Sequoia Capital
Social Media Metric Analysis
// about
As part of a contract engagement with Sequoia's early-stage scouting division, I led a data-driven initiative to identify promising startups using real-time social media insights from platforms like Instagram and Twitter.
The mission was clear: turn noisy, unstructured social data into targeted investment signals that could support strategic decisions — helping Sequoia stay ahead of market trends and founder activity.
// process
Data Sourcing & Structuring
Collaborated with Sequoia's internal data team to refine and structure scraped social media data, ensuring accuracy, recency, and contextual relevance for trend tracking.
Startup Signal Mapping
Designed a framework to track startup activity levels, engagement patterns, and audience traction to distinguish between noise and meaningful traction.
Use Case Development
Built a series of targeted scouting use cases based on company growth markers, enabling more informed outreach and portfolio filtering.
Actionable Insight Delivery
Translated raw data into digestible reports and dashboards, arming the investment team with clear insights on which startups were gaining ground and why.
// achievements
This work enabled Sequoia to move with greater speed and precision in the early-stage ecosystem — identifying high-potential startups before they appeared on conventional VC radars.