운영·데이터

Give stakeholders 100 points and make them spend it: constant-sum allocation across initiatives forces the prioritization that agree-scale surveys hide. Follow-up questions capture what they'd cut entirely, and the AI interviewer pressure-tests their biggest bet.

Captures how easy and effective it is for internal teams to reach and work with a vendor's point of contact — responsiveness, accuracy of contact info, and follow-through. An AI follow-up digs into the most recent real interaction to surface what actually happened when things went well or went wrong, beyond the rating.

A company-wide pulse survey assessing employee readiness for post-merger integration across culture alignment, process documentation, tooling access, and communication effectiveness. Designed for fielding in the weeks before or after a merger close to surface urgent gaps.

Measures cost visibility, ownership clarity, and trade-off decision-making across engineering teams. Designed for engineering leaders seeking to benchmark FinOps maturity and identify tooling or process gaps.

Measures how reps actually experience your sales tech stack — CRM friction, tool overlap, hours lost to admin, and which tools they'd cut or keep — for sales ops leaders auditing their stack. An AI follow-up reconstructs the specific moment a tool slowed a rep down, instead of collecting generic complaints.

Measures incident impact, communication effectiveness, and trust recovery across stakeholder roles. Designed for internal post-incident reviews to identify systemic improvement priorities.

Diagnoses bottlenecks, clarity gaps, and cycle-time issues across procurement request and approval workflows. Designed for internal operations teams seeking data-driven improvements to purchasing processes based on employee feedback.

Diagnoses catalog discoverability, ownership clarity, and data trust across teams. Designed for internal data practitioners to identify governance gaps and prioritize catalog improvements using NPS and behavioral metrics.

Measures data practitioners' confidence in lineage accuracy, impact analysis efficiency, and tooling gaps. Designed for data engineering, analytics, and platform teams to identify high-priority improvements to lineage infrastructure and workflows.

Measures customer perceptions of clarity, timeliness, and trust in crisis and outage communications. Designed for B2B operations teams seeking to benchmark and improve incident response communication.

위기 대응에서 실질적으로 개선할 점을 파악하기 위해 이해관계자 관점에서 장애 커뮤니케이션의 적시성, 명확성, 채널 효과, 전반적 품질을 평가합니다.

Measures safety behaviors, reporting confidence, environmental hazards, and leadership support across e-commerce fulfillment teams to identify targeted risk-reduction priorities.

Diagnoses friction in a specific internal process — where time gets lost, which steps break down, and what to fix first — built for ops leads, IT, or process owners running a targeted improvement review. A trade-off ranking surfaces the top pain point, and the AI follow-up interview digs into a concrete recent example instead of a generic complaint.

Captures stakeholder expectations for data product availability, freshness, and quality to inform internal SLO/SLA definitions. Designed for data consumers across engineering, analytics, and business teams.

Measures B2B professionals' trust in supplier provenance claims, identifies data gaps and verification practices, and surfaces priorities for improving supply-chain transparency. Designed for procurement, quality, compliance, and supply-chain roles.

Measures internal stakeholder satisfaction with operations support across resolution speed, communication quality, and professionalism, with NPS benchmarking. Designed for recurring deployment to track service improvement over time.

Assesses how a vendor or supplier is performing on quality, reliability, pricing, and support, and gauges internal appetite for renewal. Built for procurement teams and vendor managers running periodic supplier reviews, with an AI follow-up interview that digs into the specific incident or driver behind a respondent's satisfaction score instead of stopping at a number.

Evaluates stakeholder perceptions of incident communication timeliness, clarity, frequency, and helpfulness to identify priority improvements in crisis communication workflows.

Collects structured stakeholder feedback on SLA adherence, incident resolution quality, and improvement priorities over a 90-day window to identify service gaps and guide operational improvements.

An internal assessment for measuring employees' data literacy, self-service analytics confidence, tool adoption, and support needs — designed to surface skill gaps, trust issues, and barriers that inform data-enablement strategy.