Startup Genome

Our quantitative data infrastructure is the world’s most comprehensive and quality controlled. We study 3.5 million companies across 290+ startup ecosystems, combine data from the three leading venture funding databases and then remove duplicates and clean with an AI engine, machine learning techniques, and a manual review. Additionally, we work with 50+ countries to power and update the data found in our reports and policy consultancy work.

Key Definitions

Ecosystem: We define a startup ecosystem as a shared pool of resources, generally located within a 60-mile (100-kilometer) radius around a center point in a given region, with a few exceptions based on local reality. Resources typically include policymakers, accelerators, incubators, coworking spaces, educational institutions, and funding groups.

Ecosystem Success Factors Model: Our principal analytical tool, this measures different dimensions that support the performance of local startups. We look at multiple factors for our rankings: one measuring actual performance, with other Success Factors associated with performance, each comprising sub-factors and metrics.

Performance: A combination of leading, lagging, and current indicators that capture economic outcomes in a startup ecosystem.
Funding: The level and growth of early-stage funding, looking at both access and quality.
Startup Experience: The depth and diversity of the pool of prior startup experience in an ecosystem.
Talent: Measures the accessibility, quality, and cost of software engineering expertise.

Exit: An exit, in the context of startups, refers to an event in which the founders, investors, or employees of a startup realize a return on their investment by selling their ownership stake in the company. Exits include IPOs, M&A, buyouts, and reverse mergers. Starting from this year’s ranking, we are including buyouts and reverse mergers as valid exit types. We only include the first exit as relevant.

H1/H2: Fiscal periods of half a year, in which January–June is H1 and July–December is H2. Similarly, Q1, Q2, etc. refers to the four fiscal quarters of a year (January–March, April–June, etc.).

Regions: We define global regions based on UN and World Bank Definition and divide all countries into seven regions: Asia, Europe, Latin America, MENA, North America, Oceania, sub-Saharan Africa. For a full list of which ecosystems are included in each region, please see here.

Startup: We define a startup as an innovative or technology-driven company that was founded within the last 10 years and that has technology and/or scalability at the core of its business model. In addition to software, this includes startups active in Deep Tech, such as Robotics, Life Sciences, and more.

Unicorn: A startup that meets our definition and has been valued at more than $1 billion and has not exited.

General Methodology

The Startup Genome quantitative data infrastructure includes data on over 3.5 million companies, 280+ ecosystems, and survey data from more than 10,000 startup executives across the globe. These are the main datasets that make up this data science infrastructure:

Startup Genome proprietary data:
- Interviews with 100+ experts
- 2017–2022 Startup Ecosystem Survey with more than 10,000 participants per year
Crunchbase: global dataset on funding, exits, and locations of startups and investors
Dealroom: global dataset on funding, exits, and locations of startups and investors
PitchBook: private capital market data provider
Local partners (accelerators, incubators, startup hubs, investors):
- list of startups
- list of local exits and funding events
CB Insights: global dataset on unicorns

Data Sources

Primary Data Sources

Startup Genome LLC (2017–2023). StartupGenome.com Database
Dealroom.co BV. (2017–2023). Dealroom.co Database
Crunchbase (2017–2023). Crunchbase.com Database
CB Insights (2019–2023). CBInsights.com Database
PitchBook (2018–2023), a private capital market data provider Database

Secondary Data Sources

Shanghai Rankings
USPTO
WIPO
Clarivate

Cleantech Ranking

Definition

Cleantech or clean technology is an umbrella term which is used to define technologies which optimize the use of natural resources, produce energy from renewable sources, increase efficiency and productivity, generate less waste and cause less environmental pollution.

Cleantech consists of sustainable solutions in the fields of energy, water, transportation, agriculture and manufacturing systems, including advanced material, smart grids, water treatment, and efficient energy storage.

Methodology

The overall global Cleantech ecosystem ranking is a weighted average of the following factor
Scores:

Performance: 25%
Funding: 20%
Startup Experience: 12.5%
Knowledge: 10%
Talent: 7.5%
Focus: 25%

The success factors are weighted by the above percentages to establish the overall rank of each ecosystem. The time frame considered for each factor score is detailed in the ranking details below.

The weights of the factors were determined from research and experience. This method takes into account what is deemed to be of importance in ecosystem mapping and analysis overall and across all ecosystem sizes. We have used our research in the period of 2009-2020 and correlation analysis and modeling work based on linear regression analyses, using factor indexes as independent variables with the performance index as dependent variable.

Adding the actual Performance Index to the ranking formula serves to include the influence of unobserved factors on the performance of an ecosystem.

Performance
Captures the actual leading, current, and lagging indicators of ecosystem performance.

50% number of exits of $50 million+ July 1, 2018 to June 30, 2023
25% number of exits July 1, 2018 to June 30, 2023
25% log of output (number of startups in Cleantech) Jan 1, 2013 to Dec 31, 2022.

Funding
Quantifies funding metrics important to the success of early-stage startups.

90% log of number of early-stage funding deals in time period of July 1, 2018 to June 30, 2023
10% log of number of Series B funding deals in time period of July 1, 2018 to June 30, 2023

Experience
Assesses the talent early-stage startups have access to and the degree of startup experience in an ecosystem.

80% Venture A funding (log of number of historical Series A funding deals), as a proxy for number of teams that raised funds in the ecosystem in time period of July 1, 2013 to June 30, 2023
20% exits (log of number of historical $50 million+ exits), as a proxy for number of scaled teams in the ecosystem in time period of July 1, 2013 to June 30, 2023

Talent
Assesses the talent that relevant startups have access to. For this Factor, we analyzed all subjects included in Shanghai Rankings and matched to the relevant startup sub-sectors to calculate the following metrics:

40% average of TOP score from Shanghai Rankings
30% average of CNCI score from Shanghai Rankings
30% average Quality score from Shanghai Rankings

Knowledge
Quantifies the activity of technology knowledge space by measuring the published innovation.

