Johnson Family Trust

Total investments

5

Average round size

6M

Portfolio companies

1

Follow on index

0.80

Areas of investment
Supply Chain ManagementFinTechB2BBlockchainPredictive Analytics

Summary

Among the most popular fund investment industries, there are Predictive Analytics, Marketplace. Among the various public portfolio startups of the fund, we may underline Crowdz Besides, a startup needs to be aged 2-3 years to get the investment from the fund.

The usual cause for the fund is to invest in rounds with 3-4 partakers. Despite the Johnson Family Trust, startups are often financed by Payson Johnston, Techstars, Steven Lee. The meaningful sponsors for the fund in investment in the same round are Payson Johnston, Matt Johnson, WS Investments. In the next rounds fund is usually obtained by Payson Johnston, Matt Johnson, WS Investments.

Deals in the range of 1 - 5 millions dollars are the general things for fund. The fund is constantly included in less than 2 deals per year. The top activity for fund was in 2015. The average startup value when the investment from Johnson Family Trust is 1-5 millions dollars.

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Investments analytics

Analytics

Total investments
5
Lead investments
0
Follow on index
0.80
Investments by industry
  • Supply Chain Management (5)
  • B2B (5)
  • Predictive Analytics (5)
  • FinTech (5)
  • Blockchain (5)
Investments by region
  • United States (5)
Peak activity year
2019

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Quantitative data

Avg. startup age at the time of investment
9
Avg. valuation at time of investment
25M
Group Appearance index
1.00

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Crowdz 25 Jun 2023 Supply Chain Management, FinTech, B2B, Blockchain, Predictive Analytics Early Stage Venture 14M United States, California
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.