M&A Activity of Major Tech Firms

M&A Activity of Major Tech Companies:
Implications for Venture Capitalists
Allen Miller
May 5th
2014

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Table of Contents
Background & Motivation…………………………………………………………………...……3
M&A & VC Landscape in the last 3 Years……………………………………………………….4
M&A Motivations: A Review of the Literature…………………………………………………..7
M&A Motivation Model and Research Methodology…………………………………………...10
Results: Motivations Behind Tech M&A Activity………………………………………………13
Implications for VCs…………………………….……………………………………………….17
Works Cited……………………………………………………………………………………...19
Appendix…………………………………………………………………………………………20

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Background & Motivation
In February of 2014, mobile messaging company WhatsApp was purchased by Facebook
for about $16 billion, $4 billion in cash and $12 billion in stock. This was the largest tech
acquisition since HP bought Compaq for $25 billion in 2001.1
In the process, the company’s exit
generated a tremendous return for Sequoia Capital—the sole venture capital firm that had backed
WhatsApp with approximately $58.3 million over the course of three financing rounds.2
In fact,
Sequoia’s roughly 20% ownership stake resulted in an estimated $3 billion payout or a 50x
return on invested capital.3
Since then there has been a greater focus on the M&A activity of
large tech firms and what this activity implies for venture capitalists (VCs).
The focus of this paper will be to understand the recent (last 3 years) M&A activity of
four of the largest global tech companies: Apple, Facebook, Google and Microsoft. Specifically
the paper will analyze the implications this M&A activity has for early stage VCs focused on
investing in tech companies. In analyzing the acquisition activity of these major tech companies,
this paper will build a two-fold hypothesis around (1) why large tech companies have been
acquiring the specific targets they have acquired in the last three years and (2) with this
knowledge, what types of opportunities should VCs be investing in to best realize a return on
their investments through an M&A exit.
The paper will begin by providing a descriptive overview of the M&A landscape as well
as outlining important trends in the VC industry in the last 3 years. The paper will then review
the existing literature on the motives behind the M&A activity of large tech firms. Building on
1
Jordan Crook, “Facebook’s $19 Billion WhatsApp Acquisition, Contextualized,” http://techcrunch.com/2014/02/1
9/f acebooks-19-billion-whatsapp-acquisition-contextualized/, TechCrunch, (February 19, 2014).
2
“WhatsApp,” TechCrunch, http://www.crunchbase.com/company/whatsapp.
3
Ryan Lawler, “Sequoia’s A Big Winner In Facebook’s WhatsApp Acquisition, With Its Stake Worth About $3
Billion,” http://techcrunch.com/2014/02/19/sequoia-and-jim-goetz-are-big-winners-in-facebooks-whatsapp-
acquisition/, TechCrunch, (February 19, 2014).

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the existing literature, the paper will then propose a model with which to examine M&A activity
of the largest tech firms. In this section, the research methodology and econometric tools used
will be highlighted. The paper will then present the results of this M&A model answering the
motivational questions behind tech M&A activity. Finally, the paper will conclude by
demonstrating the implications of the research conducted here for early stage VCs. In doing so,
the paper will present a framework for VCs to consider when investing in startups.
M&A & VC Landscape in the last 3 Years
Since the financial crisis of 2008, global technology, media and telecom (TMT) M&A
activity has bounced back year after year to a five year high of $510 billion in 2013.4
As shown
in Exhibit 1, within the last 3 years, quarterly M&A volume in the TMT sector has risen by
nearly 100 deals per quarter from 663 in Q1 2011 to 762 in Q4 of 2013. This increasing deal
volume has particularly accelerated in 2013.5
In addition, the average deal size for global TMT
deals has also risen in recent years landing at $443.2 million in 2013.6
Within the healthy rise of TMT M&A activity, the technology subset of deal volume has
been growing particularly quickly since 2011. Exhibit 2, shows transaction volume by subset
within TMT in the last 3 years. While all three sectors have been growing since 2011, the
technology sector has grown particularly quickly. In fact, in Q3 and Q4 of 2013, both quarters
increased to record highs with 543 (Q3) and 539 (Q4) respective transactions. Importantly,
4
Peter High, “2013 Global Tech, Media, And Telecom M&A Up Over 50% From 2012,” http://www.forbes.com/sit
es/peterhigh/2014/01/20/2013-global-tech-media-and-telecom-ma-up-over-50-from-2012/, Forbes,
(January 20th
2014).
5
“Global M&A Report Technology-Media-Telecom Sectors,” BDO, February 2014, 2.
6
High, “2013 Global Tech, Media, And Telecom M&A Up Over 50% From 2012.”

