Skip to main content

Data Visualization: Visualization of Social Media Marketing Analysis Data to Generate Effective Business Revenue Model

Abstract

Right from its inception, social media has played a pivotal role in shaping the marketing strategies of today’s business. Businesses use marketing to successfully grow their market presence and improve brand awareness. The most effective marketing approach is one where social media and traditional marketing mixes are used in tandem. Social media marketing is a lucrative option for business owners as the cost of marketing is low and user feedback on social media Web sites and forums can be utilized effectively to constantly update the marketing strategy for maximizing gains. This chapter focuses on analyzing the Facebook marketing strategy of a certain company and providing a comparative study of visualization methodologies that present the client sentiment in the most lucid manner, thereby allowing the business owner to devise an effective business model with maximum returns and minimum expenditure.

Keywords

  • Data visualization
  • Social media
  • Market analysis
  • Facebook advertisement
  • Click-response
  • Business expansion

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-981-15-2282-6_5
  • Chapter length: 18 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-981-15-2282-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Hardcover Book
USD   159.99
Price excludes VAT (USA)
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

References

  1. Ringel, D. M., & Skiera, B. (2018). 19. visualizing asymmetric competitive market structure in large markets1. Handbook of marketing analytics: methods and applications in marketing management, public policy, and litigation support (p. 431).

    Google Scholar 

  2. Gründemann, T., & Burghardt, D. (2018). Classifying and visualizing the social facet of location-based social network data. In VGI Geovisual Analytics Workshop, colocated with BDVA 2018.

    Google Scholar 

  3. Hou, X., & Sourina, O. (2016). Real-time adaptive prediction method for smooth haptic rendering. arXiv preprint arXiv:1603.06674.

  4. Christopher, G. H. (1996). Choosing effective colours for data visualization. In Proceedings of the IEEE Conference on Visualization (pp. 263–270).

    Google Scholar 

  5. Tukey, J. W. (1962). The future of data analysis. The Annals of Mathematical Statistics, 33(1), 1–67.

    MathSciNet  CrossRef  Google Scholar 

  6. Bangay, S. Visview: A system for the visualization of multi-dimensional data. In Visual Data Exploration and Analysis V. (TA 1505 Pse 3298).

    Google Scholar 

  7. Foley, J., & Ribarsky, B. Next-generation data visualization tools. In L. Rosenblum, R. A. Earnshaw, J. Encarnacao, H. Hagen, A. Kaufman, S. Klimenko, G. Nielson, F. Post, & D. Thalmann (Eds.), Scientific visualization, advances and challenges. (T385 Sci).

    Google Scholar 

  8. Wong, P. C., Bergeron, R. D., Nielson, G. M., Hagen, H., Muller, H. Scientific visualization, over view, methodologies, techniques. (Q175 Nie.).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. Ramanathan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Chellam, A., Chaturvedi, A., Ramanathan, L. (2020). Data Visualization: Visualization of Social Media Marketing Analysis Data to Generate Effective Business Revenue Model. In: Anouncia, S., Gohel, H., Vairamuthu, S. (eds) Data Visualization. Springer, Singapore. https://doi.org/10.1007/978-981-15-2282-6_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-2282-6_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2281-9

  • Online ISBN: 978-981-15-2282-6

  • eBook Packages: Computer ScienceComputer Science (R0)