 76.7%, included non-compete clauses for founders and key

employees of the acquired entities, with relatively small variation in the percentage of

transactions that had non-compete clauses across the five respondents.

Figure 15: Percentage of Transactions with NonCompete Clauses in Merger Agreements

100.0%

90.0%

80.0%

77.3%

78.7%

70.0%

60.0%

50.0%

40.0%

30.0%

15.2%

20.0%

10.0%

0.0%

Total Across Respondents

Average Per Respondent

Standard Deviation

The Pearson correlation between the logarithm of acquisition values and the acquisitions that

include non-compete clauses for founders and key employees, on a range of -1 to 1, is 0.24

(statistically significant at < 1%); that is, higher value transactions were more likely to use noncompete clauses. This positive correlation is mostly driven by the smaller transactions of $25

million or less ─ the proportion of transactions with non-compete clauses roughly stabilizes for

larger transactions.

Figure 16: Percentage of Transactions with Specific NonCompete Clauses by Transaction Range

100.00%

87.65%

90.00%

80.95%

77.42%

80.00%

84.21%

85.11%

≥ $50 Million

& < $HSR SoT

Threshold

≥ $HSR SoT

Threshold

70.00%

60.00%

56.55%

50.00%

40.00%

30.00%

20.00%

10.00%

0.00%

≥ $1 Million

& < $5 Million

≥ $5 Million

≥ $10 Million

& < $10 Million & < $25 Million

≥ $25 Million

& < $50 Million

i. Transactions by Employee Size (Full-Time, Non-Sales)

In Control and Asset transactions for all or substantially all of the assets of the acquired entity (or

a division, subsidiary, office, or product, research, or development team of the acquired entity),

the respondents reported the number of full-time non-sales employees, if any, that joined the

acquiring firm after the transaction was consummated. In the majority of transactions (a total of

419) for which the number of full-time non-sales employees were reported, the number of

employees were between 1 and 10. In addition, the employee counts are positively correlated

with the sizes of the transactions.

Figure 17: Relative Frequencies of Full-Time Non-Sales

Employees Ranges by Transaction Range

Number of Transactions

62.1%

84.6%

37.1%

55.3%

60.9%

86.7%

65.6%

31.3%

18.4%

14.1%

11.1%

2.2%

26.3%

25.0%

1.3%

6.3%

0.8%

1.6%

9.4%

≥ $1 Million

& < $5 Million

≥ $5 Million

& < $10 Million

≥ $10 Million

& < $25 Million

1-10

11-50

≥ $25 Million

& < $50 Million

51-100

≥ $50 Million

& < $HSR SoT

Threshold

≥ $HSR SoT

Threshold

100+

On a more granular level, the Pearson correlation between the logarithm of transaction values

and the logarithm of the number of full-time non-sales employees of the target entities who

joined the acquiring firm after the acquisitions of the target entities is 0.74 (significant at < 1%);

that is, larger transactions tended to be associated with more employees from the target entity

joining the acquiring firm.

j. Transactions by Target Age

Staff collected additional data on the founding date of the acquired entities (excluding Hiring

Events, Patent Acquisitions, and transactions below $1 million) from PitchBook, S&P 451

Research, and Refinitiv. Staff used this information to determine the age of the target firms as of

the time of the consummation of their acquisitions, adopting several approaches to determine a

target firm’s age: using each of the three data sources individually, as well as in combination. An

advantage of the latter is that more target firms are matched with founding dates; in the cases of

differing information about a target’s founding date in the three data sources, we incorporated

either the latest founding date or the earliest founding date (uniformly across all such cases). We

report the two approaches that utilize a combination of the three data sources, using the latest

founding date (the first approach below) and the earliest (the second approach below) founding

date in cases of differing information.

Figure 18: Transactions by Target Age Group (Using Latest Available Founding

Year When Information Differs)

Target Age Range

(Using Latest

Available)

< 5 years old

≥ 5 years old & < 10

years old

≥ 10 years old & < 15

years old

≥ 15 years old

Target Founded Date

Missing

Total # of Transactions

Total

% of Total

Average # Per

Respondent

Standard

Deviation

295

148

47.9%

24.0%

29.6

23.9

14.4

9.4%

11.6

8.3

5.5%

13.1%

6.8

16.2

3.0

7.8

616

As indicated above, when the founding year differed across the three databases, we used two

different approaches to analyze the number of acquisitions per calendar year in each age group.