40% number of patents (log of number of patents related to the sub-sector) Jan 1, 2012 to Dec 31, 2021.
40% Technology Potential, a measure calculated at the technology class level globally and calculated for each ecosystem based on the technologies it produced Jan 1, 2012 to Dec 31, 2021.
10% Share of Cleantech Patents Jan 1, 2012 to Dec 31, 2021
10% Ecosystem Complexity, a measure of the capacity of the ecosystem for producing patents in complex technology classes, calculated by measuring the diversity and commonness of the published patents globally.

Focus
Quantifies the concentration of early startups and the availability of infrastructures to support their mentorship and scaling.

70% share of startups in the sub-sector, shows the concentration of startups in the sub-sector in the time period of Jan 1, 2013 to Dec 31, 2022.
30% number of Cleantech-focused accelerators and Incubators.

Blue Economy Ranking

Definition

The Blue Economy is the sustainable use of ocean resources for economic growth, improved livelihoods, and job creation while preserving the health of the ocean ecosystem. It is a sector that seeks to promote economic growth, social inclusion, and the preservation of livelihoods while at the same time ensuring environmental sustainability of the oceans and coastal areas.
The following sub-verticals are included in the Blue Economy:

Marine Energy: Marine energy (or ocean energy) encompasses wave, tidal stream, tidal range, ocean thermal, ocean current, run-of-river, and salinity, etc., through which energy can be harnessed from oceans. Oceans are the source of enormous untapped energy that is accessible to most coastal countries.

Fisheries: The farming of aquatic organisms including fish, molluscs, crustaceans, and aquatic plants. Farming implies some sort of intervention in the rearing process to enhance production, such as regular stocking, feeding, protection from predators, etc. Farming also implies individual or corporate ownership of the stock being cultivated, the planning, development and operation of aquaculture systems, sites, facilities and practices, and production and transport.

Maritime Transport: Maritime transport refers to a means of transport where goods or people are transported via sea routes. In some cases, maritime transport can encompass pre- and post-shipping activities.

Tourism: Tourism is a growth industry in many coastal communities and is based on the natural and cultural heritage of local communities. There are a number of ocean-based tourism activities, such as sailing, diving, fishing, and whale watching. Growing numbers of tourists are putting greater pressure on the environment, resources, and coastal communities.

Waste Management: Plastic marine litter has the potential to persist in the marine environment for long periods, to travel considerable distances, and to accumulate in habitats far from its point of origin. This makes it a growing transboundary global problem that recognises no national borders and spreads from coasts to open oceans. Companies that develop and scale technologies to get rid of the world’s oceans of plastic fall under this category.

Methodology

The overall Blue Economy global ecosystem ranking is a weighted average of the following factor scores:

Performance: 25%
Funding: 20%
Startup Experience: 12.5%
Knowledge: 10%
Talent: 7.5%
Focus: 15%
Legacy: 10%

Performance
Captures the actual leading, current, and lagging indicators of ecosystem performance.

20% number of exits of $50 million+ July 1, 2018 to June 30, 2023
40% number of exits July 1, 2018 to June 30, 2023
30% log of output (number of startups in the Blue Economy) Jan 1, 2013 to Dec 31, 2022).
10% number of founders/co-founders with an active role in the Blue Economy.

Funding
Quantifies funding metrics important to the success of early-stage startups.

90% log of number of early-stage funding deals July 1, 2018 to June 30, 2023
10% log of number of Series B funding deals July 1, 2018 to June 30, 2023

Experience
Assesses the talent early-stage startups have access to and the degree of startup experience in an ecosystem.

20% Venture A funding (log of number of historical Series A funding deals), as a proxy for number of teams that raised funds in the ecosystem July 1, 2013 to June 30, 2023
20% exits (log of number of historical $50 million+ exits), as a proxy for number of scaled teams in the ecosystem in time period of July 1, 2013 to June 30, 2023
60% startup creation, all time.

40% average of TOP score from Shanghai Rankings
30% average of CNCI score from Shanghai Rankings
30% average Quality score from Shanghai Rankings

Knowledge
Quantifies the activity of technology knowledge space by measuring the published innovation.

35% number of patents (log of number of patents related to the sub-sector) Jan 1, 2012 to Dec 31, 2021.
35% Technology Potential, a measure calculated at the technology class level globally and calculated for each ecosystem based on the technologies it produceds Jan 1, 2012 to Dec 31, 2021.
10% share of Blue Economy patents Jan 1, 2012 to Dec 31, 2021
10% Ecosystem Complexity, a measure of the capacity of the ecosystem for producing patents in complex technology classes, calculated by measuring the diversity and commonness of the published patents globally.
10% number of published research and journal papers related to the Blue Economy Jan 1, 2017–Dec 31, 2021

Focus
Quantifies the concentration of early startups and the availability of infrastructures to support their mentorship and scaling.

70% share of startups in the sub-sector, shows the concentration of startups in the sub-sector in the time period of Jan 1, 2013 to Dec 31, 2022.
30% number of Blue Economy-focused accelerators and incubators.

Legacy
Quantifies the backbone and large companies in the ecosystems, which are important sources of networks, partnerships, and mentorship and attract investor attention.

30% sum of market value for public companies in the Blue Economy.
30% number of employees (employees of Blue Economy public companies related to the sub-sector)
40% number of Blue Economy public companies with more than 250 employees

Methodology

Key Definitions

General Methodology

Data Sources

Primary Data Sources

Secondary Data Sources

Cleantech Ranking

Definition

Methodology

Blue Economy Ranking

Definition

Methodology

References