Hyperfocused Customer Insights Based On Graph Analytics And Knowledge Graphs

Authors

  • Sarbaree Mishra Program Manager at Molina Healthcare Inc., USA Author
  • Vineela Komandla Vice President - Product Manager, JP Morgan Author
  • Srikanth Bandi Software Engineer, JP Morgan Chase, USA, USA Author

Keywords:

Graph Analytics, Personalization, Data-Driven Decisions

Abstract

Businesses increasingly rely on graph analytics and knowledge graphs to uncover deeper customer insights. These advanced tools enable companies to map relationships between various data points, revealing hidden patterns and connections that traditional analytical methods often miss. By leveraging graph analytics, businesses gain a clearer understanding of customer behaviour, allowing for more personalized experiences and targeted strategies. Knowledge graphs take this further by organizing complex data into an easily accessible and structured format, providing a comprehensive view of how different elements interact. This allows companies to understand the broader context of customer interactions, moving beyond isolated data points to uncover the relationships that drive customer actions. With these insights, businesses can predict future behaviours, anticipate customer needs, and make more informed decisions. The applications of graph analytics and knowledge graphs span across industries, from improving customer service and marketing campaigns to enhancing product development and sales forecasting. For example, companies can use graph analytics to identify trends and recommend products that align with customers' preferences, boosting engagement and sales. By organizing and connecting data from various sources, knowledge graphs enable businesses to see the big picture and make strategic decisions that improve the overall customer experience. Moreover, the insights gained through these technologies help companies to stay ahead of the competition, making proactive decisions based on data rather than relying on reactive approaches. In essence, graph analytics and knowledge graphs transform raw data into actionable insights, providing companies with the tools to understand their customers better, predict future behaviours, and create more personalized, effective business strategies. This shift from fundamental data analysis to a deeper, more connected understanding of customer behaviour marks a significant step in how businesses engage with their audience and make data-backed decisions.

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References

Loshin, D. (2013). Big data analytics: from strategic planning to enterprise integration with tools, techniques, NoSQL, and graph. Elsevier.

Arthur, L. (2013). Big data marketing: engage your customers more effectively and drive value. John Wiley & Sons.

Graham, H. (2018). Marketing to life scientists: Fact and fiction from the frontlines.

Olson, C., & Levy, J. (2018). Transforming marketing with artificial intelligence. Applied Marketing Analytics, 3(4), 291-297.

Fader, P., & Toms, S. E. (2018). The customer centricity playbook: Implement a winning strategy driven by customer lifetime value. University of Pennsylvania Press.

Gemignani, Z., Gemignani, C., Galentino, R., & Schuermann, P. (2014). Data fluency: Empowering your organization with effective data communication. John Wiley & Sons.

Upadhyay, S., & McCormick, K. (2018). The Revenue Acceleration Rules: Supercharge Sales and Marketing Through Artificial Intelligence, Predictive Technologies and Account-Based Strategies. John Wiley & Sons.

David, L. (2013). Big Data Analytics From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph.

Suwelack, T., Stegemann, M., & Ang, F. X. (2022). Creating a Customer Experience-Centric Startup. Springer International Publishing.

West, M. (2019). People analytics for dummies. John Wiley & Sons.

Kaufman‐Scarborough, C., & Cohen, J. (2004). Unfolding consumer impulsivity: An existential–phenomenological study of consumers with attention deficit disorder. Psychology & Marketing, 21(8), 637-669.

Olson, A. B. (2022). What to Ask: How to Learn what Customers Need But Don't Tell You. BenBella Books.

Misirlis, N. (2019). Social media behavior analysis: exploring the paradigm in eHealth.

Marincolo, S. (2010). High: Insights on marijuana. Dog Ear Publishing.

Burgess, C. (2020). The new marketing: how to win in the digital age.

Thumburu, S. K. R. (2022). A Framework for Seamless EDI Migrations to the Cloud: Best Practices and Challenges. Innovative Engineering Sciences Journal, 2(1).

Thumburu, S. K. R. (2022). AI-Powered EDI Migration Tools: A Review. Innovative Computer Sciences Journal, 8(1).

Gade, K. R. (2022). Cloud-Native Architecture: Security Challenges and Best Practices in Cloud-Native Environments. Journal of Computing and Information Technology, 2(1).

Gade, K. R. (2022). Data Analytics: Data Fabric Architecture and Its Benefits for Data Management. MZ Computing Journal, 3(2).

Katari, A., Muthsyala, A., & Allam, H. HYBRID CLOUD ARCHITECTURES FOR FINANCIAL DATA LAKES: DESIGN PATTERNS AND USE CASES.

Katari, A. Conflict Resolution Strategies in Financial Data Replication Systems.

Komandla, V. Enhancing Security and Growth: Evaluating Password Vault Solutions for Fintech Companies.

Komandla, V. Strategic Feature Prioritization: Maximizing Value through User-Centric Roadmaps.

Thumburu, S. K. R. (2021). EDI Migration and Legacy System Modernization: A Roadmap. Innovative Engineering Sciences Journal, 1(1).

Thumburu, S. K. R. (2021). Transitioning to Cloud-Based EDI: A Migration Framework, Journal of Innovative Technologies, 4(1).

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Published

16-10-2023

How to Cite

[1]
Sarbaree Mishra, Vineela Komandla, and Srikanth Bandi, “Hyperfocused Customer Insights Based On Graph Analytics And Knowledge Graphs”, J. of Artificial Int. Research and App., vol. 3, no. 2, pp. 1172–1193, Oct. 2023, Accessed: Dec. 27, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/323

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