Language translation effects in Chatbots: Evidence from a randomized field experiment on a mobile commerce platform

• Research Focus: Investigates the impact of language localization in AI chatbots on user behavior in a mobile platform in India. • Theoretical Framework: The TAM, UTAUT, and CLT are used to explain user interactions with language-switching chatbots. • Methodology: Experiment where users were assigned to an English-only or bilingual version to evaluate changes in purchases and uninstalls. • Key Findings: Localization boosts purchases (+87%) but increases uninstalls (+76%), ideal for simple products, risky for complex ones. This study investigates the impact of language translation innovations in artificial intelligence (AI) digital assistants. We use data from a mobile com- merce platform application in India that introduced a Hindi and English version of its previously English-only language chatbot. The data, obtained from a randomized field experiment conducted on new users, help determine the impact of introducing language translation in conversational chatbots by quantifying its effect on user metrics such as purchases and uninstalls. In the experiment, the firm only altered the language of interaction, from English- only to Hindi and English. The firm did not make any other changes in the design or purchase flow within the application. We find that language trans- lation innovations significantly increase the number of user sessions and also improve user purchases and engagement. The increase in the engagement did not emerge from an increase in the number of sessions but from an increase in interactions within a session in the bilingual app. We also observe a sharp rise in uninstalls for the population that received the bilingual app. We find that in the bilingual chatbot, uninstalls rise with increased user interactions in a high involvement product category. In sum, the results from the field experiment show that while language translation in artificially intelligent as- sistants leads to greater purchases, it could also lead to increased uninstalls. This result suggests that implementing similar language translation innova- tions in isolation, without any modifications to in-application experience, has the potential to yield negative outcomes for the firm.

Authors

Publication Details

Journal
Journal of Business Research
Published
2025-01-29
DOI
https://doi.org/10.1016/j.jbusres.2024.115158
Citations
6
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
14.89
Controls
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article

Language translation effects in Chatbots: Evidence from a randomized field experiment on a mobile commerce platform

Anju V. Nair, Aditya R. Nayak
6 citations
Journal of Business Research
AI in Service Interactions
14.89
article

Language translation effects in Chatbots: Evidence from a randomized field experiment on a mobile commerce platform

Anju V. Nair, Aditya R. Nayak
article en
6 citations

Abstract

• Research Focus: Investigates the impact of language localization in AI chatbots on user behavior in a mobile platform in India. • Theoretical Framework: The TAM, UTAUT, and CLT are used to explain user interactions with language-switching chatbots. • Methodology: Experiment where users were assigned to an English-only or bilingual version to evaluate changes in purchases and uninstalls. • Key Findings: Localization boosts purchases (+87%) but increases uninstalls (+76%), ideal for simple products, risky for complex ones. This study investigates the impact of language translation innovations in artificial intelligence (AI) digital assistants. We use data from a mobile com- merce platform application in India that introduced a Hindi and English version of its previously English-only language chatbot. The data, obtained from a randomized field experiment conducted on new users, help determine the impact of introducing language translation in conversational chatbots by quantifying its effect on user metrics such as purchases and uninstalls. In the experiment, the firm only altered the language of interaction, from English- only to Hindi and English. The firm did not make any other changes in the design or purchase flow within the application. We find that language trans- lation innovations significantly increase the number of user sessions and also improve user purchases and engagement. The increase in the engagement did not emerge from an increase in the number of sessions but from an increase in interactions within a session in the bilingual app. We also observe a sharp rise in uninstalls for the population that received the bilingual app. We find that in the bilingual chatbot, uninstalls rise with increased user interactions in a high involvement product category. In sum, the results from the field experiment show that while language translation in artificially intelligent as- sistants leads to greater purchases, it could also lead to increased uninstalls. This result suggests that implementing similar language translation innova- tions in isolation, without any modifications to in-application experience, has the potential to yield negative outcomes for the firm.

Journal of Business ResearchVol. 190
Openalex Percentile: Top 1%
AI in Service Interactions
14.89
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