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technology continues to remain the highest relative share of transaction volume in the TMT
space—with approximately 2/3 of over-all deal volume.7
Within the technology sector there are four critical trends that have affected M&A
activity in the last 3 years. The first of these trends is in big data, which has grown rapidly in the
past 3 years. According to IBM, 2.5 quintillion bytes of data are created each day. Gathering and
mining this data is a tremendous problem that many companies are trying to solve. It is therefore
no surprise that this is one of the fastest growing areas of acquisition interest for large tech
companies. In 2013 alone, there were 40 big data companies acquired. Examples include:
BlitzerMobile acquired by Oracle and Infochimps acquired by Computer Sciences Corporation.8
Wearable technology is another increasingly important area for large tech companies.
According to Juniper Research, the wearable device market is expected to grow from $1.8 billion
in 2013 to $19 billion in 2018. Early interest in the area is coming from fitness and apparel
companies like Under Armor, which recently acquired MapMyFitness, and Nike, whose
FuelBand led to an 18% increase in the company’s equipment division profits in 2013. Other
wearable technologies like Google Glass and Sony SmartWatch are likewise receiving much
publicity.9
A third area of interest for many large tech companies is cyber security. As internet
activity continues to grow and many companies move to the cloud, there is a rising demand for
cyber security to protect against hackers and malicious software. In 2013, there were a total of 42
transactions in the security space. Examples include Stonesoft’s acquisition by McAfee and
Sourcefire’s acquisition by Cisco.10
7
8
9
“Global M&A Report Technology-Media-Telecom Sectors,” BDO, February 2014, 4-5.
10

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The fourth and final trend is the industry movement to cloud computing. Over the last 3
years, many large tech companies have transitioned to working, storing and building applications
in the cloud. There were 90 cloud M&A transactions in 2013 alone. Furthermore, within cloud
computing, cloud storage is particularly growing rapidly and is expected to be a $46.8 billion
market by 2018. As a result, companies like Dropbox have soared in popularity and been
primary candidates for acquisition.11
There are a number of important trends in the venture capital industry since 2011 that are
worth highlighting as well. As with M&A activity, venture capital financing has likewise
continued to grow over the course of the last 3 years as there has been a growing sense of
confidence throughout the entire venture ecosystem. As compared to 2011 and 2012, 2013 saw
venture capital deals rise by 3% and 9% respectively. In 2013, venture capital financing hit $29.2
billion across 3,354 deals. Exhibit 3 displays the upward trend in venture deal volume and
investment dollars since Q1 of 2011.12
In the last 3 years, venture capital firms have been moving towards making earlier stage
investments. In particular, there has been a proliferation of seed deals (smaller investments under
approximately $1 million) since 2011. Exhibit 4 shows a chart of quarterly seed deals since Q1
of 2010. As seen in the exhibit, overall seed dollars invested in 2013 increased 22% and 74%
compared to 2012 and 2011 levels. By 2013, Seed deals represented 26% of overall VC deals.
The fundraising climate for venture investors has been improving in line with
improvements to the M&A markets. It has been easier to raise a venture fund, particularly an
early stage fund, now than in any time since before 2008. In 2013, 325 funds were raised—222
of which were early stage funds. Those 325 funds raised a total of $28 billion. Importantly, many
11
12
CB Insights, “2013 Venture Capital Financing and Exit Annual Report,” http://www.cbinsights.com/blog/venture-
capital-report-2013, (January 22, 2014).

