Connecting ‘Bharat’ Online: An AI Framework of 4Vs — Voice, Video, Visual, Vernacular — for Customer Acquisition in Tier 2–3 E-Commerce
DOI:
https://doi.org/10.66635/bwky2872Keywords:
AI-enabled e-commerce, 4Vs framework, Tier 2 and Tier 3 cities, customer acquisition, vernacular commerceAbstract
Customer acquisition in e-commerce in India will soon be increasingly led by consumers in tier 2 and tier 3 towns referred to as 'Bharat'. However, there exist several barriers faced by this emerging consumer base, which includes, among others, language barriers, lack of digital literacy, text-heavy platforms, products not being well-understood, concerns of online trust and risk, and shopping cart abandonment issues. This paper reviews the adoption barriers faced by Bharat e-commerce customers and proposes the use of an AI-driven 4Vs (Voice, Video, Visual, and Vernacular) framework to facilitate acquisition of this new customer segment. Voice assistants and voice search technologies enable reduced reliance on typing and navigation, video commerce enhances understanding of the product through demonstrations and live interaction, visual tools like image search and augmented reality make customers less reliant on text and helps bridge the missing touch-and-feel barrier, and vernacular tools enhance trust via a more relatable means of interaction. The paper highlights e-commerce adoption literature, online trust and risk, shopping cart abandonment, voice assistants, video commerce, visual commerce, and localized communications. This paper seeks to contribute to e-commerce literature by offering a framework which incorporates AI-powered tools to facilitate customer acquisition.
References
1.Singh, A., Bothra, V., Sen, A., & Chakraborty, D. (2025). Navigating the Digital Marketplace: Understanding the E-Commerce Adoption Journey of Emergent Users in India. Proceedings of the ACM on Human-Computer Interaction, 9(5), 1-39.
2.Aeron, P., Jain, S., & Kumar, A. (2019). Revisiting trust toward E-retailers among Indian online consumers. Journal of Internet Commerce, 18(1), 45-72.
3.Sengupta, A., Das, S., Akhtar, M. S., & Chakraborty, T. (2024). Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media. Humanities and Social Sciences Communications, 11(1), 1-12.
4.Sharma, A., & Mittal, N. (2020). Analysis of Success of Digital Marketing Using Vernacular Contents. In Innovations in Computer Science and Engineering: Proceedings of 7th ICICSE (pp. 155-163). Singapore: Springer Singapore.
5.Mahesh, K. M., Aithal, P. S., & Sharma, K. R. S. (2022). Open Network for Digital Commerce-ONDC (E-Commerce) Infrastructure: To promote SME/MSME sector for inclusive and sustainable digital economic growth. International Journal of Management, Technology, and Social Sciences (IJMTS), 7(02), 320-340.
6.Tiwari, R., Rastogi, S., Kothari, R., Dungarwal, L., Bhootra, D., & Preksha, J. (2024). The Impact of Open Network Digital Commerce (ONDC) on India’s E-Commerce Ecosystem. International Journal of Research, 11(3).
7.Bălan, C. (2023). Chatbots and voice assistants: digital transformers of the company–customer interface—a systematic review of the business research literature. Journal of Theoretical and Applied Electronic Commerce Research, 18(2), 995-1019.
8.Sidlauskiene, J., Joye, Y., & Auruskeviciene, V. (2023). AI-based chatbots in conversational commerce and their effects on product and price perceptions: J. Sidlauskiene et al. Electronic Markets, 33(1), 24.
9.Kaur, G., Panwar, A., & Kaur, J. (2025). Voice Commerce: Current Landscape, Key Drivers and Future Prospects in the Indian Market. International Research Journal of Humanities and Interdisciplinary Studies, 6(4), 119-131.
10.Venkatakrishnan, J., Alagiriswamy, R., & Parayitam, S. (2024). Disentangling the relationship between trust, online buying, and customer satisfaction: a three-way interaction model. Journal of Marketing Analytics, 12(4), 806-828.
11.Misra, R., Mahajan, R., Singh, N., Khorana, S., & Rana, N. P. (2022). Factors impacting behavioural intentions to adopt the electronic marketplace: findings from small businesses in India. Electronic markets, 32(3), 1639-1660.
12.Luceri, B., Bijmolt, T. T., Bellini, S., & Aiolfi, S. (2022). What drives consumers to shop on mobile devices? Insights from a Meta-Analysis. Journal of Retailing, 98(1), 178-196.
13.Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8-22.
14.Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior, 86, 109-128.
15.Shukla, M., Jain, V., & Misra, R. (2022). Factors influencing smartphone based online shopping: an empirical study of young Women shoppers. Asia Pacific Journal of Marketing and Logistics, 34(5), 1060-1077.
16.Shree, S., Pratap, B., Saroy, R., & Dhal, S. (2021). Digital payments and consumer experience in India: a survey based empirical study. Journal of Banking and Financial Technology, 5(1), 1-20.
17.Padma Kiran, K., & Vedala, N. S. (2025). Assessing Unified Payments Interface (UPI) adoption and usage through the interplay of UTAUT factors. Humanities and Social Sciences Communications, 12(1), 1060.
18.Kakkar, A., Kalia, P., Panesar, A., & Sood, R. (2025). Investigating the impact of quality, technology and trust on customers’ purchase intention and word-of-mouth in S-commerce. Aslib Journal of Information Management.
19.Chawla, N., & Kumar, B. (2022). E-commerce and consumer protection in India: the emerging trend. Journal of Business Ethics, 180(2), 581-604.
