Instapanel vs User Intuition: Video Research, Speed and Cost

For research teams and agencies, User Intuition can add customer evidence to a proposal, creative decision or strategy project without commissioning a separate fieldwork engagement. Your researchers define the learning goals, review findings and choose the next question.

Instapanel’s workflow includes research design, custom audience recruitment and human analysis with AI support. Its methods include video research, mobile ethnography and combined qualitative and quantitative work, making service and deliverable scope part of the purchasing decision.

User Intuition’s AI moderator uses 5–7 levels of adaptive laddering, informed by Reynolds and Gutman’s laddering method (1988). Laddering connects a product attribute to its practical consequences and the personal values behind a decision. If a shopper says a display was hard to use, laddering can explore what they were trying to do, what they overlooked and how that affected the purchase. This gives the team an actionable explanation to pair with any visual observation. See how User Intuition applies laddering.

Instapanel’s team can adjust a questionnaire or audience while research is in progress and interpret responses through human review. User Intuition handles response-led probing within each voice interview, then uses evidence assessment to recommend the next study.

User Intuition’s starting workflow includes sign-up, guided setup, fieldwork and findings. Your team can invite participants after reviewing the brief and budget, and the platform runs conversations concurrently. That supports focused research questions on a short deadline.

Instapanel’s published timing is typically 3–10+ days from launch, with some studies completing in 24 hours. It also describes proposals within 24 hours. Custom targeting, methods and analysis affect the project schedule; User Intuition’s self-serve path removes the separate proposal step for a standard voice study.

User Intuition charges $30 per quality voice interview for moderation and analysis. Standard panel recruitment adds $30 per participant. Incentives you arrange for your own participants are separate; specialist audiences require a recruiting quote. The published pricing lets research teams and agencies budget a focused study before committing to a broader program.

Instapanel also charges per project without a subscription. Its $3,500 starting package covers 20 video participants with basic age, gender and location targeting in the US, including incentives. User Intuition’s starting price covers a smaller five-person voice study, giving teams a lower-cost way to investigate a focused question before expanding the work.

User Intuition checks whether the conversation lasted long enough to address the brief, explored the participant’s experience in depth and covered the research topics. This makes the bill depend on the substance of the interview, giving your team a clearer basis for accepting work and planning the next study.

Instapanel uses human review with AI assistance before releasing participant material. User Intuition automates Length, Depth and Coverage checks before charging for an interview. The service differs: Instapanel includes a research team’s review, while User Intuition gives your team a consistent acceptance standard in the platform.

The User Intuition Walmart preview shows a complete study, a sample presentation and proposed follow-up research. It demonstrates how a team can move from a research purpose to findings, supporting quotes and the next question to investigate.

Instapanel’s deliverables include an interactive infographic, videos, transcripts, codes and downloadable data. A findings report, statistical analysis and a brand-ready presentation are additional options. These services matter when the buyer wants help turning fieldwork into a finished deliverable.

User Intuition assesses the relevant experience, depth, variation and competing explanations in the interviews. In shopper or creative research, positive reactions may not explain what a person would choose in the store. The review examines the situations, alternatives and tradeoffs behind the reaction, helping your team plan a follow-up that tests the decision rather than repeating the same stimulus. Recommendations prioritize the gaps with the greatest consequence for the research purpose, so the next step addresses the decision your team must make.

User Intuition’s evidence review is informed by Malterud et al.’s information power framework, which relates sample adequacy to the relevant information interviews provide, and Hennink et al.’s saturation research, which distinguishes identifying a theme from understanding its meaning. User Intuition applies these principles to decide whether a gap calls for deeper analysis of existing interviews or a targeted study with people whose experiences are missing.

For example, we interviewed 43 Walmart shoppers to understand purchase decisions, trip friction and return intent. Thirty-six said they would shop at Walmart again, but stated intent leaves the next store choice unresolved. User Intuition recommends recontacting shoppers after their next comparable trip to understand what distinguished those who returned from those who chose another store. Explore the Walmart study and sample presentation to see the findings and two recommended follow-up studies.

User Intuition’s agent research workflow connects planning and execution. For example, an assistant can retrieve the reactions to an earlier campaign, prepare a brief for people who noticed it but did not act, and estimate the next study’s cost. Your team reviews the plan and approves spending; the assistant can monitor progress and return findings linked to source interview moments.

Instapanel offers downloadable research materials and project support from its team. User Intuition’s MCP and API workflow lets an assistant work directly with research retrieval, study preparation and approved execution.

User Intuition’s synthetic participants preserve individual experiences and behavioral differences that generic LLM feedback can flatten. A frequent category buyer and a person who has never considered the product may interpret the same creative differently. User Intuition models their distinct histories and habits, helping a researcher sharpen the next interview guide and prioritize relevant follow-up audiences. Calibration uses the differences between modeled and real responses to refine the representation of each person.

This design is informed by Park et al. (2024). Using interviews with 1,052 people, the researchers built simulations that reproduced General Social Survey answers 85% as accurately as those people reproduced their own answers two weeks later. The useful principle is individual grounding paired with measurement against the person represented. See how User Intuition grounds and calibrates synthetic participants.