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VC firms are doing fewer new deals per year than in the past. Instead firms are re-investing in
their best portfolio companies to maximize their equity stakes and limit dilution.13
A final important macro-trend in the VC industry is the ability for firms to solicit
investments from the public. In 2013, the Securities and Exchange Committee (SEC) gave the
go-ahead for certain provisions in the 2013 JOBS Act—including the ability for firms to publicly
talk about fundraising. Even though, only one VC firm (as of April 2014), ff Venture Capital, has
solicited funds from the general public, it is clear that public solicitation of investments and
crowd funding are here to stay. AngelList has already revolutionized the VC syndicate by
allowing one angel investor to lead a group of accredited investors. Eventually, more investors
(even those who are not accredited) will be allowed to make small investments in private
companies under the crowd funding provision of the JOBS Act.14
M&A Motivations: A Review of the Literature
There is an extensive body of work on the motivational reasons why large tech firms
acquire smaller companies. In his work on M&A activity, Florian Frensch summarized much of
the thought leadership in the field. Exhibit 5 outlines many of these M&A motivational theories
by author.15
In addition to these motivations, Frensch also argues that there may be a number of
high-level macro developments that lead to acquisition. Most notably, Frensch argues that
globalization leads to economy of scale requirements and changes in certain industry dynamics
force consolidation through M&A activity.16
13
“Adapting and Evolving: Global venture capital insights and trends,” Ernst & Young, 2014, 11.
14
Joanna Glasner, “Top Venture Capital Trends in 2013,” http://www.pehub.com/2014/01/top-venture-capital-
trends-in-2013/, Reuters PE Hub, (January 3, 2014).
15
Florian Frensch, The Social Side of Mergers and Acquisitions, (Berlin: DUV, 2007), 27.
16
Frensch, The Social Side of Mergers and Acquisitions, 27.

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Michael Garbade pushed Frensch’s research a bit further by focusing more exclusively on
tech M&A activity. Garbade argues that M&A activity by large tech firms can be categorized
into two distinct buckets: value maximizing and non-value maximizing. Value maximizing
activity entails any activity that results in accrued value to shareholders. Non-value maximizing
activity is driven by other reasons and is not economically sound. Non-value maximizing activity
can include: a firm’s desire to increase market position, management’s desire to increase prestige
and general empire building goals to flex power or status.17
Garbade further argues that there are two types of value-maximizing M&A activity:
operational and financial synergy. Financial synergy centers on increased diversification and
lowered risk. In particular, Garbade argues that large tech firms may acquire a smaller firm in
order to reap the benefits of a reduction in the weighted average cost of capital (WACC). If the
cash flows of the two firms are negatively correlated, and there is a low risk of insolvency that
results from the merger, the acquiring firm can reap the benefits of financial synergy by
purchasing the smaller firm.18
Operational synergy, according to Garbade, consists of revenue-enhancing activities or
cost-reducing activities—essentially affecting both ends of the value stick. On the revenue-
enhancing side, large tech firms may acquire smaller companies in order to increase total sales
by cross-selling products, take advantage of an already installed customer base and exploit
existing distribution channels. On the cost-reducing side of the value stick, large tech firms may
acquire smaller companies in order to take advantage of economies of scale and scope.19
17
Michael Garbade, International Mergers & Acquisitions, Cooperations and Networks in the e-Business Industry,
(Mannheim: GRIN, 2007), 7.
18
Garbade, International Mergers & Acquisitions, Cooperations and Networks in the e-Business Industry, 6.
19
Garbade, International Mergers & Acquisitions, Cooperations and Networks in the e-Business Industry, 5.

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Aswath Damodaran built on Garbade’s initial work by examining the operational synergy
piece of the puzzle more closely. Damodaran argues that there are four specific operational
synergies that a larger firm can benefit from when purchasing a smaller company. The first of
Damodaran’s reasons is economies of scale, which allow the combined firm to become more
cost-efficient. Damodaran argues that this motivation shows up most often in horizontal mergers.
The second operational synergy is greater pricing power due to reduced competition and higher
market share. Damodaran argues that this motivation mostly shows up in mergers of firms in the
same business and often results in the creation of an oligopoly.20
The third operational synergy Damodaran outlines is the motivation to combine a variety
of different functional strengths to shore up on weaknesses in the acquiring firm’s skill set (i.e.
value chain integration). For example, a firm with strong marketing capabilities might acquire a
smaller tech company with a well-developed product line. The fourth and final operational
synergy Damodaran outlines is the pursuit of higher growth in new or existing markets. For
example, a U.S. consumer electronics product firm may acquire an emerging market firm with an
established brand and distribution to increase sales of its products.21
M&A Motivation Model and Research Methodology
The focus of this paper is to test and further expand upon the value-maximizing,
operating synergy motivators introduced by Damodaran. The rationale behind this focus is that
operational synergies are the most relevant and identifiable variables for VCs to focus on as they
think about M&A as an exit option. Operational synergies are also: specific, repetitive (allowing
20
Aswath Damodaran, The Value of Synergy, NYU Stern School of Business, October 2005, 4.
21
Aswath Damodaran, The Value of Synergy, 5.

