How B2B International checks quality and compliance across every interview, in every language

B2B International’s business-to-business market research depends on interviews run across dozens of languages and every one of those interviews needs to meet high quality and compliance standards. The problem was scale: a single audio takes up to an hour to review, making quality and compliance a time-consuming part of the interview workflow. After rigorous compliance, legal and information security assessments, obtaining informed consent from all parties, and ensuring the technology met B2B International's governance requirements, the team tested HappyScribe's AI Chat on a live project as an additional quality and compliance screening tool.

Checking interviews one language at a time

For Simon Brett, Senior Quality & Compliance Manager at B2B International, the old process was slow and partial by design. English interviews meant listening to the audio end to end. Other languages would inflate costs, as external resources and QC training had to be accounted for. Some languages, including French, German, and Brazilian Portuguese, were translated to English using HappyScribe and following along as best he could.

"Reading the translation while listening to it was the only way that I could check some of these interviews," Simon said. The team brought in native speakers, "but we don't always have the resource to do that in every language."

The bigger constraint was coverage across a project. The Interviewer Quality Control Scheme [IQCS] and Market Research Society [MRS] standards call for checking at least 10% of interviews; B2B International always checks more. "I'd listen to between 10 and 15% of the total number of interviews," Simon said. "So if they completed 100 interviews, I'd listen to 10 or 15 of them." Some languages were effectively impossible for him to monitor. Team 'catch-ups,' 1-2-1 chats and time-consuming data checks were employed as alternatives.

And the gaps had a cost. When an interviewer accidentally skipped a question that should have been asked or the survey question routing failed, the team had to investigate why and sometimes re-contact the respondent. "To maintain quality and ensure all questions were asked, the rising cost to fieldwork can be significant, so spotting issues in any language early on is paramount," Simon explained. The pressure was clear. Catch issues early or pay for them later.

Turning a transcript into a structured QC report

To test the approach, Simon performed initial testing on a 5-minute project. After reassuring himself on how the AI works and its effectiveness in English, he then worked on a live project that had just gone into field. He ran HappyScribe's AI Chat across roughly 30 to 40 interviews and realised this would be a fantastic supplement to the existing quality control processes and mandatory human review required by IQCS standards While still following IQCS and MRS standards in monitoring, HappyScribe was used on all languages equally, so there was no bias towards English being monitored more than say Japanese or Arabic.

The method was a single, carefully written prompt. He uploaded the approved question set as a PDF, then asked the AI to list every question the interviewer actually asked, compare each one to the approved question set, and mark it as a perfect match, a partial match, or no match. The output came back as a table including the recording name, the question asked, the match status, any discrepancies, and a timestamp pointing straight to the moment in the audio.

"The AI is only as good as the prompt you use," Simon said. The timestamp was a later addition. "I thought it'd be really good if I could get this to take me directly to the question in the audio for further checks. So I just added it, and it did. It was perfect."

The results held up against his own manual checks, and then some. "It probably picked up more than I would" Simon said. On one question, the research team had substituted a single word, "established" for "stable," across a batch of interviews. "In all six audios, the AI actually spotted a single word had been replaced with another" and flagged it for investigation. It turned out the interviewers were using a newer, approved version of the question set. The AI had caught a deliberate change before it was communicated to the quality team.

Simon was clear-eyed about the limits. "AI is an additional tool rather than a replacement," he said, and "I'd rather it flag something than not flag it." “You do spend time checking AI flags, as it turned out to be much stricter than a human reviewer, but the time was well worth it and the flags were a benefit rather than a nuisance, and all the flags were human reviewed before any quality or compliance action was taken.

Compliance checks that go the extra mile

One thing surprised him. The AI model recognised the legal nature of the content and began checking the informed consent steps at the front and back of each interview, treating them as a legal script. It verified that interviewers read out the privacy policy, gave their name, and got a clear yes or no on consent, and it listed each step with its own timestamp, to enable fast and easy human review, exactly as it did for the questions.

"It checks the compliance step by step without me actually asking it. It seems to recognise that it's a legal script," Simon said. "No idea why it knows how to do that. Didn't ask it to, but it does."

90% faster review, vastly wider coverage

The time saved is the headline. A single audio that took 45 to 60 minutes to review manually now takes about five minutes for HappyScribe’s AI to analyse, a reduction of roughly 90%. Simon can queue 10 or more at once and work on other compliance tasks while it processes in the background. Being able to cast the net so widely and so quickly over large volumes of interviews gives B2B International a real advantage.

That speed changes what is possible. Instead of a 10 to 15% sample, Simon can now run a quick check of almost every interview submitted. "It allowed me to check far more interviews than I would normally," he said, "instead of just checking around 10 or 15%, which is what we normally do." It also opened up the languages he found difficulty monitoring before. "It allowed me to pick up with more interviewers and give them some really good feedback and guidance" across more languages than before.

The freed-up time went to other impactful and collaborative work. In one week alone, Simon was able to pull together security and certification material that helped a colleague win a new contract, the kind of task he says he "probably wouldn't have had time to do" before.

Although AI reviewing can now be applied to almost every interview, Simon is clear that they continue to meet or exceed IQCS quality standards using traditional human review of interview recordings. AI can then be used to augment the existing human processes by identifying potential issues and directing attention across the wider sample, while quality and compliance decisions stay the responsibility of human reviewers.

"It's allowed me to tighten up quality control across all of the languages, and really get a much more consistent and accurately presented questionnaire to the respondents," Simon said. "It's a great tool that helps speed up the whole QC process, where I can actually feel more confident about the whole project delivery."

Results in a nutshell

Coverage jumped from a 10 to 15% sample to almost every interview: Quality checks now span the full project, greatly enhancing quality and compliance at the project level.

Quality control extended to all languages: All languages can now be monitored in-house and checked, allowing for rapid follow-up or intervention even when no reviewer is available that speaks that language

Compliance checked automatically: It assists in finding potential issues for review, and only on monitoring conducted above and beyond minimum standards achieved by humans.

More time for impactful and collaborative work: With enhanced QC and the time savings and quality boost this brings, the compliance team can dig deeper into client queries and support new business, including material that helped win a recent contract.

HappyScribe AI is used as an additional quality and compliance layer and is not a replacement for human quality control. All AI tools are subject to appropriate legal, privacy, information security and compliance review.