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Ranked: Who Made the Most U.S. Unicorn Acquisitions Since 1997?

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A bubble chart visualizing the companies that made the most U.S.-based unicorn acquisitions between 1997 and 2021.

Who Made the Most U.S. Unicorn Acquisitions Since 1997?

The elusive unicorn is no longer a myth in the U.S. startup world, with over a thousand private startups reaching a $1 billion valuation in the last 25 years.

While some of these startups eventually go public and go on to become household names, it’s also common for founders to exit through mergers and acquisitions (M&A), by selling their startup to another organization. In fact, over half of the 1,110 unicorns in the U.S. have made some sort of an exit—either through an IPO, a direct listing, a SPAC or an acquisition—since 1997.

Ilya Strebulaev, professor of finance and private equity at the Stanford Graduate School of Business, brings us this visualization featuring the companies that acquired the most unicorns over the last 25 years.

Strebulaev’s database lists 137 private and public companies along with PE firms who’ve acquired at least one unicorn since 1997, totaling 177 acquisitions.

The Biggest U.S. Unicorn Acquirers

In total, 27 companies have acquired two or more unicorns, accounting for nearly 38% of all acquisitions. 110 companies have acquired just one unicorn.

Company/ PE GroupAcquired
Meta5
Cisco4
Alphabet4
Amazon3
Nortel Networks3
Bristol-Myers Squibb3
Johnson & Johnson3
Merck & Co.3
AT&T3
Recruit Holdings2
IBM2
Microsoft2
Thoma Bravo2
Headspace Health2
Allergan2
Qualcomm2
Rakuten2
Adobe Systems2
Eli Lilly2
Vista Equity2
Dell2
Uber2
Oracle2
Nestle2
Lucent Technologies2
Broadcom Corporation2
GlaxoSmithKline2
Searchlight Capital Partners1
Singtel1
Vmware1
Internet Capital Group1
Hellman & Friedman1
AppLovin1
Ciena Corporation1
Redback Networks1
Aether Systems1
Fresenius Medical Care1
Electronic Arts1
Genentech1
Inktomi1
VistaJet1
Ariba1
Keurig Dr Pepper1
Fullscreen1
Sycamore Networks1
Novartis1
TP ICAP1
eBay1
DoveBid1
McKesson1
IG Group1
Empower Retirement1
Dentsply Sirona1
Novo Nordisk1
Centocor1
Bausch Health1
Dainippon Sumitomo Pharma1
Medtronic1
Mubadala Investment Company1
Cint Group1
Qualtrics1
Rocket Companies1
Saudi Arabia's PIF1
Prosus1
Cigna1
One Medical1
Exact Sciences1
Teladoc Health1
Ericsson1
SoFi1
PayPal Holdings1
Bayer1
Monsanto1
AMD1
Aurora1
Marvell International1
Bill.com1
ADC1
Blackberry1
Dealertrack1
Cox Enterprises1
L'Oreal1
AstraZeneca1
Workday1
Iron Mountain1
Splunk1
Stonepeak1
American Express1
OfferUp1
VMware1
Ontario Teachers' Pension Plan1
Groupon1
Allstate Corporation1
LinkedIn1
SAP1
Mindbody1
Mallinckrodt1
BlackBerry1
Walmart1
GMT Communications1
Brightstar Capital1
Enterprise Holdings1
Healtheon Corporation1
Apple1
PetSmart1
Epiphany1
Rice Energy1
Unilever1
SBA Communications1
Bridgepoint Advisers1
Aurea1
Vector Capital1
FireEye1
Littlejohn & Co1
Alexion1
SoftBank Investment Advisers1
Francisco Partners1
Betfair Group1
Shift Technologies1
Hudson's Bay1
Illumina1
Hewlett Packard Enterprise1
AbbVie1
Salesforce1
Hanergy1
Teleflex1
Twilio1
Okta1
Celgene1
NantCell1
VMware & EMC Corp1
Intuit1
Yahoo!1
Netmarble Games1
F5 Networks1
Roche1
Centerbridge Partners1
Total177

Meta, the parent company of Facebook, leads the pack with the most unicorn acquisitions in the U.S., purchasing five unicorns since its founding in 2008, including: Kustomer, WhatsApp, Instagram, CTRL-Labs, and Oculus VR.

Notably, WhatsApp—which closed at a purchase price of $19 billion—was Meta’s most expensive acquisition yet, over nine times their next most expensive purchase, Oculus VR.

Meanwhile, Alphabet (now the parent company of Google) and Cisco are tied in second place with four U.S. unicorn acquisitions each.

  • Alphabet: YouTube, Actifio, Nest Labs, Looker Data Sciences
  • Cisco: Cerent, Duo Security, AppDynamics, Jasper

Unlike its Big Tech peers, Apple has only made the one U.S. unicorn acquisition: navigation company HopStop that helped bring public transit features to Apple Maps.

Meanwhile, 56% of acquirers received venture capital funding of their own when they were private companies. This includes pack leaders like Meta, Cisco, Alphabet, and Amazon.

Are Unicorn Acquisitions Slowing Down?

Unicorn acquisitions are driven by two factors: the rate at which new unicorns are minted, and the climate for M&A transactions more broadly.

To begin with, the minting of new unicorns is largely influenced by the venture funding environment. Funding opportunities increase when interest rates go down, which makes riskier, venture-scale ideas more enticing. During the last decade of persistently low interest rates up until 2022, unicorns flourished more than ever.