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for pattern recognition by VCs), have predictive power and can be used to build an investment
thesis.
The paper does not focus on non-value maximizing M&A activity (i.e. management
hubris, empire building, market expansion, etc.) as these motivators are random, personality-
dependent, situation-specific, have no predictive power and do not lend themselves to building
an investment thesis with. Likewise this paper does not focus on financial synergy as these
variables are also very hard to predict, often happen at various points in the business cycle, are
opportunistic and do not lend themselves to investment thesis building. The paper chooses
instead to focus on an area (operating synergy) that VCs can apply directly when making long
term investment decisions.
This paper combines all four of Damodaran’s variables with 3 additional variables that I
wanted to test (both in terms of strength and significance) in building out a complete
motivational model for large tech firm M&A activity. Damodaran’s four motivational variables
(as described above) are: economies of scale, greater pricing power, value chain integration and
growth in new or existing markets. To these variables, I have added 3 additional motivational
variables: enhance core capabilities, tap into large network effects and take advantage of steep
switching costs. These seven motivational M&A variables are outlined in Exhibit 6 below:
Exhibit 6: Miller’s VC-Focused M&A Motivation Typologies
Typology Explanation
Economies of Scale Economies of scale refer to a cost-reducing strategy whereby the
acquirer benefits as a result of decreases in cost per unit due to
total output increasing.
Greater Pricing Power The acquiring firm can have greater pricing power if acquisition
of the target results in reduced competition and higher market
share.
Value Chain Integration Value chain integration refers to Michael Porter’s concept of
either vertical or horizontal integration to take ownership of more
of the activities required to produce a final good or service.
Growth in New or Growth into a new or existing market implies increasing both

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Existing Market market penetration and exposure.
Enhance Core
Capabilities
Enhancing core capabilities translates into shoring up a firms core
business and further enhancing its competitive advantage.
Tap into Large Network
Effects
An acquirer may benefit from a target due to the target’s network
effects—when a network effect is present, the value of a product
or service grows as more people use it.
Take Advantage of
Steep Switching Costs
When consumers are forced to incur costs in switching from one
product to another, the acquirer may benefit from this increased
customer loyalty.
*Shaded region represents variables introduced in this study. Remaining region represents Damodaran’s typologies.
After deciding to build the M&A activity model around these seven variables, I then had
to find representative M&A data on large tech firms. I selected Facebook, Google, Apple and
Microsoft as the 4 acquiring firms for several reasons. First, each of these four firms is in the top
ten tech firms globally by market capitalization. This means that they are purchasing venture-
backed tech startups frequently. In addition, because these are global firms, they are purchasing a
variety of companies in many different industries and at various prices. It also means that they
are interested in acquiring both enterprise (B2B) and consumer facing (B2C) companies. In
addition, I purposefully chose 2 long-standing giants in the tech industry (Apple and Microsoft)
as well as 2 relatively “newer” entrants (Facebook and Google). Through this process, I was able
to create a representative sample with which to build a motivational M&A model.
After selecting the four large acquiring firms, I then looked at the publicly available
M&A history from Q1 of 2011 to present of each firm using CapitalIQ.22
I only included
companies where the premium paid was publicly available—this left a list of roughly 25%-50%
of the target companies for each of the four large tech firms. The remaining companies were
acquired for undisclosed amounts. As a result, there were a total of 40 acquired companies that
were examined in this study. For each acquired company I recorded the industry category it fit
under, whether it was a B2B or B2C company and the premium paid by the acquirer.
22
S&P Capital IQ, https://www.capitaliq.com/home.aspx, McGraw Hill Financial.

