HEUXIVA: A Set of Heuristics for Evaluating User eXperience with Voice Assistants

Voice assistants have become increasingly common in everyday devices such as smartphones and smart speakers. Improving their user experience (UX) is crucial to ensuring usability, acceptance, and long-term effectiveness. Heuristic evaluation is a widely used method for UX evaluation due to its efficiency in detecting problems quickly and at low cost. Nonetheless, existing usability/UX heuristics were not designed to address the specific challenges of voice-based interaction, which relies on spoken dialog and auditory feedback. To overcome this limitation, we developed HEUXIVA, a set of 13 heuristics specifically developed for evaluating UX with voice assistants. The proposal was created through a structured methodology and refined in two iterations. We validated HEUXIVA through heuristic evaluations, expert judgment, and user testing. The results offer preliminary but consistent evidence supporting the effectiveness of HEUXIVA in identifying UX issues specific to the voice assistant “Google Nest Mini”. Experts described the heuristics as clear, practical, and easy to use. They also highlighted their usefulness in evaluating interaction features and supporting the overall UX evaluation process. HEUXIVA therefore provides designers, researchers, and practitioners with a specialized tool to improve the quality of voice assistant interfaces and improve user satisfaction.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-10-18
DOI
https://doi.org/10.3390/app152011178
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HEUXIVA: A Set of Heuristics for Evaluating User eXperience with Voice Assistants

Daniela Quiñones, Sandra Cano, Luis Rojas, Juan Manuel Ramírez et al.
1 citations
Applied Sciences
AI in Service Interactions
2.48
article

HEUXIVA: A Set of Heuristics for Evaluating User eXperience with Voice Assistants

Daniela Quiñones, Sandra Cano, Luis Rojas, Juan Manuel Ramírez, Camila Serrá, Viviana Barrientos
article en
1 citations

Abstract

Voice assistants have become increasingly common in everyday devices such as smartphones and smart speakers. Improving their user experience (UX) is crucial to ensuring usability, acceptance, and long-term effectiveness. Heuristic evaluation is a widely used method for UX evaluation due to its efficiency in detecting problems quickly and at low cost. Nonetheless, existing usability/UX heuristics were not designed to address the specific challenges of voice-based interaction, which relies on spoken dialog and auditory feedback. To overcome this limitation, we developed HEUXIVA, a set of 13 heuristics specifically developed for evaluating UX with voice assistants. The proposal was created through a structured methodology and refined in two iterations. We validated HEUXIVA through heuristic evaluations, expert judgment, and user testing. The results offer preliminary but consistent evidence supporting the effectiveness of HEUXIVA in identifying UX issues specific to the voice assistant “Google Nest Mini”. Experts described the heuristics as clear, practical, and easy to use. They also highlighted their usefulness in evaluating interaction features and supporting the overall UX evaluation process. HEUXIVA therefore provides designers, researchers, and practitioners with a specialized tool to improve the quality of voice assistant interfaces and improve user satisfaction.

Applied SciencesVol. 15(20)
Pontificia Universidad Católica de Valparaíso (CL), Federico Santa María Technical University (CL)
Agencia Nacional de Investigación y Desarrollo
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.