Electric Twin raises £10m seed to predict customer responses using synthetic audiences
This article covers Electric Twin, a martech startup that has raised £10m in a seed funding round to scale its synthetic audience models that predict customer responses to messaging, product launches and strategy decisions. The funding aims to support the startup's expansion and development of predictive tools for product and marketing teams to test scenarios and accelerate customer insight across multiple markets.
Electric Twin, a martech startup, has raised £10 million in a seed funding round — a £7 million round led by Atomico plus a previously undisclosed £3 million pre-seed — to scale its synthetic audience models that predict customer responses to messaging, product launches and strategy decisions.
Why it matters
Organisations still rely on slow, expensive market research when they need to make time-sensitive choices. Electric Twin’s approach promises faster, repeatable testing of scenarios that could shorten decision cycles for product and marketing teams. For businesses that need near‑real‑time insight across multiple markets, a reliable predictive layer could change how risk and launch decisions are made.
Inside the product
Electric Twin combines real‑world survey data with large language models, social science research and machine learning to generate synthetic audiences. These simulated populations are intended to model how different groups will respond to messaging, products or strategies, allowing companies to test scenarios without running full-scale primary research.
The firm says it has run more than 40,000 evaluations across 155 countries to train its prediction engine. Academic research conducted with Professor Michael Muthukrishna at the London School of Economics is cited as finding the technology delivers insights 10,000 times faster than traditional research methods with 95 per cent accuracy. Customers named in the announcement include News UK and Lebara, which are using the platform to shorten insight turnaround from weeks to seconds.
Who are the investors?
The disclosed seed round was led by Atomico and joined by LocalGlobe, Mercuri and Samos Investments. A group of angel investors also participated, including Marc Andreessen; Cal Henderson, co‑founder and CTO of Slack; Eric Salama, former Kantar CEO; Tom Shinner, COO of Entrepreneur First; and Louis Mosley, Executive Vice President, UK and Europe at Palantir.
The £10 million total combines the £7 million seed and an earlier, previously undisclosed £3 million pre‑seed. Atomico framed the investment as backing a team applying machine learning and social science to an established market research problem.
In the announcement, Ben Blume, Partner at Atomico, said:
Companies are desperate to understand their customers, but still lack the tools to unlock insights cost‑effectively and at scale. Electric Twin is forging a genuinely new path, bringing science and machine learning to the clunky, static world of market research and opening up a new era of deeper, more accurate and far faster insight generation. Their product is already market leading in this rapidly emerging space and will only grow more powerful. Alex and Ben bring unique experience in making critical decisions at scale, and we are proud to partner with them and the team as they continue their rapid growth journey.
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Founder perspective
In the announcement, Alex Cooper, Co‑Founder & CEO at Electric Twin, said:
Electric Twin was born from our experience leading through crisis, where we spotted a common problem: too many decisions had to be made with incomplete information. We wanted to build a solution that allows leaders to understand their audiences better than ever before - to speak to them instantly, ask them anything, and predict how they will behave. This investment will enable us to scale our vision and put synthetic audiences at the heart of business strategies.
The company plans to use the funding to push global expansion and deepen its synthetic audience models, extending the range of scenarios organisations can test.
The bigger picture
Electric Twin sits at the intersection of martech, AI and market research. Its claim of rapid, high‑accuracy predictions responds to growing demand for faster customer insight tools as companies operate across more markets and digital channels. The model also raises questions that buyers and regulators will want answered over time, notably around the limits of synthetic data, transparency of model assumptions and how findings map back to real human behaviour.
The deal also reflects continued interest from martech investors in startups that layer AI on top of traditional research workflows. As UK and European companies look to tighten timeframes for product and marketing decisions, tools that reduce the lag between insight and action may attract further funding and adoption.
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