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In addition, I used a binary variable classification system to record whether an M&A
motivation variable was present in the rationale behind each acquisition. These motivations were
unearthed by reading the acquiring company’s press release as well as industry analyst reports.
For example, in Facebook’s acquisition of Instagram, the M&A motivation variables present
included enhancing core capabilities (photo sharing is a core function of Facebook), tapping into
large network effects (Instagram had 30+ million users23
at the date of sale) and taking advantage
of steep switching costs (Instagram users spend an average of 257 minutes per month24
on the
site). Exhibit 7 provides an overview of the various inputs that went into building the model.
After organizing and collecting the data outlined above on Apple, Facebook, Google and
Microsoft, I was equipped with enough information to provide both descriptive statistics as well
as econometric analysis. For the descriptive statistics portion of this study, I simply used the data
collected and performed a number of calculations. For the econometric portion of this analysis I
ran two linear regressions. First, I regressed all 7 of the M&A motivation variables on premiums
paid by the acquiring firms. I noticed that several of the variables were not statistically
significant, so I ran a second regression where the statistically insignificant M&A motivation
variables were removed. The results of this analysis follow.
Results: Motivations Behind Tech M&A Activity
Of the 40 acquired firms included in this study, Google (16) acquired the most followed
by Microsoft (9), Facebook (9) and Apple (6). Exhibit 8 shows the breakdown of deal volume by
industry while Exhibit 9 shows the break down by consumer facing (B2C) vs. enterprise facing
(B2B). By industry, Consumer Media and Entertainment companies were the highest share of
23
Bruce Upbin, “Facebook Buys Instagram For $1 Billion. Smart Arbitrage.” http://www.forbes.com/sites/bruceupb
in/2012/04/09/facebook-buys-instagram-for-1-billion-wheres-the-revenue/, Forbes, (April 9, 2012).
24
Craig Smith, “April 2014 by the Numbers: 70 Interesting Instagram Statistics,” http://expandedramblings.com/ind
ex.php/important-instagram-stats/#.U12x71ca2qU, DMR, (March 6, 2014).

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startups being acquired at 33% followed closely by Cloud Platforms and Data Organization
companies with 28% share. B2C companies represented 60% of the acquisition deal volume as
opposed to 40% for B2B companies.
The total amount paid for these 40 companies was $56.9 billion. The average premium
paid was $1.4 billion, but this was skewed by a few outliers (standard deviation of $3.5 billion).
The median, a far better measure of central tendency in this case, was $108.3 million. The
minimum transaction price paid since 2011 was Facebook’s acquisition of Little Eye Software
for $14.5 million in Q1 of 2014, while the maximum paid was Facebook’s acquisition of
WhatsApp for $16.4 billion (also in Q1 of 2014).
Exhibit10 shows the breakdown of premiums paid by 5 different price ranges. As seen in
the exhibit, 61% of the startups acquired by the four large tech firms were acquired for less than
$150 million and only 10% were acquired for more than $5 billion. The four companies acquired
for more than $5 billion were: WhatsApp (Facebook), Motorola (Google), Skype (Microsoft) and
Nokia’s phone business (Microsoft). These four were joined by Instagram (Facebook), Oculus
VR (Facebook), Yammer (Microsoft), Waze (Google) and Nest Labs (Google) in the billion
dollar club. Notably, Apple has not spent more than $400 million in a single transaction since Q1
of 2011 (it did so on its acquisition of Anobit Technologies.)
By industry, as shown in Exhibit 11, the largest average premiums paid were for
companies in the Consumer Media and Entertainment and Hardware and Devices categories.
These high averages were a result of a number of high profile acquisitions in these categories
(for example: Facebook’s acquisition of WhatsApp and Google’s acquisition of Motorola.) A
final observation worth noting, and as seen in Exhibit 12, is that the average premium paid for

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B2C companies was nearly 10x the average amount paid for B2B companies: $2.2 billion vs.
$210.5 million.
The econometric tools employed (i.e. linear regression) yielded notable findings. The first
regression looked at the effects of all seven of the M&A motivation variables outlined above on
the premium paid by the acquiring firm. The regression results, including the equation, variables
and measures of statistical significance are displayed below in Exhibit 13 (the full regression
output is included in Exhibit 14):
Exhibit 13: Regression Results of M&A Motivation Variables
Premium Paid = -$5,500 + $2,950(β1) + $324(β2) + $3,780(β3) + $109(β4) + $2,168(β5) + $4,193(β6) + $1301(β7)
Regression Variable M&A Motivation Variable Coefficients P-value
β0 Intercept -5,499.905383 0.00107
β1 Economies of Scale 2,950.104683 0.0179
β2 Greater Pricing Power 324.1651438 0.71664
β3 Value Chain Integration 3,779.654943 0.0037
β4 Enhance Core Capabilities 108.9788665 0.90296
β5 Growth in New and Existing Markets 2,167.603976 0.03084
β6 Large Network Effects 4,193.220288 0.0006
β7 Steep Switching Costs 1,301.206602 0.13808
*Shaded Rows represent statistically significant variables.
There are several characteristics of the regression worth pointing out. First, the intercept
(β0) is negative, which limits the full application of the regression equation. This is likely due to
a small sample size and data that is not normally distributed. Because of this negative intercept,
we cannot make a direct dollar connection between each M&A motivation variable and the
premium paid by the acquiring firm. That being said, we can make some relative observations
based on the size of each beta coefficient.
Additionally we can make some important observations regarding statistical significance.
As seen in the exhibit above the four M&A motivation variables that were statistically significant
include: economies of scale, value chain integration, growth in new and existing markets and

