Brand tracking platform with survey-driven insights and always-on monitoring
Tracksuit runs a brand measurement platform built on Python, React, and Node.js, backed by Snowflake, dbt, and Databricks for analytics. The hiring mix is heavily tilted toward data (6 roles) and marketing (4), with only 3 engineering open positions — a strong signal the core product is largely built and the company is shifting focus toward go-to-market and survey operations scaling. Active projects reflect this: the engineering roadmap centers on survey engine maturity and internal analytics infrastructure, while go-to-market efforts target paid acquisition, organic search presence, and ABM programs.
Tracksuit provides brand tracking and measurement software for marketing and strategy teams. The platform combines survey data collection with continuous brand monitoring, designed to make brand performance data accessible and actionable at the executive level. Founded in 2021 and headquartered in Auckland, the company operates with 51–200 employees and is actively scaling survey operations and product capabilities. Their tech stack spans modern full-stack tools (React, Node.js, TypeScript) with heavy investment in data infrastructure (Snowflake, dbt, Databricks, BigQuery), indicating a data-centric business model. Hiring is concentrated in Australia and New Zealand.
Tracksuit's stack includes Python, React, Node.js, and TypeScript on the application side, with PostgreSQL and AWS for infrastructure. Analytics and data pipelines run on Snowflake, dbt, Databricks, and BigQuery. They also integrate HubSpot for CRM and Google Analytics 4 for web tracking.
Core projects include building and scaling a survey engine, launching new products, and developing an internal analytics platform. Go-to-market efforts focus on paid acquisition, ABM programs, organic search growth, and website conversion optimization.
Tracksuit's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.