Newton Research

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Newton Research builds a team of marketing analytics agents that do the work a data science team would, without moving your data. Founded by repeat entrepreneurs whose founding team carries more than seventy years of combined marketing analytics and data science experience, the company raised a nine million dollar Series A in 2025 led by Greycroft with Bessemer Venture Partners. Led by chief executive John Hoctor, Newton set out to make sophisticated marketing measurement, once limited to the largest enterprises, affordable and accessible to brands, agencies, publishers, and platforms. The core idea is that agents work alongside analysts natively inside a company's own data environment, with no movement or leakage of sensitive data. Newton's agents take real action on your behalf, writing code, executing analyses, and pushing audiences, budget allocation changes, and optimized bid lists directly to the relevant platforms and tools. A typical user is reported to save around one hundred twenty six hours a month by handing repetitive analytics off to Newton, freeing time for higher value work while a person keeps judgment and creativity in the loop. New customers start with a team of specially trained expert agents that arrive pre loaded with a curated marketing science playbook. That playbook shows up as blueprints, push button flows that let non technical users run common marketing analytics use cases on their own data, from audience analysis and channel optimization to incrementality testing, marketing mix modeling, and attribution. Teams that want to go further can build and iterate on their own optimization and measurement in a no code interface, or spin up a fully custom agent in days rather than months. Transparency is a deliberate design choice. Newton gives full visibility into the code and processes its agents execute, so analysts can see and trust every model and analysis rather than taking a black box on faith, and the agents are regularly tested against more than a hundred and ten marketing analytics questions to hold accuracy. Insights come back through natural language and refresh in minutes, and the whole capability can be white labeled into a platform's own interface for its customers.