Using graphs to model and analyze the customer journey
A conceptual guide to getting started
In today’s landscape of voluminous data, complex customer interactions, and Machine Learning models (for recommendations and propensities), understanding the customer journey is paramount for ultimate business success. Traditional databases are an option for supporting this understanding — but at some point, they lack the efficiency to do so in a simple manner and at scale.
Graph technology has become a more suitable and powerful option to promote this understanding, its growth being driven by the affordability and improvement of cloud computing and related technology. Graphs are undoubtedly the choice for modeling and visualizing complex data and relationships.
The goal of this article is to help you and your business start thinking about how graphs can be used to understand the journey among your customers. The information presented here is not meant to serve as an in-depth guide for building a graph platform — that will come later in this multi-article series. Instead, conceptual details are presented, and some high-level code is shared.
By leveraging a graph structure and moving to an unstructured format for our customer journey data and relationships, our team has been able to identify and explore the actions…
