At Opinòmetre we work with a rigorous methodological approach, adapted to each project and focused on generating reliable information for strategic decision-making. We combine quantitative and qualitative techniques, integrating solid data collection processes, advanced analysis and the production of applied reports. Our working model covers all phases of the study: methodological design, data generation, technical analysis and the presentation of clear, structured and actionable results.
We apply quantitative techniques aimed at obtaining structured and representative data that allow robust statistical analyses.
Face-to-face surveys assisted by electronic devices. They allow greater control of the interview and are suitable for complex questionnaires or audiences with lower digital access.
Computer-assisted telephone interviews. They ensure speed, fieldwork control and wide geographical coverage with automated quality control.
Self-administered online questionnaires. An agile and efficient method for large samples and audiences with digital access.
A traditional method used in specific studies where a physical format or access to certain groups is required.
Product tests carried out in controlled environments to assess perception, acceptance or direct experience.
Product evaluation in the consumer’s usual environment to measure real use and natural behaviour.
Techniques aimed at understanding deep motivations, attitudes and perceptions that cannot always be captured through structured surveys.
Moderated group dynamics that allow exploring collective opinions, attitudes and discourses on a specific topic.
Structured or semi-structured individual conversations to analyse personal perceptions and experiences in depth.
Tools that help identify latent attitudes and unconscious perceptions through indirect stimuli.
Design of controlled scenarios to assess behaviour and response to different variables.
Systematic analysis of behaviour in real environments without direct intervention.
Anonymous service evaluation to measure service quality and the actual user experience.
We apply advanced statistical techniques that allow data to be interpreted with scientific rigour and solid conclusions to be obtained.
Production of tables, charts and measures of central tendency, dispersion and shape to describe the information collected.
Preliminary techniques to identify patterns, trends and possible relationships between variables.
Construction of confidence intervals, hypothesis testing and sample design that allow results to be generalised to the population.
Analysis of relationships between variables and segmentation of results.
Modelling of causal relationships between variables in their different forms (linear, logistic, etc.).
Principal components, factor, discriminant and cluster analysis to identify complex structures in the data.
Structural equation models, multilevel analysis, time-series analysis and survival analysis for more complex studies.
Structured interpretation of discourse and social context using specific comparative analysis techniques and mixed methodologies.
Study of context, narrative and meaning-making in the collected discourse.
A structured consultation technique with experts to reach consensus in complex scenarios.
Qualitative comparative methods that allow the analysis of causal configurations in complex social phenomena.