20.Clemons, E. K., Wilson, J., Matt, C., Hess, T., Ren, F., Jin, F., & Koh, N. S. (2016). Global differences in online shopping behavior: Understanding factors leading to trust. Journal of Management Information Systems, 33(4), 1117-1148.
21.Ingham, J., Cadieux, J., & Berrada, A. M. (2015). e-Shopping acceptance: A qualitative and meta-analytic review. Information & Management, 52(1), 44-60.
22.Ganguly, B., Dash, S. B., Cyr, D., & Head, M. (2010). The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture. International Journal of Electronic Business, 8(4-5), 302-330.
23.Suurmaa, P. (2021). The impact of website design on e-loyalty through customers’ trust and satisfaction.
24.Kukar-Kinney, M., & Close, A. G. (2010). The determinants of consumers’ online shopping cart abandonment. Journal of the Academy of Marketing Science, 38(2), 240-250.
25.Huang, G. H., Korfiatis, N., & Chang, C. T. (2018). Mobile shopping cart abandonment: The roles of conflicts, ambivalence, and hesitation. Journal of Business Research, 85, 165-174.
26.Ha, N. T., Nguyen, T. L. H., Nguyen, T. P. L., & Nguyen, T. D. (2019). The effect of trust on consumers’ online purchase intention: An integration of TAM and TPB. Management Science Letters, 9(9), 1451-1460.
27.Mou, J., Shin, D. H., & Cohen, J. F. (2017). Trust and risk in consumer acceptance of e-services. Electronic Commerce Research, 17(2), 255-288.
28.Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2022). Understanding the drivers of online trust and intention to buy on a website: An emerging market perspective. International Journal of Information Management Data Insights, 2(1), 100065.
29.Kukar-Kinney, M., Scheinbaum, A. C., Orimoloye, L. O., Carlson, J. R., & He, H. (2022). A model of online shopping cart abandonment: evidence from e-tail clickstream data. Journal of the Academy of Marketing Science, 50(5), 961-980.
30.Wang, S., Ye, Y., Ning, B., Cheah, J. H., & Lim, X. J. (2022). Why do some consumers still prefer in-store shopping? An exploration of online shopping cart abandonment behavior. Frontiers in Psychology, 12, 829696.
31.Regina, A. L. V., & Munasinghe, M. A. T. K. (2022). The dilemma of information overload: A review of literature from accounting and finance related studies. South Asian Journal of Finance, 2(2).
32.Rawool, V., Foroudi, P., & Palazzo, M. (2025). AI-powered voice assistants: developing a framework for building consumer trust and fostering brand loyalty. Electronic Commerce Research, 25(6), 4471-4503.
33.Fernandes, T., & Oliveira, E. (2021). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180-191.
34.Moriuchi, E. (2019). Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. Psychology & Marketing, 36(5), 489-501.
35.McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in human behavior, 99, 28-37.
36.Gnewuch, U., Morana, S., & Maedche, A. (2017). Towards designing cooperative and social conversational agents for customer service.
37.Hoy, M. B. (2018). Alexa, Siri, Cortana, and more: an introduction to voice assistants. Medical reference services quarterly, 37(1), 81-88.
38.Jain, P., & Bhowmick, A. (2025). Analyzing code-switching scenarios in india’s diverse linguistic landscape using end-to-end asr systems with vitb-hebic. Computers and Electrical Engineering, 122, 109978.
39.Toshniwal, S., Sainath, T. N., Weiss, R. J., Li, B., Moreno, P., Weinstein, E., & Rao, K. (2018, April). Multilingual speech recognition with a single end-to-end model. In 2018 IEEE international conference on acoustics, speech and signal processing (ICASSP) (pp. 4904-4908). IEEE.
40.Tsiourti, C., Ben Moussa, M., Quintas, J., Loke, B., Jochem, I., Lopes, J. A., & Konstantas, D. (2016, September). A virtual assistive companion for older adults: design implications for a real-world application. In Proceedings of SAI intelligent systems conference (pp. 1014-1033). Cham: Springer International Publishing.
41.Li, J., Chen, C., Azghadi, M. R., Ghodosi, H., Pan, L., & Zhang, J. (2023). Security and privacy problems in voice assistant applications: A survey. Computers & Security, 134, 103448.
42.Hu, M., & Chaudhry, S. S. (2020). Enhancing consumer engagement in e-commerce live streaming via relational bonds. Internet Research, 30(3), 1019-1041.
43.Yim, M. Y. C., Chu, S. C., & Sauer, P. L. (2017). Is augmented reality technology an effective tool for e-commerce? An interactivity and vividness perspective. Journal of interactive marketing, 39(1), 89-103.
44.Lou, C., Zhou, X., Huang, X., Xin Yun, G., Yan Jie, L., Kin Tat Bryan, L., & Xin Rong, P. (2023). Flattering me in the right way: exploring language use and ethnic cues in localized advertising among Singaporean consumers. Journal of Interactive Advertising, 23(1), 55-72.
45.Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the academy of marketing science, 49(1), 30-50.
46.Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the academy of marketing science, 48(1), 24-42.
47.Sun, Y., Shao, X., Li, X., Guo, Y., & Nie, K. (2019). How live streaming influences purchase intentions in social commerce: An IT affordance perspective. Electronic commerce research and applications, 37, 100886.
48.Qin, H., Peak, D. A., & Prybutok, V. (2021). A virtual market in your pocket: how does mobile augmented reality (MAR) influence consumer decision making? Journal of Retailing and Consumer Services, 58, 102337.
49.Singh, N., & Matsuo, H. (2004). Measuring cultural adaptation on the Web: a content analytic study of US and Japanese Web sites. Journal of Business Research, 57(8), 864-872.



