Graph visualization for customer 360

Turning customer data into actionable insight

The customer 360 data challenge

Successful businesses need customer insight. Whether it’s to increase profits, cut costs, provide a better service or make predictions about future behavior, understanding customer data is critical.

That’s exactly what ‘customer 360’ is: collecting and refining data about customer interactions to form a single customer view that reveals useful business insight.

As digital processes allow businesses to collect increasing volumes of data, they need powerful analysis and visualization tools to turn it into something useful. Graph visualization is key to that workflow.

Complex customer data is easy to explore and understand with graph visualization

Why customer 360?

The purpose of customer 360 varies from industry to industry.


Healthcare firms want to manage patient complaints and understand medical referrals.


Insurance companies want to investigate fraud and perform compliance activities.


Retailers want to reduce customer churn, modernize data architecture and find up-sell opportunities.

There’s also a growing variety of data available for collection:

  • Demographic data – names, places, ages, etc
  • Buyer history – previous purchases, refunds, deliveries
  • Campaign interaction – emails opened, adverts clicked, discounts redeemed
  • Influence – associations with other customers
  • Communication – emails, calls, social media interactions, complaints filed

Businesses often collect thousands of data points for every customer, covering the entire customer journey. They need to refine this into something useful for two distinct audiences:

Customer-facing agents

This audience needs fast insight into a customer or account to manage specific interactions. They might need to quickly understand previous dealings to help decide on the next best action or identify patterns in complaints to prevent churn.

Data analysts & management

This audience needs a view of many different customers simultaneously. When they understand aggregated data they can see correlations in behavior, make predictions to reduce risks, and uncover opportunities to exploit.

Complex customer data is easy to explore and understand with graph visualization

How does graph visualization help?

Graph visualization is a crucial part of customer 360 workflows.

This webinar follows the full Customer 360 workflow, from source data to visualization, via mapping, entity resolution and data enrichment, including a deep dive into a healthcare use case.

Fast knowledge transfer

The node-link model gives analysts and customer-facing agents an intuitive way to communicate complex scenarios. In a time-pressured environment, they can easily understand large volumes of data and uncover insight.

A flexible model

Graph visualization is a valuable tool for understanding any connected dataset. It’s also flexible, so a single tool can be used across different data sets, by different teams, asking different questions.

Overcome data silos

A big challenge to achieving customer 360 is internal data silos and master data management. Information is often stored in many different places and formats. Graph visualization ‘virtually’ brings together data from across the enterprise, and performs small-scale entity resolution in the front-end.

Powerful ways to bring out patterns

Graph visualization is an ideal way to make sense of customer information. Combining a high-level viewpoint with a detailed dive into specific connections, it’s possible to understand patterns, trends, and correlations in large volumes of customer data.

Why choose us?

At Cambridge Intelligence, we’ve helped organizations including Barclays, CGI, and First Republic Bank to build powerful customer 360 applications. They’ve used our graph visualization toolkits to create data exploration tools, fully customized to their users, data and the questions they need to answer.

If you’d like to try our software for yourself, just request a free trial.

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