산업별

Diagnoses where people get stuck when a product or service requires them to upload photos — for listings, claims, verification, or proof-of-delivery flows. Combines closed questions on device, friction points, and guideline clarity with an AI follow-up that reconstructs the exact moment the upload process broke down, so teams for marketplaces, insurance, real estate, and verification products know what to fix first.

Assesses how ready and motivated a business is to launch, expand, or upgrade its e-commerce capabilities — covering current online sales performance, feature priorities, budget trade-offs, and price sensitivity. Built for teams scoping a digital commerce investment, with an AI follow-up that digs into the single biggest obstacle blocking online growth.

Qualifies and recruits candidates for a focus group by screening for category usage, conflicts of interest, prior research participation, and scheduling fit, then capturing core demographics. An AI follow-up interview asks candidates to describe their real experience with the topic in their own words, surfacing rehearsed 'professional respondent' answers and gauging how articulate and engaged they'll be in the room.

Captures what shoppers came to buy, how they navigated the store, what they did when an item was missing, and how checkout felt — with an AI follow-up that digs into the real reasoning behind substitution choices and navigation friction. Built for retail insights and category management teams.

Measures how well your continuous improvement or Kaizen-style program actually functions day to day — suggestion volume, leadership follow-through, training gaps, and real barriers — for operations and HR teams running lean or quality initiatives. An AI follow-up reconstructs what actually happened to a recent improvement idea instead of general opinions about the program.

Gathers employee preferences on format, timing, budget priorities, and inclusivity for your company holiday celebration, plus a rating of intent to attend this year. An AI follow-up interview digs into why people would or wouldn't show up, so planners can fix the real barriers instead of guessing.

Captures why runners signed up for your 5K, how smooth their registration felt, and which race-day logistics matter most to them — built for race directors, event marketers, and charity partners planning future runs. The AI follow-up digs into any registration friction and the real motivation behind the signup, not just the option they clicked.

A structured post-lesson observation form for instructional coaches, administrators, and peer observers to rate teaching practices, student engagement, and instructional strategy — with an AI follow-up interview that reconstructs the specific moments behind the ratings so feedback is concrete enough to coach from.

Collects structured technician feedback on the clarity, accuracy, accessibility, and timeliness of aerospace maintenance documentation to drive safety and efficiency improvements.

Measures how members feel about meeting logistics, book picks, and discussion quality in a recurring book club — with an AI follow-up that digs into the 'why' behind their most recent discussion rating so organizers know what to fix versus what to keep. Built for book club leads, library programs, and reading communities checking in every few months.

Measures rider perceptions of safety, trust, incident prevalence, and feature priorities across ride-hailing platforms. Designed for CX and product teams seeking actionable insights to improve rider retention and safety outcomes.

Measures how satisfied clients are with a recent salon visit — stylist skill, cleanliness, wait time, value, and ambiance — plus loyalty signals like rebooking intent and recommendation likelihood. An AI follow-up interview reconstructs the specific moment behind a client's rating, giving salon owners concrete, actionable fixes instead of vague scores.

A confidential board-administered review of the Executive Director's leadership, financial stewardship, fundraising, staff culture, and governance partnership. Combines multi-area rating batteries, a prioritization exercise, and an AI follow-up interview that digs into the reasoning behind the overall rating and contract recommendation, giving the board a richer picture than scores alone.

For organizations in high-risk professions (first responders, healthcare, social services, journalism) to understand how often staff are directly exposed to traumatic events on the job and whether current support systems actually help. An AI follow-up interview explores what support was present or missing after a recent difficult incident, without asking anyone to relive graphic details.

Assesses how big and reachable the opportunity is for a new product, service, or market entry — awareness, purchase intent, price tolerance, and competitive standing — for product and strategy teams, with an AI follow-up that probes the real reasons behind stated purchase intent.

Tracks how people in a weight loss program, coaching service, or health app are actually progressing — what's getting in their way, where they're putting effort, and which support features they'd value most — with an AI follow-up that reconstructs the last time they fell off track and what would have changed the outcome. Built for programs and coaches optimizing retention and results.

방송사, 스폰서, 스포츠 미디어 브랜드를 위한 상식 겸 태도 설문으로, 팬들이 월드컵을 얼마나 밀접하게 시청하는지, 대회에 대해 실제로 무엇을 알고 있는지, 그리고 무엇이 계속 시청하게 만드는지를 측정합니다. AI 후속 인터뷰에서는 팬들이 왜 자신이 응원하는 팀을 지지하는지, 그리고 예측에 대한 자신감을 실제로 이끄는 요인이 무엇인지 깊이 파고듭니다.

Tracks voter registration status, candidate preference, issue priorities, and approval of current leadership, for campaigns, newsrooms, and political researchers running online polls. An AI follow-up interview digs into the reasoning behind each respondent's vote choice — especially undecided voters — instead of stopping at a checkbox.

타깃 시장이 누구인지, 무엇을 필요로 하는지, 가격을 다른 요소와 어떻게 비교해 판단하는지, 그리고 현재 귀사 대신 어디를 이용하는지를 파악합니다. AI 후속 질문을 통해 그 선택 뒤에 숨은 진짜 트리거를 드러냅니다. 출시, 리포지셔닝, 또는 확장에 앞서 시장이나 세그먼트를 가늠하는 제품, 마케팅, 리서치 팀을 위해 설계되었습니다.

Measures how satisfied readers are with your publication's accuracy, depth, timeliness, and relevance, and which content types they value most. An AI follow-up interview digs into the reasoning behind each reader's satisfaction rating so editorial and product teams know what to fix or double down on.