This first approach above takes the latest available founding year (and hence the lowest age) for

these firms in cases of differing information.

Figure 19: Number of Transaction by Target Age Group (Using

Latest Available Founding Year When Information Differs)

≥ 15 years old

≥ 10 years old & < 15 years old

≥ 5 years old & < 10 years old

< 5 years old

Target Founded Date Missing

100

150

200

250

300

350

Under this first approach, the number of acquisitions in the youngest (< 5 years old) age group

exceeds the number of acquisitions in each of the other age groups.

Figure 20: Number of Transaction by Calendar Year (Using

Latest Available Founding Years When Information Differs)

Number of Transactions

2010

2011

< 5 years

2012

2013

≥ 5 years & < 10 years

2014

2015

2016

≥ 10 years & < 15 years

2017

2018

2019

≥ 15 years

missing

The number of acquisitions in the youngest age group (< 5 years old) fluctuated over time,

peaking in 2014. The number of acquisitions in other age groups tended to be higher in the later

years than in the earlier years.

The second approach uses the earliest available founding year (and hence the highest age when

information in the three databases differed) and results in some of the acquisitions shifting from

younger to older age groups. Under this second approach, the number of acquisitions in the

youngest (< 5 years old) age group also exceeds the number of acquisitions in each of the other

age groups. However, this approach results in a smaller number of acquisitions in the youngest

(< 5 years old) age group and larger numbers of acquisitions in all three other age groups.

Figure 21: Transactions by Target Age Group (Using Earliest Available Founding

Year When Information Differs)

Target Age Range

(Using Earliest

Available)

< 5 years old

≥ 5 years old & < 10

years old

≥ 10 years old & < 15

years old

≥ 15 years old

Target Founded Date

Missing

Total # of Transactions

Total

% of Total

Average # Per

Respondent

Standard

Deviation

242

171

39.3%

27.8%

48.4

34.2

19.0

18.8

10.2%

12.6

7.6

9.6%

13.1%

11.8

16.2

4.8

7.8

616

Figure 22: Number of Transaction by Target Age Group (Using

Earliest Available Founding Year When Information Differs)

≥ 15 years old

≥ 10 years old & < 15 years old

≥ 5 years old & < 10 years old

< 5 years old

Target Founded Date Missing

100

150

200

250

300

In summary, depending on the approach used, between 39.3% to 47.9% of transactions were for

target entities that were less than five years old at the time of their acquisition. This percentage

range could also be different (i.e., fall outside of this range), as the target entities in 13.4% of the

transactions did not have founding dates located in any of the three databases.

Figure 23: Number of Transaction by Calendar Year (Using

Earliest Available Founding Years When Information Differs)

Number of Transactions

2010

2011

< 5 years

2012

2013

≥ 5 years & < 10 years

2014

2015

2016

≥ 10 years & < 15 years

2017

2018

≥ 15 years

missing

2019

Under the second approach, the number of acquisitions in the youngest age group (< 5 years old)

also peaked in 2014, and the number of acquisitions in the other age groups again tended to be

higher in the later years than in the earlier years.

k. Transactions by Sector

Using information from the S&P 451 Research database, we assigned Primary Sector categories (Level 1 in the S&P taxonomy, which

is the broadest of four levels) to target entities in all categorized transactions (excluding Hiring Events and Patent Acquisitions) where

this information was available (it was not available for approximately 270 transactions). The eight categories with the highest number

of acquisitions, in descending order, were:

Mobility (mobile devices and device-based software and content);

Application Software (front-end applications such as CRM, ERP, SCM, BI, commerce and vertical business software);

Internet Content & Commerce (internet destination and internet-enabled services);

Infrastructure Management (software to control and manage IT infrastructure including software development, BPM,

virtualization and application performance and cloud management);

Information Management (software to control information flows including collaboration, email and data management and

retrieval);

Systems (computers, peripherals and control systems);

Security (IT security software and systems including physical security and surveillance); and

Media Technologies (systems to control VOD, broadcasting and streaming media, including set top boxes, video encoding and

production systems).

