European start-ups are being created and growing at
an unprecedented pace these days, attracting the attention of global
investors, customers, and corporate partners alike. In the process, they
are proving the conventional wisdom wrong: launching a start-up amid
the continent’s fragmented value pool doesn’t necessarily have to be
such a challenging proposition.
Despite the range of systemic challenges start-ups still face ,
including regulatory and cultural challenges, growing numbers of
dynamic new ventures are thriving. These bold players offer valuable
lessons for others aspiring to similar heights—and to a European
continent striving to stay economically and technologically competitive
with the rest of the world.
To better understand how these standouts succeed, we studied the top
1,000 European tech start-ups founded after 2000 in 33 countries, which
include 21st-century companies such as Spotify, Adyen, and BioNTech. We
analyzed them along 15 critical growth dimensions and variables such as
geography and vertical, as well as on the requirements for the time,
funding, and revenues it takes to reach unicorn status (see Exhibits 1
and 2; also see the sidebar, “About our research”). Three key insights
emerged from our analysis:
Successful European tech start-ups follow one of four distinct roads to success:
network, scale, product, or deep tech, each with its own
characteristics regarding revenue growth, employees, and other similar
markers.
Different strategic plays require different success factors,
such as overindexing on commercial roles for scale players, focusing on
an initial product hook for product players, or pursuing M&A
activities for scale and network players.
Reaching unicorn status requires on average €100 million to €200 million in funding, with 70 to 80 percent of the companies that make it achieving the €1 billion valuation mark within ten years of founding.
Exhibit 1
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Exhibit 2
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Four winning strategic plays
Our research on the top 1,000 European tech start-ups showed that
these companies follow one of a small number of distinct paths to
successful scaling, built around a core strategic approach: network,
scale, product, or deep tech. While these categories are not mutually
exclusive, each of them provides a path to scale. We believe this
classification provides practical utility for entrepreneurs, executives,
and investors as they launch and attempt to scale ventures (Exhibit 3).
Exhibit 3
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By assessing themselves with regard to these strategic plays,
European start-ups and scale-ups (and their investors) can spend less
time and effort trying to figure out what they do best or how to do it
on a wider stage and instead make better, faster decisions and focus
resources for the greatest effect. Yet, knowing what strategic approach
to embrace is only part of the equation. It is also critical to know
what tactical moves tend to lead to success for each of the different
strategic plays (Exhibit 4).
Exhibit 4
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Our analysis suggests a range of five such critical factors are at
work. For network players, it’s crucial to win local markets one by one
and not try to grow globally in one fell swoop. Scale plays need to
overindex on building strong commercial capabilities. Both network and
scale players benefit from M&A. Product-play companies need to
prioritize a compelling product and narrow use case initially, while for
deep-tech plays, attracting the best research and development talent is
most important.
Winning markets one by one: Network plays
These types of companies tend to be marketplace, mobility, and
social-media start-ups, such as Delivery Hero (online food delivery) and
Tier (micromobility). They require an addressable market that is
concentrated in a relatively small geographical area such as a city—a
“hyperlocal” market. Because languages, cultures, and governments vary
so widely among European cities, successful network-play start-ups enter
these markets one by one, adapting their go-to-market strategy as they
proceed, rather than all at once with a global approach as might be
possible in a region with more uniform characteristics between cities.
This effect of winning market by market is visible in the experiences
of shared e-scooter players, which operate in cities where there is
really only room for a few competitors, and first movers do not always
win. In numerous European cities, local competitors Tier and Voi have
taken the lead over Lime despite its early start (Exhibit 5). For
example, in Berlin, Lime was able to provide the largest e-scooter fleet
when entering the market in 2019, with its unmatched global scale. A
year later, however, Tier is leading the key market with an estimated
share (based on Google search interest) of 34 percent, beating Lime (28
percent). So, adapting go-to-market strategies to each new city is
critical not only to winning at the outset but also to maintaining a
winning position. For its part, Tier has found success by winning
contracts with local governments and other local public-transport
companies to offer e-scooter services.
