Tegus vs User Intuition: Expert Calls and Interview Costs

Tegus Expert Call Services sources relevant specialists for human-led or AI-led consultations. The transcript library can also provide existing perspectives on a company, market or industry. These resources are useful when specialist experience is central to interpreting a market or testing an investment thesis.

User Intuition’s customer diligence workflow investigates the people whose choices underpin that thesis: buyers, users, former customers or prospective adopters. Teams can combine their accounts with specialist research. For the broader content-search and intelligence-platform decision, see the AlphaSense comparison.

Tegus’ AI-led call workflow incorporates research topics and AlphaSense context into the interviewer’s preparation. The service manages expert sourcing, scheduling and compliance review, giving the conversation a specialist research setting.

User Intuition’s laddering approach is informed by Reynolds and Gutman’s laddering method, which connects product attributes to consequences and personal values. A customer may describe integration as a reason to stay with a vendor, then explain that switching would jeopardize a critical reporting routine and their credibility with management. That chain helps a diligence team assess the source of retention and how durable it may be.

An existing Tegus transcript can provide an immediate perspective without new fieldwork. A commissioned expert call follows sourcing, participant availability, interview execution and review. The published transcript turnaround begins after the conversation, so it should be considered separately from the time to start a new engagement.

User Intuition supports BYOP or a 4M+ vetted panel and interviews in 80+ languages. For research about a specific company, recruit people with the relevant customer experience. Findings arrive as interviews finish, allowing comparison across segments during fieldwork. Rare profiles and specialist screening can extend recruitment and require a separate quote.

Tegus’ call-service terms include pay-as-you-go calls without a minimum commitment and prepaid packages. Human-led and AI-led calls use the expert-rate-plus-transcription model. Broader AlphaSense platform and transcript-library access uses a separately scoped subscription.

User Intuition’s five-interview example includes the interview workflow and analysis. Standard panel recruitment adds $30 per participant; BYOP incentives are separate. A named-company buyer or specialized professional is recruited to order. Match the study budget to the firsthand experience the question requires, then use evidence assessment to direct follow-up spending.

For customer research, User Intuition checks whether the conversation contains enough relevant substance to address the learning goals. Completion alone does not determine the charge. This helps teams avoid paying for shallow accounts and removes the administrative work of requesting refunds for failed interviews.

Tegus also provides quality protection: its AI-call documentation says it reruns a call at no cost if quality falls short, alongside automated and human compliance review. User Intuition’s safeguard operates through automatic Length, Depth and Coverage checks before the interview is billed.

User Intuition’s evidence review is informed by Malterud et al.’s information power framework and Hennink et al.’s meaning-saturation research. These approaches connect sample adequacy to relevant information and distinguish identifying a theme from understanding it in depth. For an investment thesis, User Intuition can distinguish detailed buying or renewal experiences from broad expressions of confidence. It can recommend analyzing an existing switching account more deeply or interviewing a missing customer group, prioritizing the gap that could change the commercial assessment.

The gap between what buyers say and what drove their decision is measurable: across 10,247 buyer interviews, price was cited in 62.3% of lost deals but was the primary driver in 18.1% (User Intuition research). That is why an expert’s view of a market is worth pairing with the customers who made the decision. See a worked evidence-review example, with two recommended follow-up studies.

AlphaSense can analyze expert transcripts alongside other market intelligence and source its answers to the underlying material. A researcher can use these perspectives to develop a hypothesis and identify the customer experience that would help test it.

With User Intuition’s agent workflow, the team can review a proposed brief and budget, approve spending and launch a targeted study. The assistant returns findings with supporting accounts for assessment. This connects the research question, new fieldwork and the next decision within a repeatable workflow.

User Intuition builds synthetic participants from real, opted-in respondents, using their individual traits, habits and behaviors. It repeatedly compares synthetic responses with the same respondents’ real answers to calibrate the models. That grounding preserves differences in experience and priorities that generic LLM feedback tends to flatten.

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 study informs User Intuition’s emphasis on individual grounding and repeated calibration. For diligence, this helps a team develop more specific questions about adoption, renewal or switching before selecting the customer audience.

On User Intuition’s preregistered benchmark, synthetic participants built from a person’s own interview closed 81% of the fidelity gap, against 19% for demographics alone, in within-domain response prediction. Method and results.