Artificial Intelligence-Based Consumer Communication by Brick-and-Mortar Retailers in India Leading to Syllogistic Fallacy and Trap – Insights from an Experiment

H. R., Ganesha and Aithal, Sreeramana (2020): Artificial Intelligence-Based Consumer Communication by Brick-and-Mortar Retailers in India Leading to Syllogistic Fallacy and Trap – Insights from an Experiment. Published in: International Journal of Applied Engineering and Management Letters (IJAEML) , Vol. 4, No. 2 (15 December 2020): pp. 211-221.

Abstract

It is observed that a majority of organized brick-and-mortar (B&M) retailers in India believe that they have adopted the latest Artificial Intelligence-based consumer communication (AIBCC) tools/solutions and are yielding accurate outputs that can be used for interpretation, conclusion, and decision-making concerning consumer communications. This belief/assumption in itself is a classic example of a syllogistic trap. This study reveals that the B&M retailers in India are least worried about AIBCC tools/solutions repeatedly sending promotional/campaign messages to consumers based on their past transactional data till they come back again to the store without knowing the ‘Purpose of Previous Purchase’. This is mere because the cost of such communications is negligible (Just costs about 1 US dollar for sending 500 messages to a mobile phone number). We have also observed that the B&M retailers are unaware of the potential negative impacts of false/fake/artificial promotional/campaign messages being sent to consumers as a result of syllogistic fallacy caused by the AIBCC tools/solutions on the overall brand image in the consumers’ minds. Experimentation results demonstrate that the existing belief of the organized B&M retailers in India which assumes that the AIBCC tools/solutions are accurate is just a misconception and does not hold. On the other hand, when we experimented by identifying two main gaps (input and output-level) in their existing AIBCC tool/solution for six months at over 35 percent stores of a select retailer, the real treatment effect indicated that the experimental group of stores has shown (i) two times higher rate of conversion to any promotional/campaign messages; (ii) 19 times better in capturing the ‘Purpose of Purchase’ field; (iii) 22% lesser consumer communication expenses; (iv) 22.80% higher revenue generation; and most importantly; (v) 4.25 times higher store-level profits in comparison with the control group of stores. We have also noted that in the control group of stores about 36% of the customers/consumers who have received the promotional/campaign messages from the automated AIBCC tool/solution were not real consumers. Besides finding evidence of the syllogistic fallacy and trap, our results are also consistent with our ‘Theory of B&M Retailing in India and the concept of ‘Debiasing by Instruction’ by Evans et al.

• Item Type: MPRA Paper
• Language: English
• Keywords: Indian Retail; Brick-and-Mortar Retail; Artificial Intelligence; Digital Analytics; Consumer Communication; Syllogistic Trap; Syllogistic Fallacy; Customer Relationship Management; CRM
• Subjects: M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M1 - Business Administration > M15 - IT Management; M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M3 - Marketing and Advertising > M31 - Marketing; M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M3 - Marketing and Advertising > M39 - Other

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