Validating personas for better communication: A structured model for low-resource contexts

Objective. This study proposed a structured and accessible model for validating data-driven personas, with a focus on precision, particularly in low-resource communication and design contexts. Design/Methodology/Approach. The study was grounded in the design science research (DSR) methodology and introduced a seven-step validation process centered on a double weighting system. The method was applied in a real-world case involving a Brazilian fintech company. Structured interviews, predefined scoring logic, and proximity-based analysis were used to measure the alignment between personas and real individuals. Results/Discussion. The model effectively quantified the degree of alignment between respondents and personas through a persona approximation index termed the “FIT Index.” The application of a heatmap-style matrix facilitated interpretation, revealing both strong and diffuse alignments. Lower scores yielded valuable insights, suggesting partial identification with the designated personas. This identification facilitated the implementation of informed adjustments to communication strategies. Conclusions. The proposed model demonstrated efficacy in evaluating the representativeness of personas through the utilization of rudimentary instruments such as spreadsheets and structured questionnaires. It provided a replicable and scalable framework for organizations and scientific teams that aimed to enhance communication practices with limited technical resources. Value. This study addressed a practical gap by presenting an empirical, proximity-based model for persona validation. The originality of this approach lay in its double weighting strategy, which combined attribute relevance and response alignment. This strategy contributed to the democratization of data-driven communication and design practices in low-resource contexts.