Auckland and Sydney based market research start-up Ideally has raised $16 million at $100m valuation in a Series A round. Founded by James Donald, Joshua Nuu-Steele and Brendan Cervin, Ideally is targeting a long-standing inefficiency in the research industry: the time and cost required to generate actionable insight.
Investors
led by Shearwater Capital, with participation from OIF Ventures, Altered Capital, Icehouse Ventures and Ecliptic VC, as investors increase their exposure to platforms reshaping how companies understand customers.
OIF Ventures, an early backer of Ideally, has maintained its support through the latest round, underscoring conviction in the company’s trajectory and category positioning. The broader syndicate — spanning Australia, New Zealand and global investors — points to ambitions beyond the domestic market.
Investors are effectively backing the emergence of what some describe as “insight infrastructure”: software that embeds customer understanding directly into daily workflows, rather than treating it as a periodic function.
The problem it Solves
Traditional research processes can take months and cost six-figure sums, typically delivered through external agencies and static reporting. Ideally’s proposition is to collapse that cycle into a continuous, on-demand workflow, enabling teams to test ideas, validate creative and gather feedback in near real time.
Customers
The company has gained traction across more than 250 brands in Asia-Pacific and the United States, embedding its platform across product, marketing and commercial functions.
Among its customers, Treasury Wine Estates has used the platform to reduce product development timelines from six months to under 90 days by incorporating consumer feedback earlier in the process. Burger King is testing limited-time menu items prior to launch, while Google is applying the tool to link user insight more directly to creative development.
Where to from here?
The investment reflects a broader shift within corporates towards faster, more iterative decision-making as product cycles shorten and competitive pressure increases. Platforms that enable continuous feedback are beginning to displace traditional, episodic research models.
For Ideally, the next phase will focus on scaling enterprise adoption and deepening integration across decision-making processes. The company is aiming to become a default layer in how organisations test, learn and iterate.
If successful, the shift would mark a departure from traditional research models towards a system where insight is continuously generated and immediately applied — reshaping how companies bring products to market and manage risk.
