Improving Venture Capital Analysis using Data-Driven Research and Models

Client Background

The clients were investors interested in technology companies and venture capital. They realized there is a need for a data-driven methodology to analyze technology companies and reduce investment risks.

Industry: Investment Management

Location: USA

Engagement: Data and Technology


faster portfolio customization

Problem Statement

Investors need an objective, data-driven methodology to analyze technology companies to make informed investment decisions and reduce risks associated with investing in the space.


  1. Develop a proprietary adoption index that measures and scores the adoption of
  2. technology companies.
  3. Utilize various metrics and factors sourced from different data sources.
  4. Create proprietary investment portfolios, research, and recommendations for various
  5. investment vehicles and accounts.
  6. 4. Implement a technology stack for data analysis, visualization, and API development.


  1. Identified relevant metrics and factors for measuring technology adoption.
  2. Developed a process to consume and clean data from various sources.
  3. Assigned proprietary weights to each metric and factor based on their importance.
  4. Tested the index using backtests and projections.
  5. Used the index to create investment portfolios, research, and recommendations.
  6. Implemented a technology stack for data analysis, visualization, and API development.

Technology Stack


Accelerated Portfolio Customization:

2x faster portfolio customization process, enhancing responsiveness to market changes.

Efficiency Gains in Decision-Making:

Decrease in decision-making time, enabling a quicker response to opportunities.

Enhanced Data Analysis Efficiency:

Boosted the data analysis speed, leading to sharper investment strategies.

Informed Investment Decisions:

Enabled investors to make more informed investment decisions, reducing risks.

Tailored Investment Portfolios:

The creation of tailored investment portfolios, optimized returns for various accounts.

Technology Stack Implementation:

The technology stack used for visualization ensured seamless execution and reliability.