Third Point Ventures

Type

Venture Capital

Status

Active

Location

New York, United States

Total investments

108

Average round size

176M

Portfolio companies

72

Rounds per year

3.86

Lead investments

26

Follow on index

0.33

Exits

22

Stages of investment
Early Stage VentureLate Stage Venture
Areas of investment
InternetSoftwareFinancial ServicesFinTechInformation TechnologyArtificial IntelligenceMachine LearningHealth CareEnterprise SoftwareCloud Data Services

Summary

Third Point Ventures is the famous VC, which was founded in 1995. The venture was found in North America in United States. The leading representative office of defined VC is situated in the New York.

Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. The fund has no specific favorite in a number of founders of portfolio startups. When startup sums 4 or 5+ of the founder, the probability for it to get the investment is little. Among the most popular portfolio startups of the fund, we may highlight Lyft, Social Finance (SoFi), ContextLogic (dba. Wish). For fund there is a match between the location of its establishment and the land of its numerous investments - United States. Among the most popular fund investment industries, there are Financial Services, Health Care.

The typical case for the fund is to invest in rounds with 5-6 participants. Despite the Third Point Ventures, startups are often financed by Mayfield Fund, Aperture Venture Partners, Founders Fund. The meaningful sponsors for the fund in investment in the same round are Bay Partners, Aperture Venture Partners, Pelion Venture Partners. In the next rounds fund is usually obtained by Sapphire Ventures, Rakuten, Didi Chuxing.

The fund was created by Daniel S. Loeb. We also calculated 9 valuable employees in our database.

Opposing the other organizations, this Third Point Ventures works on 5 percentage points less the average amount of lead investments. Deals in the range of 50 - 100 millions dollars are the general things for fund. The real fund results show that this VC is 28 percentage points more often commits exit comparing to other companies. The high activity for fund was in 2015. Despite it in 2019 the fund had an activity. The typical startup value when the investment from Third Point Ventures is more than 1 billion dollars. The fund is constantly included in 2-6 deals per year. The top amount of exits for fund were in 2015.

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Investor highlights

Industry generalist
Yes
Industry focus
GeneralistConsumer/RetailBlockchain/Crypto/Web3CybersecurityAI/Big Data Show 10 more
Stage focus
GeneralistPre-SeedSeedSeries ASeries B Show 3 more

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Investments analytics

Analytics

Total investments
108
Lead investments
26
Exits
22
Rounds per year
3.86
Follow on index
0.33
Investments by industry
  • Software (29)
  • Information Technology (21)
  • Artificial Intelligence (18)
  • Financial Services (17)
  • FinTech (16)
  • Show 127 more
Investments by region
  • United States (94)
  • Singapore (1)
  • Switzerland (5)
  • Germany (1)
  • Colombia (1)
  • Show 3 more
Peak activity year
2021
Number of Unicorns
11
Number of Decacorns
16
Number of Minotaurs
10

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Quantitative data

Avg. startup age at the time of investment
11
Avg. valuation at time of investment
1B
Group Appearance index
0.93
Avg. company exit year
6
Avg. multiplicator
2.97
Strategy success index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
CloudVelox 12 Feb 2015 Software, Enterprise Software, Cloud Data Services, Data Integration Late Stage Venture 15M United States, California, San Jose
Grip Security 22 Aug 2023 Early Stage Venture 41M Tel Aviv District, Tel Aviv-Yafo, Israel
Sailo 15 Jan 2018 E-Commerce, Peer to Peer, Marketplace, Travel Seed 1M United States, New York

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By same location

By same geo focus

By doing lead investments

How we get our data

At Unicorn Nest, we combine cutting-edge technology with human expertise to build one of the most reliable venture capital databases in the market. Our process begins with automated AI-enhanced data collection, leveraging the full potential of Large Language Models (LLMs).

Later, our team of analysts takes it further with manual verification, using proprietary tools for data cleaning and validation to ensure accuracy and reliability. We cross-check and enhance our findings through press and media monitoring, integrating information from trusted news outlets and venture capital aggregators. Finally, we stay ahead of the curve by monitoring social networks like LinkedIn and X.com.