Figures 24-31 depict the total number of acquisitions per calendar year in each of these categories, along with some notable

technological events that pertain more specifically to each category.51

Events listed are based solely on public information and are included in order to provide context to Figures 24-31.

Figure 24: Number of Mobility Transactions Per Year

- Google introduced Google Nexus smartphone

- Apple introduced iPad

- Uber launched first in San Francisco

- Instragram released

Number of Transactions

- Apple CarPlay released

- Apple Pay announced

- Apple Watch released

- Pinterest launched iPhone app

- Snapchat launched app

- Apple launched iMessage

- Apple integrated Siri into iPhone

- Amazon introduced Kindle Fire tablet

- Google Assistant announced

- Instagram launched "Stories" feature

- Apple announced AirPods

- Apple launched standalone

Podcasts app

- Amazon released Kindle

Paperwhite

- Facebook launched Stories feature

- Apple announced FaceID for iPhone

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 25: Number of Application Software Transactions Per Year

- Minecraft released; acquired by

Microsoft in 2014

- Microsoft announced Windows 10

- Microsoft released

Windows 8

- Alphabet DeepMind's AlphaGo AI

defeated top ranked Go player

Number of Transactions

- Salesforce completed acquisition of

analytics platform Tableau

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 26: Number of Internet Content and Commerce Transactions Per Year

- Google Wallet launched

- Google launched Google+

- Google shuts down Google+

Facebook filed IPO

- Square launched Square Cash

- PayPal acquired Venmo

Number of Transactions

- Facebook launched Trending Topics feature

- Facebook introduced free friend-to-friend

payment service

- Bitcoin reached $10,000

for the first time

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 27: Number of Information Management Transactions Per Year

- Microsoft acquired Skype

- Microsoft launched Office 365 globally

November 2011: Asana launched

- Microsoft acquired Yammer

- Slack launched

Number of Transactions

- Whatsapp Business launched

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 28: Number of Infrastructure Management Transactions Per Year

- Microsoft announced generally availability of Azure ExpressRoute

- Google announced Kubernetes

- AWS launched Lambda

- Microsoft Azure released

- Google Cloud Storage launched

- IBM acquired Red Hat

Number of Transactions

- AWS CloudFormation launched

- Apple announced iCloud

- AWS Direct Connect introduced

- Average number of SaaS apps used

per organization doubled from 2015

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 29: Number of System Transactions Per Year

- Microsoft announced Kinect for Xbox 360

- Google announced its plans for a self-driving

car, what would be called Waymo

- Google Glass announced

- OculusVR formed

- Microsoft released Surface

- Microsoft released Xbox One; Sony

released PlayStation 4

Number of Transactions

- Microsoft released HoloLens

- Google released

Chromebook

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 30: Number of Security Transactions Per Year

4.5

- Lockhead Martin released Cyber Kill Chain model

- WannaCry ransomware attack took place

- Ring launched its first video doorbell

3.5

- NIST released Framework for Improving

Critical Infrastructure Cybersecurity

Number of Transactions

2.5

1.5

0.5

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

Figure 31: Number of Media Technologies Transactions by Year

- Twitch launched; acquired by

Amazon in 2014

- Spotify reached over 100M total MAU

- Google released Chromecast

Number of Transactions

- Amazon announced Echo and

Alexa

- Apple TV+ debuted

- Netflix had over 167 million global

streaming paid memberships worldwide

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

4. Summary

The five technology platform 6(b) respondents identified 616 non-HSR reportable

transactions above $1 million, in addition to 101 Hiring Events and 91 Patent Acquisitions. The

respondents reported an additional approximate 60 transactions below $1 million and 160

financial investments. Voting Security (Control) and Asset acquisitions comprise 65% of all of

the above transactions. When excluding Hiring Events, Patent Acquisitions, and transactions

below $1 million, Voting Security (Control) and Asset acquisitions comprise 85% of the

transactions.

