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A structured concept testing survey for evaluating new e-commerce ideas with online shoppers. Measures appeal, clarity, perceived differentiation, and trial intent to inform positioning decisions before launch.
View templateMeasures A/B testing ease-of-use, guardrail adoption, result trust, and decision confidence among product and engineering teams. Use it to identify friction points, governance gaps, and training needs to scale experimentation.
View templateMaps the complete journey of a customer's most recent e-commerce session—from intent and actions to friction points and blockers—to diagnose conversion drop-off and prioritize UX improvements.
View templateAssesses experimentation program maturity across culture, process, tooling, governance, and outcomes. Designed for product, growth, and data teams to benchmark capabilities and identify improvement priorities.
View templateA structured diary study instrument for capturing in-the-moment e-commerce experiences across touchpoints and tasks. Designed for repeated daily entries to identify pain points, emotional states, and task-completion barriers throughout the customer journey.
View templateSegments online shoppers by purchase behavior, experience drivers, and communication channel preferences. Use this to build data-driven buyer personas and optimize channel strategy for e-commerce brands.
View templatePre-qualifies potential stakeholder interviewees by assessing role fit, recent domain involvement, and scheduling availability for 45–60 minute research sessions.
View templateA structured 3-entry diary study for UX researchers to capture real online shopping journeys, friction points, and purchase decision drivers over a 14-day period.
View templateMeasures consumer purchase frequency, channel preferences, decision drivers, and trade-offs in online shopping. Designed for ecommerce researchers and product teams seeking actionable shopper segmentation insights.
View templateA post-experience research survey evaluating the effectiveness of AI interview moderators across demographic groups. Measures overall experience quality, perceived empathy and understanding, cultural sensitivity, accessibility, and direct comparisons with human moderators. Designed to detect demographic moderation effects.
View templateSegments financial app users by usage behavior, feature priorities, trust levels, and demographics to build data-driven personas and inform product strategy.
View templateThis survey explores researcher experiences with reproducibility, transparency, and data quality in AI-moderated research. It serves as a replication study template to understand current practices, identify barriers, and assess the role of platform transparency in enabling reproducible AI-moderated studies.
View templateA meta-research coding instrument for researchers to systematically evaluate and compare data quality from AI-moderated interviews versus traditional qualitative methods. Designed for repeated use across multiple data sets. Estimated completion time: 12-15 minutes per data set evaluated.
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