Datanaya's Customer 360 Unifies Data and Boosts Enterprise Loyalty
The Problem
When data is fragmented, businesses can't get at the customer insight they need. Whether it's to increase profit, cut costs, provide a better service, or make predictions about future behaviour, understanding customer data is critical.

Today's digital processes amass large volumes of data and information is often stored in many different places and formats. Powerful analysis and visualization tools are needed to make sense of this data and turn it into something useful – graph visualization is key to that process.

The Solution
Customer 360 makes complex data easy to explore and understand.

Customer 360 is a proprietary solution that uses graph visualization to collect and refine data about customer interactions to reveal useful business insights. It 'virtually' brings-together data from across the enterprise and performs small-scale entity resolution in the front-end.

The uses for Customer 360 vary from industry to industry.

· Healthcare firms can manage patient complaints and understand medical referrals.

· Insurance companies can investigate fraud and perform compliance activities.

· Retailers can reduce customer churn, modernize data architecture, and find up-sell opportunities.

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

· Customer demographics – 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
How it looks in action
Businesses map the entire customer journey through a collection of thousands of data points. This data then needs to be made useful for two distinct audiences.

· Customer-facing agents – requires fast insight to manage specific customer interactions like understanding past behaviour to inform the next best action or identifying complaint patterns to prevent churn.

· Data analysts and management – requires a birds-eye view of many customers simultaneously in order to aggregate data, see correlations in behaviour, make predictions to reduce risks, and discover opportunities to exploit.

Superior Features:

· Fast knowledge transfer

With node-link technology, analysts and customer-facing agents can easily interpret large volumes of data and communicate complex scenarios in an intuitive way, even in a time-pressured environment.

· Flexible data model

Graph visualization offers endless flexibility to extract value from any connected data set.

A single tool can be used across different data sets, by different teams, asking different questions.

· Micro and macro viewpoints

Gain a deep understanding of patterns, trends, and correlations in large volumes of customer data through a high-level viewpoint, specific detailed connection, or a combination of both.