Focusing on the 616 transactions at or above $1 million (that exclude Hiring Events and

Patent Acquisitions), the study led to a number of observations:



The total number of such transactions per calendar year across the five respondents

ranged from 43 at its lowest per calendar year (in 2012) to 79 at its highest (in 2014), and

remained relatively higher in 2015-2019 (ranging from 63 to 74 transactions) than in

2010-2013 (ranging from 43 to 63 transactions).



The number of such transactions in each transaction size range fluctuated but generally

trended up over the 2010-2019 time period (ranges were between $1 Million and $5

Million, with 23.54% of the transactions; between $5 Million and $10 Million, with

15.10% of the transactions; between $10 Million and $25 Million, with 26.30% of the

transactions; between $25 Million and $50 Million, with 13.64% of the transactions;

between $50 Million and $HSR Size of Transaction Threshold, with 6.17% of the

transactions; and greater than the HSR Size of Transaction Threshold, with 15.26% of the

transactions).



Of these transactions, 65% were between $1 million and $25 million.



Asset and Control transactions (including Voting Security Control and Non-Corporate

Interest Control transactions) were the most common in each transaction range. For

transactions exceeding $5 million, the majority were Control transactions. Moreover,

higher-value transactions were more likely to be Control acquisitions.



The majority of transactions in each transaction range were for domestic firms, with

roughly two thirds of the entities acquired in each transaction range being domestic.



In 36% of the transactions, the acquirer assumed some amount of debt or liabilities. Such

debts and liabilities, when added to the purchase price of the target, would have tipped

the purchase amount of three transactions above the HSR Size of Transaction threshold.

That is, three more transactions would have been added to the 94 transactions already

above the HSR Size of Transaction threshold.



More than 79% of transactions also used deferred or contingent compensation to founders

and key employees, with relatively small variation across the five respondents. Higher

value transactions were more likely to use deferred or contingent compensation. Of the

transactions reported, nine additional transactions would have exceeded the HSR Size of

Transaction threshold (i.e., in addition to the 94 transactions already above the HSR Size

of Transaction threshold) at the time of their consummation when adding the deferred or

contingent compensation to their purchase price.



More than 75% of transactions included non-compete clauses for founders and key

employees of the acquired entities, with relatively small variation in the percentage of

transactions that had non-compete clauses across the five respondents. Higher value

transactions were more likely to use non-compete clauses.



In more than 50% of the transactions for which the number of the target entity’s full-time

non-sales employees that were hired by the acquirer was reported by respondents (68% of

the transactions), the number of employees was between 1 and 10. In addition, the

employee counts are positively correlated with the size of the transaction.



At least 39.3% of the transactions where the target’s age was available (86.9% of the

transactions) were for firms that, as of the time of the consummation of the transaction,

were less than five years old. The distribution of the acquired firms’ ages in each calendar

year appeared to marginally, though not considerably, change over 2010-2019. The

largest such variation was for the number of acquisitions of firms that were less than five

years old, which mostly decreased after 2014.



Most of the transactions that were classified into technology categories were concentrated

in the categories of Mobility (mobile devices and device-based software and content,

which comprised more than 10% of the acquired firms), Application Software (front-end

applications such as CRM, ERP, SCM, BI, commerce and vertical business software,

which comprised more than 9% of the acquired firms), and Internet Content &

Commerce (internet destination and internet-enabled services, which comprised more

than 6% of the acquired firms). In the Mobility and Application Software categories, the

number of transactions peaked in 2015; in the Internet Content & Commerce category,

the number of transactions peaked in 2011.

This report analyzed certain aspects of the set of non-HSR reportable transactions by five

of the largest technology firms during the period of 2010-2019. Notably, the report adds to the

existing body of empirical literature on the subject by analyzing a number of trends and patterns

identified in the data. The information intends to inform ongoing discussions among

policymakers, academics, and other stakeholders.

September 2021

This is a copy of a public record, reproduced as it was published. It is not legal advice, and it may not be the version a court would rely on. Check the official source before you cite it.