Sprig vs User Intuition: Adaptive Surveys and Depth Interviews

A structured survey can compare responses to consistent measures. A depth interview can investigate an unexpected experience, trace the trade-offs behind a decision, and challenge your starting assumptions. Both can include open-ended questions and AI follow-ups.

For example, a team tracking whether checkout satisfaction has changed needs a consistent measure across waves. A team trying to understand why shoppers lose confidence during checkout needs accounts of the task, alternatives, and perceived risks. Choose the method around that decision, and inspect whether the output gives you a trend to monitor or an explanation you can use to design a change.

Sprig’s survey research platform supports reaching participants through external panels, email, and your product. User Intuition supports panel and own-participant interviews, with findings linked to the conversations behind them.

User Intuition runs studies and audiences in parallel, without a platform-imposed hourly interview cap. User Intuition lets research teams and agencies start with a brief, review the interview guide, and invite their own participants or recruit from the panel. Findings appear as quality interviews complete. Starter requires no monthly subscription or sales call; audience availability and response affect the completion time.

Sprig can reach an available audience through email or in-product surveys, or recruit through external panels. Its enterprise quote covers the capabilities and deployment required. User Intuition offers direct sign-up and published rates, so a research team can prepare a focused interview study and begin inviting participants without a sales process.

User Intuition’s interview design is informed by Reynolds and Gutman’s laddering method (1988). Instead of stopping at “price is too high,” an interview can explore the alternatives considered, the expected benefit, and the event that made a purchase feel risky. Those accounts can reveal which dimensions a later survey should measure. This helps your team decide whether to test a price change, explain the benefit more clearly, or address a specific perceived risk behind the survey response.

Sprig’s market research offering includes conjoint, MaxDiff, pricing studies, and adaptive follow-ups. That makes it a substantive alternative when the question calls for structured choice or measurement.

Sprig’s panel workflow includes audience targeting, screeners, quotas, and participant quality controls. This enables research beyond in-product feedback.

User Intuition offers a 4M+ vetted panel and 80+ languages, with standard recruiting at $30 per participant in addition to the voice platform fee. For either method, recruit people with relevant experiences. An active user, a former customer, and a prospect can have materially different evidence to contribute.

For a new-market question, specify the category experience and buying role you need, rather than relying on a broad demographic profile. You may want recent buyers, people who considered the category and declined, or customers of another provider. Those groups can reveal different barriers; defining them in the brief makes recruitment feasibility and the resulting evidence easier to evaluate.

User Intuition’s checks assess whether participants complete the interview, explain relevant experiences in depth, and cover the research brief. A genuine participant can finish a conversation without providing enough substance to meet those standards. Automatic checks help protect your budget and reduce the work of reviewing failed sessions and requesting billing corrections.

This matters when comparing interviews with survey research: Kantar reports that researchers discard an average of 38% of survey data because of quality concerns. These industry-wide losses make the handling of unusable responses a practical buying consideration. Sprig advertises bot detection, duplicate prevention, and response-quality controls; User Intuition’s interview billing is tied to passing its automatic quality checks.

Each User Intuition quality voice interview costs $60 all-in with panel recruitment, so five cost $300. With your own participants, five cost $150 in platform charges; any incentives you offer are separate, and specialist audiences are recruited to order.

Sprig previously advertised a free tier and a $175/month Starter plan. Its public pricing page presents custom enterprise quotes; the former plans are historical price references, not today’s entry offers. Compare the cost of the research design you need, including recruitment and any platform commitment.

User Intuition’s evidence review assesses relevant experience, depth, variation, and competing explanations. For each learning goal, its review shows what the evidence supports, what limits the conclusion, and what that means for the research decision. It turns an unresolved survey pattern into a focused follow-up: which experience to investigate, whose perspective is needed, and which explanation could change the product or marketing decision.

User Intuition’s evidence review is informed by Malterud et al.’s information power framework, which emphasizes the relevant information interviews provide, and Hennink et al.’s saturation research, which distinguishes identifying a theme from understanding it in depth.

User Intuition applies these principles to assess whether existing interviews contain enough relevant detail to answer your research question. It can recommend deeper analysis when the evidence is already available, or targeted follow-up interviews when important experiences or explanations are missing.

A shopper study illustrates how this evidence review works. We interviewed 43 Walmart shoppers to understand how they made purchase decisions, where they encountered friction, and what would bring them back. Five shoppers described difficulty choosing between product variants. That points to a practical next question: would clearer product information help them choose? User Intuition recommends testing the current information against a simple comparison guide with recent category shoppers, then exploring what makes the decision easier.

For product research, apply the same review to the task and user group: what caused the friction, whose experience is missing, and what evidence would change the proposed improvement?

Explore the Walmart study and sample presentation, including the interviews, findings, and two recommended follow-up studies.