Gong vs User Intuition: Buyer Research and Pricing

A sales conversation may record an objection without resolving its role in the final decision. A buyer might discuss price repeatedly while procurement, implementation risk or an internal sponsor determines the outcome. User Intuition’s win-loss interviews investigate the sequence of events, alternatives and trade-offs after the decision.

Gong’s revenue intelligence connects customer interactions to coaching and deal analysis. Those insights can inform the interview brief: start with a disputed loss reason and recruit buyers who can explain what happened. You can keep Gong for revenue operations while using User Intuition for focused research.

User Intuition uses 5–7 levels of adaptive laddering. If a buyer says implementation felt risky, follow-ups can uncover the failed rollout they remember, the operational consequences they feared and the reassurance they needed. That detail can change a proof-of-concept offer, onboarding promise or sales message.

The approach is informed by Reynolds and Gutman’s laddering method, which connects attributes to consequences and personal values. For win-loss research, it helps distinguish the feature a buyer mentions from why that feature mattered to the purchase. Your team receives evidence it can use to change the buying experience. See how User Intuition applies laddering. RudderStack interviewed 40+ lost prospects within 48 hours in a win-loss study and found two blindspots that exit surveys and rep debriefs had missed: who controlled the budget, and which competitor had claimed a persona.

For a recent loss analysis, bring a list of buyers and define the decision you want to explain. User Intuition interviews participants when they are available and produces findings as quality conversations finish. Recruit across decision outcomes or buyer roles without adding a moderator’s calendar for each interview.

Recruitment and response affect turnaround. Your own closed-deal contacts are usually the relevant audience for deal-specific questions; User Intuition’s 4M+ vetted panel can support broader category-buyer research. Interviews in 80+ languages help teams investigate regional differences using the same learning goals.

User Intuition’s five-interview example costs $300 with standard panel recruitment. Incentives for your own participants are separate; specialist recruiting requires a quote. Research teams and agencies can assign the study cost to a client, segment or research question without purchasing seats for everyone who needs the findings.

Gong’s pricing page says its platform fee depends on the number of users and that integrations with your existing technology stack are free. Compare that team-wide investment with the specific research you need to commission. The pricing table below separates commitment, usage and recruitment.

For win-loss research, a participant who repeats “price” without describing the evaluation should not consume the same interview budget as a detailed account of the decision. User Intuition checks whether the conversation develops substantive answers and covers the brief before billing.

Gong’s license and platform fees cover its revenue software. User Intuition’s quality rule covers newly conducted research interviews. Passing those checks makes a conversation billable; the evidence review then assesses how much the interviews collectively support the proposed conclusion.

User Intuition’s evidence review is informed by Malterud et al.’s information power framework and Hennink et al.’s research on meaning saturation. These approaches relate sample adequacy to relevant information and distinguish noticing a theme from understanding it in depth. User Intuition applies these ideas to assess whether a loss reason is explained across relevant roles and deal outcomes. It can recommend deeper analysis of interviews that already contain the answer, or targeted interviews when a missing buying experience could change the conclusion.

A shopper study illustrates how this evidence review works. We interviewed 43 Walmart shoppers to understand purchase decisions, trip friction and return intent. Thirty-six said they would shop at Walmart again. User Intuition recommends recontacting shoppers after their next comparable trip, then comparing those who returned with those who chose another store. This tests what turns stated intent into a store choice. Explore the Walmart study, two recommended follow-ups and sample presentation.

Gong’s MCP server is read-only and can return links to the calls and emails behind its answers. This is useful when an assistant needs to explain an account risk or prepare for a deal review.

User Intuition’s agentic research workflow lets that investigation lead to a new study. For example, ask an assistant to examine whether implementation concerns recur among recent losses, prepare interviews for the missing buyer roles and return the evidence for the resulting recommendation. The workflow connects analysis to research your team can commission.

For win-loss work, User Intuition’s synthetic participants can help explore how different buyer roles interpret a revised implementation promise. Their individual experiences help your team refine the brief and identify the objections to investigate with the next group of buyers. Explore User Intuition’s synthetic participants.

This design is informed by Park et al. (2024). Their simulations of 1,052 people reproduced General Social Survey answers 85% as accurately as those people reproduced their own answers two weeks later. The result informs User Intuition’s person-specific grounding and repeated calibration against the original respondent. Gong’s account and deal insights support analysis of recorded customer activity; User Intuition’s calibrated participants support exploration of new research questions.