Exhibit 5
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That focus can still be costly. To subsidize early usage across a
local market, network-focused companies require the highest funding of
all plays, with an average funding since founding of €243 million
compared with €164 million for all of the top 1,000 companies we
analyzed.
Overindexing on commercial roles: Scale plays
Start-ups pursuing scale plays seek to win through rapid sales growth
early on, relying on initial commercial success to create the economies
of scale they need to dominate a market.
To achieve this early commercial success, outperforming scale
start-ups invest more heavily in sales, marketing, and
business-development roles. On average, these positions account for 42
percent of all employees, compared with about 33 percent for the other
strategic plays. To support sales, they have a stronger focus on
operational roles (17 percent) compared with product (9 percent) and
deep-tech plays (14 percent).
Overall, successful scale players tend to have the most
employees—almost twice as many as product players and even three times
as many as successful deep-tech players (Exhibit 6). At the same time,
scale players typically focus less on product roles (28 percent)
compared with about 40 percent for the other strategic plays. This is a
reflection of the fact that success is generally achieved more through
sales than through product differentiation.
Exhibit 6
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The companies that pursue this play are frequently e-commerce,
consumer, or media companies, such as Spotify (music and other audio)
and Zalando (fashion and lifestyle). This is confirmed in scale-play
companies’ average revenue since founding, which is the highest with
€826 million compared with €277 million for companies in the top 1,000
companies we analyzed.
As scale companies mature, the relative size of their commercial
functions decreases, resulting in the increased importance of other
roles, particularly product and tech roles. In our sample of start-ups
that are less than five years old, the share of commercial functions is
43 percent on average, which drops to 39 percent for start-ups that are
six to ten years old, and 34 percent for older start-ups. A closer look
at five of the most valuable European scale players (Farfetch,
HelloFresh, Spotify, The Hut Group, and Zalando) shows this transition
into product and tech roles: having matured to a degree, these scale
players now have about 35 percent of their employees in commercial
positions.
Expanding and consolidating with M&A: Network and scale plays
Companies pursuing either a network play or a scale play often rely
more heavily on M&A to expand into new regions and consolidate
markets, rather than launching in new markets on their own. This
approach is especially effective for European start-ups, which need to
enter more markets in more countries to attain an addressable market
that is sizeable enough.
Network- and scale-play start-ups conduct between 1.6 and 1.9 deals
across all funding rounds, which is twice as many as the average in our
sample (Exhibit 7). By contrast, M&A activity among ventures
pursuing a product play is below the average across the group, at 0.7
deals, and most start-ups going for a deep-tech play are unlikely to
engage in M&A at all.
Exhibit 7
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M&A provides the opportunity to accelerate growth and can entail
arbitrage effects when a large successful start-up acquires a smaller
start-up valued at a lower multiple. On the other hand, heavy M&A
activity can turn out to be a costly distraction, especially for
early-stage start-ups, effectively slowing their organic growth. In
deciding how intensively to pursue M&A, the start-ups we studied
consider organizational capacity and resources to integrate the acquired
company.
Starting with a stellar offering and a narrow use case: Product plays
Successful product players start with an outstanding product in a
narrow use case before moving to a full-suite offering. Getting the
product (and market fit) right early on is more important to these kinds
of start-ups, and so their product and tech roles—R&D, engineering,
product management, and IT, for example—have greater importance. At the
same time, their focus on commercial and operational roles is much
lower than for the other strategic plays. Product players are usually
B2B software-as-a-service (SaaS) providers or fintechs such as Personio
(HR software) and N26 (neobanking). We found that product players
require the least amount of funding, with €145 million in funding
compared with €164 million on average for all of the companies we
analyzed. They are also dominant in Europe, occupying about 45 percent
of the region’s top 1,000 tech start-ups.
These companies’ emphasis on product excellence is also visible in
Apple App Store ratings. Among a subset of companies whose apps are
critical to the product experience, almost 35 percent of product-play
companies have developed a top-rated app, as compared with an average of
around 30 percent for other plays. Product quality is also more closely
associated with growth for product plays—product-play companies with an
outstanding App Store rating grow 27 percent faster than their
counterparts with lower-rated apps.