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large network effects. The remaining three variables are not statistically significant according to
our model. Re-running the regression on the four statistically significant variables we get the
results displayed below in Exhibit 15 (full regression output can be found in Exhibit 16):
Exhibit 15: Regression Results of Statistically Significant M&A Motivation Variables
Premium Paid = -$4,547 + $2,649(β1) + $3,649(β2) + $2,105(β3) + $4,228(β4)
Regression Variable M&A Motivation Variable Coefficients P-value
β0 Intercept -4,546.658515 0.00062
β1 Economies of Scale 2,648.970749 0.027376
β2 Value Chain Integration 3,648.626285 0.004524
β3 Growth in New and Existing Markets 2,104.69961 0.017684
β4 Large Network Effects 4,228.180754 0.000483
The regression equation above shows us the relative values large tech firms place on various
M&A motivation variables. The results can be broadly bucketed into B2C variables and B2B
variables—although there is certainly some overlap.
On the B2C front, unsurprisingly, tech firms like Apple, Facebook, Google and Microsoft
place the largest premiums on startups with large network effects. Acquiring companies like
Instagram, WhatsApp and Skype allows these firms to essentially acquire a massive customer
base with a large customer life-time value. Because of the large network effects, these customers
are unlikely to switch to substitutes. Big tech firms can then monetize these acquired customers
over a long period of time as well as cross-sell products and services on their existing platforms.
According to our regression output, these big tech firms also place an important (though
not nearly as large) premium on B2C companies that allow them to grow in new and existing
markets. B2C companies like Snaptu (a mobile platform for feature phones in developing nations
acquired for $70 million) and Oculus VR (a virtual reality and gaming device company acquired
for $2.3 billion) allow big companies like Facebook to enter new markets—whether geographic,
customer-segment specific or newly emerging industries.

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When it comes to B2B acquisitions, the M&A model provides evidence that large tech
companies place a heavy premium on value chain integration and economies of scale—both
means to maintain a competitive advantage. Apple’s acquisition of semiconductor company
Anobit Technologies for $400 million is a great example of value chain integration. Apple has
slowly been moving away from hard drives to flash memory beginning with the iPod and most
recently its MacBook Air. Flash memory allows Apple’s products to be thinner and run on less
power. Acquiring Anobit allowed the firm to acquire the hardware component needed to
complete value chain integration and transition fully from hard drives to flash memory chips.
Though not as important as value chain integration from a relative perspective, large tech
companies also consider economies of scale when acquiring B2B companies. Within that realm,
companies that provide a service or toolkit that enable a bigger tech company to take advantage
of scale economies are also often worth acquiring. Microsoft’s acquisition of Pando, a file-
sharing technology that works peer-to-peer like bit-torrent, is a great example of this. Pando’s
technology can be applied to Microsoft products like Xbox and Windows Phone App Store, to
reduce costs in these divisions and enable Microsoft to take advantage of its economies of scale.
Implications for VCs
The implications of the findings in this paper are critical to venture investors and can be
used to make high potential investments in early stage startups with the end goal of an M&A
exit. The first thing venture investors must realize is that we are currently in a very “frothy”
market environment—both on the M&A front and on the venture investing front. Acquisitions
and venture deals are at post-financial crisis highs in terms of volume and size. On the venture
side, seed investing has particularly accelerated in the last few years. While optimism is

