Great Question Raises $13M: The Future of UX Research Software

Great Question, an Oakland-linked UX/customer research platform, has announced a Series A led by Inovia Capital with participation from Y Combinator, January Capital and Character Capital. The company described the raise as $13 million USD; some coverage also frames it as “$20 million” (a currency conversion figure).

The funding is aimed at scaling an end-to-end research stack—recruitment and scheduling, interview operations, analysis/synthesis, and a governed insights repository—while doubling down on AI features that reduce the time and specialist labor required to run studies at enterprise scale.

Why investors are backing it

Enterprises increasingly want “research democratization”: enabling product, design, and marketing teams to run high-quality studies without bottlenecking on a central research org—while still keeping governance, templates, and permissions tight. Great Question is positioning itself as the workflow layer that makes that safe and repeatable.

That pitch matters because the research toolchain is fragmented. Many orgs still stitch together scheduling + panels + video + transcription + a repository + a survey tool, then lose insights in silos. Great Question is selling consolidation and control.

Potential stock market impact

Great Question is privately held, so there’s no direct ticker reaction. The more realistic market impact is second-order—competitive pressure and spend reallocation inside budgets that ultimately flow to public vendors.

1) Mild competitive pressure on “CX/insights” software baskets.
Publicly traded analytics, customer-experience and marketing-ops vendors could see incremental deal friction if Great Question displaces point tools or compresses seat expansion for adjacent products. The near-term risk is small (this is still a Series A scale business), but the direction is clear: consolidation platforms tend to reduce “tool sprawl” spend.

2) Tailwind for hyperscalers (indirect).
If Great Question’s AI roadmap increases usage of transcription, summarization, storage, and model inference, that can translate into higher cloud consumption—often landing with the major cloud ecosystems. It’s a thin tailwind rather than a headline driver, but it’s structurally supportive for large-scale cloud economics.

3) Watch for procurement dynamics, not hype.
The stock-market-relevant signal will be whether enterprises standardize research operations on a single governed platform. If they do, you’ll see knock-on effects: fewer niche renewals, tighter vendor lists, and more spend concentrated into “platform” vendors.

Consumer privacy impact

Even though Great Question sells B2B, the underlying data often includes high-sensitivity consumer/participant information: identity/contact details for recruitment, session recordings, voice/video, transcripts, behavioral notes, and potentially demographic attributes depending on study design.

Key privacy risks as the platform scales:

• Data minimization drift: larger panels and “always-on” research can incentivize collecting more participant data than necessary.
• AI processing ambiguity: if transcripts/recordings are used to power AI synthesis, customers will demand clarity on model training boundaries, retention, and subprocessors.
• Cross-border transfer and retention: global teams plus centralized repositories raise questions around where data is stored, how long it persists, and how deletion requests propagate.

What “good” looks like (and what buyers will ask for):

• Explicit controls around retention, deletion, and data residency, plus auditable access logs.
• Clear statements on whether customer data is used for training, and how opt-outs work.
• Strong consent flows for participants, especially for recorded sessions and any sensitive categories.

Bottom line: the funding accelerates product velocity, but it also increases the urgency of privacy-by-design—because the dataset is inherently human and identifiable.

reat Question operates in the user research and insights software market, where several established platforms compete for enterprise R&D, product, design, and customer-insights budgets. Unlike generic survey or analytics tools, these competitors focus on workflows that help teams recruit participants, conduct studies, and derive actionable insights.

Key competitors include:

• User Interviews – A widely used platform for recruiting research participants, screening, scheduling, and incentives, often paired with other tools for analysis.
• UserTesting – A mature user research service offering usability tests, video feedback, and broad participant panels, but typically requires stitching together external analysis tools.
• Qualtrics Strategy & Research – A heavyweight enterprise research suite combining advanced survey capabilities, analytics, and feedback mechanisms at scale.
• Respondent & Forsta – Platforms that support participant recruitment and moderated studies with robust research management features.
• Lyssna (formerly UsabilityHub), Hotjar, Maze – Tools that emphasize specific research methods such as rapid surveys, usability testing, or preference testing.

How Great Question differentiates:
Great Question aims to unify the entire research workflow—from participant recruitment and scheduling through moderated sessions, AI-assisted transcripts and analysis, to a governed insights repository—within a single platform that doesn’t require stitching together multiple services.

Competitive implication:
Where competitors may excel in breadth (e.g., large panels or advanced analytics) or depth in one function (e.g., usability testing or enterprise surveys), Great Question’s thesis is workflow integration and governance. Its value proposition is less about replacing every tool in the stack and more about reducing friction and technical debt in running repeatable, compliant large-scale research programs.

If it executes effectively, Great Question could shift spend away from fragmented stacks toward a unified enterprise research platform—putting pressure on incumbents to partner or broaden their workflows to remain competitive.

From my point of view, Great Question is not just “another research tool”—it’s trying to become the operating system for research teams. I’ve seen enterprises waste weeks because insights are scattered across spreadsheets, calendars, Zoom recordings, Notion docs, and disconnected survey tools.

If Great Question executes well, it can compress the entire research cycle—from recruitment to synthesis—into a repeatable pipeline. That’s exactly what enterprises pay for: speed, governance, and consistency, not just features.

The bigger signal for the market is this: the category is moving from single-function tools to integrated research platforms. And in the next 12–24 months, the winners will be the companies that reduce friction and prove they can protect participant data at scale.