The Hybrid Model, which is frequently used in quantitative studies, makes use of 2 or more data collection techniques, usually CATI, CAPI and CAWI, in order to maximize coverage, accuracy and response rates. The combination of approaches provides the flexibility to collect data according to the needs and constraints of various types of respondents in terms of preference, technological access, or location.

This could mean that, for instance, CAWI would be used for urban tech-savvy groups, CAPI for topics of rural non- connected respondents and CATI for follow-ups/clarifications. This also promotes the representativity of and the quality and information completeness of the data.

The hybrid model combines both methods’ strengths. CAWI is fast and scalable, CATI allows for more control and supervision by interviewers, and CAPI has more depth and clarity through face to face interaction. Together they triangulate each other’s flaws and help to provide deeper and more balanced insights.

It is a useful method in designing large scale surveys, longitudinal and cross-national studies where standardization and flexibility are prerequisites of the methodology. It is also well-suited to sensitive subjects because some of the questions can be difficult for a respondent to answer without help from the interviewer, while others can be administered alone.

The hybrid model is highly dependent on coordination, maintaining consistent survey designs across modes, and strong integration of the data. Questionnaire and response formats should be standardized in order to achieve meaningful comparisons across modes.

The logistical complexity and planning required by the hybrid model is more difficult to achieve, but its benefits in quality of response and inclusiveness are sizable. It also demonstrates the changing demands of contemporary research and provides a way to consider a quantification that is accurate, far reaching, and in depth.