Skip to main content
Springer Nature Link
Log in

Sentimental Analytics on Indian Big Billion Day of Flip Kart and Amazon

  • Original Research
  • Published:
SN Computer Science Aims and scope Submit manuscript

Abstract

Millennials are raised in a gadget-filled and highly networked marketing environment and received a great deal of attention from the marketers for being very optimistic and open to different digital products. Millennials look not for just products but a whole new customer experience while they shop online. The probability of winning millennial customer sentiment is logical if the marketer attempts behavioural marketing strategies through multiple online channels. Though there are many versions of the age group of millennials, they are dexterous in comprehending various interfaces and visual cues which enables the marketers reach out to them cost-effectively unlike interacting with Gen X and Y who need aggressive marketing communication. In this context, people-based personalised approach to attract the millennials becomes imperative as they demand a customized communication style. Moving from breaking the advertising clutter to popularizing a brand online, the marketers have come to a phase where they are forced to break the clutter to reconquer the millennial on digital podia. The paper involves the application of appropriate analytics-based statistical tools on primary data from the millennial samples to appreciate the effectiveness of such communication in establishing individual human connections on online selling e-marketers. Thus, based on 5000 twitters driven from Twitter platform a sentiment analytics results to explore that Amazon performed better than Flipkart during Big Billion Day Sales 2019 in India. For this text/opinion mining is performed on tweets extracted from on Tweeter platform. Further analysis also imbibed Fine-grained and Aspect based Sentiment Analysis along with Rule-based approach in sentiment analytics for better understanding of sentiments and emotions on online buying behaviour.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Alim A, Shukla D (2020) A big data parameter estimation approach to develop big social data analytics framework for sentiment analysis. Soc Netw Comput Intell Springer, Singapore, pp. 755–764

  2. Apampa O (2020) Using big data analytics to enhance consumers’ sustainable purchase decision-making of groceries online.

  3. Belleau BD, Summers TA, Xu Y, Pinel R. Theory of reasoned action purchase intention of young consumers. Cloth Tex Res J. 2007;25(3):244257.

    Google Scholar 

  4. Donnelly C, Scaff R. Who are the millennial shoppers? And what do they really want. Accent Outlook. 2013;2:1–7.

    Google Scholar 

  5. Cassidy S (2017) Millennial generation's impact on small business marketing landscapes.

  6. Lingelbach D, Patino A, Pitta DA. The emergence of marketing in Millennial new ventures. Consum Market. 2012;29(2):136–45.

    Article  Google Scholar 

  7. Lantor GP. Marketing to millennials: reach the largest and most influential generation of consumers ever. J Consum Market. 2014;31(5):401–3.

    Article  Google Scholar 

  8. Kumar TM, Murugeswari R, Devaraj D, Hemalatha J (2020) Comparison of deep learning and random forest for rumor identification in social networks. In: International conference on innovative computing and communications. Springer, Singapore pp. 133–146

  9. Moore M. Interactive media usage among millennial consumers. J Consum Market. 2012;29(6):436–44.

    Article  Google Scholar 

  10. McPherson S (2016) How Millennials are changing the face of retail shopping. https://www.aabacosmallbusiness.com/advisor/millennialschanging-face-retail-shopping-025220847.html.

  11. Nimon S. Generation Y and higher education: the" other" Y2K. J Inst Res. 2007;13(1):24–41.

    Google Scholar 

  12. Nimon S. Generation Y and higher education: the other Y2K. J Inst Res. 2007;13(1):24–41.

    Google Scholar 

  13. Liu Q, Zhang X, Huang S, Zhang L, Zhao Y. Exploring consumers’ buying behavior in a large online promotion activity: the role of psychological distance and involvement. J TheorAppl Electron Comm Res. 2020. https://doi.org/10.4067/S0718-18762020000100106.

    Article  Google Scholar 

  14. Li K, Chen Y, Zhang L. Exploring the influence of online reviews and motivating factors on sales: a meta-analytic study and the moderating role of product category. J Retail ConsumServ. 2020;55:102107.

    Article  Google Scholar 

  15. Plazibat I, Dadić M, Petričević D (2017) Do the millennials make a difference in retail. Theory Appl Knowl Econ 186.

  16. Surveying Strategy. Research tactics for engaging millennials—white paper, Kelton Global, 2013.

  17. Supermarket and Retailer. SA retailers urged to adopt e-commerce to retain clients. 2013 [Accessed 2 August 2016].

  18. Smirnova A. Use of personal data in digital advertising: Study of Millennials’ Attitudes. 2018

  19. Sisodia DS, Reddy R. Analysis of public sentiments about mega online sale using tweets on big billions day sale. In: Sentiment analysis and knowledge discovery in contemporary business (pp. 59–76). IGI Global. 2019

  20. The millennial generation is changing the face of consumer marketing, January 15th, 2014, BCG press release.

  21. Varma M, Kumar V, Sangvikar B, Pawar A. Impact of social media, security risks and reputation of e-retailer on consumer buying intentions through trust in online buying: a structural equation modeling approach. J Crit Rev. 2020;7(1):119–27.

    Google Scholar 

  22. William AJ, Arulraj A. A study on customer behaviour on big billion day sale on flipkart with reference to Coimbatore. J Gujarat Res Soc. 2019;21(2):452–60.

    Google Scholar 

Download references

Funding

There exists no funding for this study from any source.

Author information

Authors and Affiliations

  1. Amity Business School, Amity University Mumbai, Navi Mumbai, Mumbai, India

    Pushpendu Rakshit

  2. Galgotias University, Greater Noida, Uttar Pradesh, India

    Pramod Kumar Srivastava

  3. Amity Business School, Amity University Mumbai, Navi Mumbai, Mumbai, India

    Mohd Afjal

  4. School of Business, Galgotia University, Greater Noida, Uttar Pradesh, India

    Shailendra Kumar Srivastava

Authors
  1. Pushpendu Rakshit
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Pramod Kumar Srivastava
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Mohd Afjal
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Shailendra Kumar Srivastava
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Pushpendu Rakshit.

Ethics declarations

Conflict of interest

Author A [Dr. Pramod Kumar Srivastava] declares that he/she has no conflict of interest. Author B [Dr. Pushpendu Rakshit] declares that he/she has no conflict of interest. Author C [Dr. Mohd Afjal] declares that he/she has no conflict of interest. Author D [Dr. Shailendra Kumar Srivastava] declares that he/she has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the topical collection “Computational Statistics” guest edited by Anish Gupta, Mike Hinchey, Vincenzo Puri, Zeev Zalevsky and Wan Abdul Rahim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rakshit, P., Srivastava, P.K., Afjal, M. et al. Sentimental Analytics on Indian Big Billion Day of Flip Kart and Amazon. SN COMPUT. SCI. 2, 204 (2021). https://doi.org/10.1007/s42979-020-00441-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s42979-020-00441-3

Keywords