17
abundant in the venture community, it is critical to understand that business cycles ebb and
flow—the current environment will not last indefinitely.
But while the current environment continues to last, now is an ideal time for VCs to start
a venture firm or raise a new fund. Not only is optimism high among the limited partners (those
who invest in VCs) pouring money into the venture community, the SEC is also making it easier
for firms to solicit funds from the general public through the JOBS Act. There is a particularly
high level of outside interest in early stage investing on both the B2C and B2B ends of the
spectrum.
VCs should likewise realize that they can be successful investing in either B2B or B2C
companies, though they ought to adopt different strategies for each group. With B2C companies,
venture investors should realize that there is a greater likelihood of a billion dollar exit (as
opposed to B2B companies). That being said, while there are more billion dollar B2C exits, the
average venture-backed exit is just slightly north of $100 million. In order to achieve successful
B2C M&A exits, VCs should focus on companies that are building products with large network
effects or that have witnessed significant growth in new and existing markets. In particular, they
should focus on Consumer Media and Entertainment and/or Cloud Platforms and Data
Organization companies.
Venture investors investing in B2B companies should understand that the exit prices of
this group are on average lower (as compared to B2C companies), but that these prices are also
more consistent. VCs focused on enterprise companies should focus on finding gaps in large tech
firms whereby the acquisition of a startup would provide the acquiring firm the ability to take
advantage of economies of scale or integrate along the value chain in an advantageous way.

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Regardless of whether focused on investing in consumer facing or enterprise facing
startups, VCs targeting an M&A exit should invest based on four trends that major tech firm are
reacting to. First, big data is everywhere and can be mined, analyzed and applied across every
industry. Second, wearable technology is an important platform providing an even greater
extension of mobility than the phone. Third, the world is moving from the desktop to the cloud,
creating a need for tools to work, store and build in this cloud computing environment. Fourth, as
we move to the cloud, a new layer of security will be needed to protect against cyber-attack.
To conclude, it is an exciting time to be an early stage venture investor. Despite the
challenges and risks involved in the business, there is certainly much potential to achieve a high
level of success. Focusing on the M&A activity of the largest tech firms is a great way to begin
building toward that success.

19
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http://te chcrunch.com/2014/02/19/facebooks-19-billion-whatsapp-acquisition-contextualized/.
TechCrunch. (February 19, 2014).
Aswath Damodaran. The Value of Synergy. NYU Stern School of Business, October
2005, 4-5.
Frensch, Florian. The Social Side of Mergers and Acquisitions. (Berlin: DUV, 2007). 25-
27.
Garbade, Michael. International Mergers & Acquisitions, Cooperations and Networks in
the e-Business Industry. (Mannheim: GRIN, 2007). 5-7.
Glasner, Joanna. “Top Venture Capital Trends in 2013.” http://www.pehub.com/2014/01/
top-venture-capital-trends-in-2013/. Reuters PE Hub. (January 3, 2014).
“Global M&A Report Technology-Media-Telecom Sectors,” BDO, February 2014, 2-6.
High, Peter. “2013 Global Tech, Media, And Telecom M&A Up Over 50% From 2012.”
http://www.forbes.com/sites/peterhigh/2014/01/20/2013-global-tech-media-and-telecom-ma-up-
over-50-from-2012/. Forbes, (January 20th
2014).
Lawler, Ryan. “Sequoia’s A Big Winner In Facebook’s WhatsApp Acquisition, With Its
Stake Worth About $3 Billion.” http://techcrunch.com/2014/02/19/sequoia-and-jim-goetz-are-
big-winners-in-facebooks-whatsapp-acquisition/. TechCrunch. (February 19, 2014).
“WhatsApp.” TechCrunch. http://www.crunchbase.com/company/whatsapp.

20
Appendix
Exhibit 1
Global TMT Transaction Volume (2011-2013)
Source: BDO Paper (Global TMT M&A Report)
Exhibit 2
Number of Transactions by Sector within TMT (2011-2013)
Source: BDO Paper (Global TMT M&A Report)

21
Exhibit 3
Quarterly VC Deals (2011-2013)
Source: CB Insights
Exhibit 4
Quarterly VC Seed Deals (2010-2013)
Source: CB Insights

22
Exhibit 5
Summary of M&A Rationale by Author
Author Reason for M&A Transaction
Buhner (1990):
295
 Market power, especially for horizontal mergers
 Information advantage, which allows the recognition of
undervalued companies
 Synergies, which allow an increase of performance
 Inefficient management of the acquisition target
 Financial benefits through tax advantages or lower cost of
capital through risk diversification
 Management interest such as prestige, power and
recognition
 Hubris of the top management
 Free cash flows
Bamberger
(1994)
 General Acquisition Motives
o Growth
o Capacity increase
o Risk Diversification
 Specific Acquisition Motives
o Time advantage compared to internal investment
projects
o Acquisition of specific, non-tradable resources
o The acquisition target is undervalued and an
opportunity
 Miscellaneous acquisition motives
o Motives of individuals, such as top manager hubris
Hayward &
Hambrick
(1997)
 Synergies
 Poor past performance of the management team of the
target
 Hubris of the CEO of the acquiring firm
Koegeler (1991)  Risk diversification
 Stagnation of markets
 Usage of cash resources to further diversify rather than
consolidate
 Top-management desire for further growth
 Realization of synergies
Source: The Social Side of Mergers and Acquisitions

