What It Actually Takes to Run Global, Industry-Ready Research

Global, multi-market research asks a lot of a research stack: participants who speak different languages, terminology specific to an industry, and a team that can actually use what comes back, not just archive it. Without the right tooling, that means building the same study multiple times over and stitching the results together by hand, slow, expensive, and the kind of overhead that keeps teams from doing the multi-market research they actually need.

Outset's platform handles this directly. Participants respond in their own language and dialect. Researchers get results back in the language they work in. Industry-specific terminology transcribes accurately, regardless of field. And the evidence itself, not just the transcript, is watchable and understandable by any stakeholder.

Participants Choose Their Language

A participant selects their preferred language at the start of the interview, before the screener begins, and the AI moderator conducts the whole conversation in that language from there.

The system also recognizes regional dialects, not just top-level languages: a participant speaking Brazilian Portuguese gets a different voice and phrasing than one speaking European Portuguese, and the same holds for other regional variants.

If a colloquial term gets picked up inconsistently, like the Hong Kong Cantonese word for strawberry (士多啊梨) versus its more formal form (草莓), a researcher can correct it once and have that correction apply consistently across the rest of the study. One guide, one study, however many languages and dialects the research calls for.

Good for:

• Concept testing across multiple countries in a single fielding window

• Global usability studies without maintaining parallel study builds

• Research reaching underserved language communities within a single market

Voice Interviews Hold Up Over Longer Sessions

Alongside multi-language support, the voice interview must feel natural. The moderator responds faster and more consistently, even in longer, more extended conversations that used to feel like they were dragging.

Response lag is one of the most common reasons a voice interview loses a participant partway through, and fixing it matters most for studies that run long or reach participants over less-than-ideal connections.

Results Come Back in the Language You Work In

Multilingual fieldwork used to mean multilingual analysis. Outset translates interview transcripts and quotes back to whichever language a researcher works in, not just English, so a Japanese interview can be reviewed in Russian, or any other language a team needs, with no separate translator required.

One Clip, Any Stakeholder, Reach Beyond the Research Team

None of this matters if the evidence never leaves the transcript. Highlight reels carry English captions, so a 15-second clip pulled from question five of a Portuguese interview is watchable and understandable by a stakeholder who only reads English, no separate editing or subtitling step required.

Combined with multi-language interviewing and accurate terminology, this closes the loop end to end: research runs in the participant's language, gets reviewed in whichever language the researcher works in, and gets shared as evidence anyone across the org can watch and act on, not just the people who ran the study.

Terminology That Holds Up, Including Healthcare

General-purpose transcription tends to mangle specialized vocabulary: drug names, clinical shorthand, brand names, industry jargon. A single mangled term is enough to make a whole report feel untrustworthy.

Outset can be tuned to recognize the terminology a study depends on, whether that's a healthcare team running patient interviews or a fintech team discussing proprietary product names. If a term slips through, a researcher can search and replace it once, correcting it across every transcript in the study.

What This Means

You can find pieces of this elsewhere. What's harder to find is all of it, plus screen-share and Figma-based product research, in one platform. Most teams stitch this together across three or four vendors. Outset runs it as one.

Board of Innovation used it to run 250 interviews across 3 countries and 4 languages in days, testing 15+ concepts, and got back a single synthesis report at the end.

Research doesn't stop being useful because a participant doesn't speak English, or because the subject matter is technical. It shouldn't have to.