Meanwhile, as tech companies like Apple, Microsoft, Alphabet, and Meta began seeing outsized profits in the 2010s, venture investors and their LPs looked to get in on the ground floor of tech startups that could emulate their success, often paying premium valuations for the chance. Simultaneously, big tech looked to acquire unicorns themselves, both to augment their business lines and to squash potential competitors.

However, the era of “easy money” may have come to an end, and privately-held startups have seen valuations drop in recent years. This means that for the next little while—at least until monetary policy stops tightening—unicorns could become a rarer sight.

Unicorn acquisitions may also see a similar fate. Persistent inflation and the government anti-trust push are just some of the other factors that have led to VC-backed startup acquisitions falling to their lowest quarterly levels in a decade. The more expensive the valuation, the harder to find a buyer, which means that some unicorns may even lose their $1 billion tag even when they do get acquired.

How does a startup become a unicorn? Check out How Startups Can Improve Their Odds of Becoming a Unicorn which provides a blueprint to navigate this enormous task.
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This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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AI

Visualizing Global Attitudes Towards AI

We visualize survey results from over 19,000 adults across 28 countries to see how attitudes towards AI differ around the world.

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Comparing Public Sentiment Towards AI, by Country

Artificial intelligence (AI) is one of the fastest growing and most disruptive technologies in the world today. Because it has the potential to drastically impact society, it’s important to measure how people are feeling towards it.

This infographic visualizes survey data from market research firm, Ipsos, to see how attitudes towards AI varies by country. By including each country’s GDP per capita, we can see that wealthier populations are more skeptical about products and services that use the technology.

Data and Methodology

This data is based on a 28-country survey of 19,504 adults aged 18 to 74. Polling took place between November and December 2021, and the results were published in January 2022.

This survey took place before the recent explosion in popularity of generative AI tools such as ChatGPT, DALL-E, and Midjourney, but forms the foundation for how people view this rapidly improving technology.

The table below lists the percentage of respondents who agreed with the following statement:

“Products and services using artificial intelligence have more benefits than drawbacks”

Country% Agreeing With StatementGDP per capita
China78%$12,556
Saudi Arabia76%$23,186
India71%$2,257
Peru70%$6,622
Malaysia65%$11,109
Mexico65%$10,046
Colombia64%$6,104
Chile63%$16,265
South Korea62%$34,998
Türkiye60%$9,661
Brazil57%$7,507
South Africa57%$7,055
Argentina55%$10,636
Russia53%$12,195
Spain53%$30,104
Italy50%$35,658
Hungary49%$18,728
Poland48%$18,000
Japan42%$39,313
Sweden40%$61,029
Belgium38%$51,247
UK38%$46,510
Australia37%$60,443
Germany37%$51,203
United States35%$70,249
Netherlands33%$57,768
Canada32%$51,988
France31%$43,659

GDP per capita as of 2021. Source: World Bank

Ipsos notes that their samples from developing economies like China and India were “more urban, more educated, and more affluent than the general population”. Thus, the results for these countries likely reflect the more tech-savvy segments of their population.

Further Survey Results

Respondents were asked additional questions about AI, which we’ve included in the tables below. Let’s start with this statement:

“Products and services using artificial intelligence make my life easier”

Country% Agreeing With StatementGDP per capita
China87%$12,556
Saudi Arabia80%$23,186
Peru74%$6,622
South Korea74%$34,998
Mexico73%$10,046
India72%$2,257
Colombia71%$6,104
Malaysia71%$11,109
Türkiye71%$9,661
Chile70%$16,265
South Africa67%$7,055
Brazil65%$7,507
Russia64%$12,195
Argentina59%$10,636
Spain59%$30,104
Poland58%$18,000
Italy54%$35,658
Japan52%$39,313
Hungary50%$18,728
Belgium49%$51,247
Netherlands47%$57,768
Australia46%$60,443
Sweden46%$61,029
Germany45%$51,203
UK45%$46,510
Canada44%$51,988
United States41%$70,249
France39%$43,659

As expected, we see a similar trend as in the previous question’s results. It seems that developing countries are embracing AI to greater lengths.

Next, we’ll look at a more forward-looking statement:

“Products and services using AI will profoundly change my daily life in the next 3-5 years”.

Country% Agreeing With StatementGDP per capita
China80%$12,556
Saudi Arabia80%$23,186
South Korea76%$34,998
India74%$2,257
Türkiye73%$9,661
South Africa72%$7,055
Malaysia71%$11,109
Peru71%$6,622
Chile67%$16,265
Colombia65%$6,104
Mexico65%$10,046
Brazil61%$7,507
Argentina60%$10,636
Russia60%$12,195
Poland56%$18,000
Spain56%$30,104
Hungary55%$18,728
Italy53%$35,658
Japan53%$39,313
Netherlands53%$57,768
Belgium52%$51,247
Australia50%$60,443
Sweden50%$61,029
UK46%$46,510
United States46%$70,249
France45%$43,659
Canada44%$51,988
Germany44%$51,203

Once again, populations from wealthier countries are at the lower end of the results. This could be due to societal factors (differing attitudes towards technology), economic structure, or some combination of both.

To elaborate on economic structure, let’s look at the world’s two biggest economies, the U.S. and China. The following table shows the distribution of each country’s workforce across the three major sectors.

Economic SectorU.S.China
Agriculture1%25%
Industry20%28%
Services79%47%

As of 2019. Source: Statista

Developing economies such as China have a larger proportion of agricultural and industrial employment, while advanced economies like the U.S. are typically more services oriented. Structural differences such as these could have an impact on how a population views AI.

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