23
Exhibit 6
M&A Model: Data Collected
Source: Created by Author
Company Type
B2B
B2C
Industry Category
Consumer Media &
Entertainment
Ecommerce & Financial
Services
Cloud Platforms & Data
Organization
Hardware & Devices
Advertising & Marketing
M&A Motivational
Variable
Enhance Core Capabilities
Greater Pricing Power
Steep Switching Costs
Large Network Effects
Growth in New and
Existing Markets
Economies of Scale
Value Chain Integration

24
Exhibit 7
Exhibit 8
15%
8%
33%
28%
18%
Acquisitions by Industry (2011-2013)
Advertising & Marketing
Ecommerce & Financial
Services
Consumer Media &
Entertainment
Cloud Platforms & Data
Organization
Hardware & Devices
40%
60%
Acquisitions: B2B vs. B2C (2011-2013)
B2B
B2C

25
Exhibit 9
0
2
4
6
8
10
12
14
$0-$50 $50.01-$150 $150.01-$500 $500.01-$5,000 Greater than
$5,000
Number of Companies in each "Premiums
Paid" Range (in $mm)

26
Exhibit 10
Exhibit 11
$129.19 $89.00 $197.17
$2,169.42
$3,650.42
$0.00
$500.00
$1,000.00
$1,500.00
$2,000.00
$2,500.00
$3,000.00
$3,500.00
$4,000.00
Advertising &
Marketing
Ecommerce &
Financial Services
Cloud Platforms
& Data
Organization
Consumer Media
& Entertainment
Hardware &
Devices
Average Premiums Paid by Industry (in $mm)
$210.53
$2,233.25
$0.00
$500.00
$1,000.00
$1,500.00
$2,000.00
$2,500.00
B2B B2C
Average Premiums Paid: B2B vs. B2C (in $mm)

27
Exhibit 12
Regression Using all M&A Motivation Variables
Regression Statistics
Multiple R 0.773564202
R Square 0.598401574
Adjusted R Square 0.510551918
Standard Error 2480.386638
Observations 40
ANOVA
df SS MS F
Regression 7 293352281.2 41907469 6.811655314
Residual 32 196874172 6152318
Total 39 490226453.2
Coefficients
Standard
Error t Stat P-value
Intercept -5499.90538 1528.498364 -3.59824 0.001066473
*Economies of Scale 2950.104683 1181.852584 2.49617 0.017898047
Greater Pricing Power 324.1651438 885.2725605 0.366176 0.716643989
*Value Chain Integration 3779.654943 1207.076666 3.131247 0.00370477
Enhance Core Capabilities 108.9788665 886.8077375 0.122889 0.902963623
*Growth in New and Existing Markets 2167.603976 959.6169174 2.258822 0.030842904
*Large Network Effects 4193.220288 1100.721788 3.809519 0.000596206
Steep Switching Costs 1301.206602 855.4825992 1.521021 0.138075561
*Indicates statistical significance.

28
Exhibit 13
Regression Using all Statistically Significant M&A Motivation Variables
Regression Statistics
Multiple R 0.749243073
R Square 0.561365183
Adjusted R Square 0.511235489
Standard Error 2478.653959
Observations 40
ANOVA
df SS MS F
Regression 4 275196062.4 68799016 11.19825685
Residual 35 215030390.7 6143725
Total 39 490226453.2
Coefficients
Standard
Error t Stat P-value
Intercept -4546.65851 1209.018873 -3.76062 0.000620209
Economies of Scale 2648.970749 1150.514901 2.302422 0.027376032
Value Chain Integration 3648.626285 1202.422783 3.034396 0.004524044
Growth in New and Existing Markets 2104.69961 845.3624606 2.489701 0.017684409
Large Network Effects 4228.180754 1098.739855 3.848209 0.000483176

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