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Graph-Powered Analytics and Machine Learning with TigerGraph
book

Graph-Powered Analytics and Machine Learning with TigerGraph

by Victor Lee, Phuc Kien Nguyen, Alexander Thomas
July 2023
Intermediate to advanced
314 pages
8h 28m
English
O'Reilly Media, Inc.
Content preview from Graph-Powered Analytics and Machine Learning with TigerGraph

Chapter 3. See Your Customers and Business Better: 360 Graphs

This chapter will employ some real-world use cases to illustrate two of the six graph powers that we discussed in the previous chapter: “Connecting the Dots” and the “The 360 View”. The 360 view offered by graphs helps enterprises and agencies see their data more comprehensively, which in turn enables better analytics. In the first use case, we build a Customer 360 (C360) graph to enable a company to track and understand presales customer journeys. In the second case, we build a Drug Interaction 360 graph so researchers can develop safer drug therapies.

After completing this chapter, you should be able to:

  • Define the term C360 and explain its value proposition

  • Know how to model and analyze customer journeys in a graph

  • Know how to use graph analytics to count and filter properties and relationships

  • Set up and run a TigerGraph Cloud Starter Kit using GraphStudio

  • Read and understand basic GSQL queries

Case 1: Tracing and Analyzing Customer Journeys

A business is nothing without sales. Selling, whether to consumers (B2C) or to other businesses (B2B), has become not only an art but also a science. Businesses analyze every stage of their interactions with a prospect (a potential customer) from beginning to end, hopefully resulting in a sale. According to Gartner, worldwide spending on customer relationship management (CRM) software increased by 15.6% in 2018 to reach $48.2 billion in 2020.1 Salesforce has established ...

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Publisher Resources

ISBN: 9781098106645Errata Page