With relatively limited resources initially, product-play start-ups
focus intensely on both reaching adoption fast and providing a strong
customer experience. To help achieve this, they often develop their
initial product for a select, well-defined use case. This drives early
usage as well as the collection of detailed customer feedback, which is
essential for further product development and scaling-up to a larger
customer base. For example, N26, the German neobank, focused on adoption
early, offering only basic banking products such as current accounts
and credit cards. Only later did the company expand its offering to
adjacent categories. After attaining scale, it subsequently moved to
higher-margin products, such as lending and investing. At that point,
N26 was ready to explore partnerships with other fintechs, which helped
to open up cross-sell opportunities.
Winning with top research talent: Deep-tech plays
Deep-tech players tend to work on AI, hardware, biotech, or
healthcare, and so they focus longer and more intensively on exploratory
research and development than companies pursuing other strategic plays.
Lilium (electric air-mobility service) and Graphcore (accelerators for
AI and machine learning) are examples. The companies in this group are
characterized by a relatively low number of employees, with 211
employees on average, as compared with an average of 488 employees for
the companies we analyzed. As expected, they have the highest (46
percent) share of employees in R&D roles; by comparison,
product-play companies have 38 percent of employees in such roles, and
the percentage is closer to 30 and 28 percent for network and scale
plays, respectively. As a result, they receive on average 1.87 patents
per year, significantly higher than product-play companies (0.19 patents
per year), scale-play companies (0.21 patents per year), and
network-play companies (0 patents per year).
One important way leading deep-tech start-ups separate themselves
from the rest of the pack is by hiring the top research talent in
Europe. On average, 27 percent of their hires come from the top 100
international universities, which is 51 percent above the average in our
sample group (Exhibit 8).
Valuations also correlate to the quantity and caliber of the R&D
team. In comparing deep-tech companies with similar funding, those with a
higher share of top-tier researchers achieve 43 percent higher
valuations than others (Exhibit 9).
Exhibit 8
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Exhibit 9
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Companies pursuing a deep-tech play require more extensive funding
long before they become winners. As such, they need investors that have a
similar long-term vision and willingness to fund a long R&D phase.
For example, Lilium, which is developing vertical take-off and landing
personal aircraft, has managed to attract large investment years before
reaching commercialization.
What it takes to build a European tech unicorn
In our analysis of the most successful European tech start-ups, we
looked at the amount of time, funding, and revenues required to build a
unicorn across each of the four strategic plays (Exhibits 10 and 11).
Exhibit 10
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Exhibit 11
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Time required. Most of the companies we
studied reached unicorn status within ten years of founding. Network and
deep-tech players especially tend to reach unicorn status early, while
significant shares of scale players (24 percent) and product players (31
percent) take more than ten years.
Funding required. To reach a valuation of
€1 billion, these companies, on average, required €100 million to €200
million in funding, implying a valuation of five to ten times the
capital raised. However, this figure differs quite significantly among
the strategic plays. Network and deep-tech players required the highest
funding amount, approximately €200 million, to reach a valuation of four
to six times the capital raised. Scale and product players required
lower funding (approximately €80 million for scale players and €160
million for product players) to reach a valuation of ten to 12 times and
five to seven times the capital raised, respectively.
Revenue required. We found a wide
difference in typical revenue levels among the companies pursuing
different strategic plays and reaching unicorn status. Scale players
achieved approximately €200 million in revenue, implying a revenue
multiple of four to six times their funding, followed by network and
product plays, with approximately €50 million to €90 million in revenue
at multiples of ten to 20 times funding. Deep-tech unicorns are the main
outlier with typical revenue levels at about €8 million, implying a
revenue multiple of 100 to 150 times, reflecting the massive promise of
future revenue included in deep-tech valuations.
European start-ups and scale-ups and their investors can use these
findings to assess their own approach and identify quicker paths to
success by concentrating their resources on the right targets.
Understanding one’s own product and approach within the context of these
strategic plays and success factors can help organizations and players
across the European start-up ecosystem follow in the footsteps of these
European tech champions.
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