Beyond Cost and Time: What CPI, IR, and LOI Really Tell You

CPI, IR, and LOI are fundamental metrics in market research planning, but their influence goes beyond cost and timelines. Together, they affect respondent participation, engagement levels, and the overall reliability of collected data. When considered in combination, these metrics help research teams design studies that are both feasible and dependable.

Cost Per Interview (CPI) represents the investment required to secure a qualified completion. It is shaped by audience availability, screening complexity, and survey length. In practice, CPI also reflects the effort expected from respondents, which can influence willingness to participate and complete a study attentively.

Appropriate CPI setting supports stable fieldwork and predictable delivery, particularly for specialised or hard-to-reach audiences.

Incidence Rate (IR) measures the percentage of respondents who qualify after screening. Lower IRs typically indicate more selective targeting and require higher screening volumes to meet quotas. Monitoring IR early in fieldwork helps teams validate assumptions, refine screening logic, or adjust feasibility expectations before timelines are impacted.

IR is therefore a useful indicator of how efficiently a target audience can be accessed.

Length of Interview (LOI) estimates the time required for survey completion. LOI influences respondent engagement, drop-off rates, and data consistency, particularly in studies with complex routing or open-ended questions. Research literature shows that longer or cognitively demanding surveys increase the risk of respondent fatigue, making LOI a key consideration in study design.

Aligning LOI with survey complexity helps maintain consistent attention throughout the interview.

At TrustSample, CPI, IR, and LOI are evaluated together during study setup and continuously reviewed during fieldwork. Through early piloting, behavioural monitoring, and AI-supported quality checks, we focus on maintaining realistic expectations around recruitment and engagement. This balanced approach supports efficient fieldwork while protecting the reliability of the final data.