<![CDATA[Customer service chatbots have become a primary interface in e-commerce platforms, yet little is known about how interaction-quality perceptions relate to user trust in Southeast Asian contexts. This cross-sectional survey examined the associations of response relevance, response transparency, and interaction ease with trust in CLEO, the customer service chatbot embedded in the Lazada mobile application, among 200 users across the five administrative cities of Jakarta. Data were collected between February and March 2026 via a 16-item five-point Likert-scale questionnaire, with satisfactory reliability across all scales (α = .856–.876). Multiple linear regression with HC3 standard errors was applied. The model explained approximately 37.7% of variance in trust (adjusted R² = .368; F(3, 196) = 39.58, p < .001). All three predictors were positively associated with trust: response relevance was the strongest predictor (B = 0.44, β = .421, p < .001), followed by response transparency (B = 0.26, β = .265, p < .001) and interaction ease (B = 0.21, β = .207, p = .001). Sensitivity analysis on 184 complete-response cases yielded consistent results. Findings suggest that chatbot developers should prioritize answer accuracy, transparent identity disclosure, and conversational ease to foster user trust in e-commerce chatbot interactions.]]>
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