Author: Rick F. van der Lans
Date: June 2018
Which organization doesn’t want a perfect 360-degree view of their customers? One click on a button, and everything that’s known about a customer is shown. Every organization wants this. But how? In this second article in a series on use cases of data virtualization we describe how this technology can help create this perfect view.
The 360-Degree Customer View
Let’s explain the term 360-Degree Customer View first. This article contains a very suitable description: “A 360-degree view of the customer is a single, end-to-end picture of the customer’s journey and experience with a company, and how they felt at steps along the journey. […] enabling […] a unified view of all customer touch points with all departments involved in customer relationships.”
Creating such a unified view can be a real challenge. Customer data is commonly spread out across diverse systems developed with different data storage technologies. Additionally, we can run into semantic issues, systems may use inconsistent definitions for customer or related business concepts. Also, the quality of customer data coming from separately developed systems can differ enormously. And don’t forget we have to deal with customer data that is created externally, for example, in social media or by companies specializing in collecting socio-demographic data.
Creating a 360-Degree Customer View the Old Way
The old way of creating a unified view is to physically copy the customer data from all the source systems and storing it in a separate data store. Next, the data is processed, cleansed, and then made available for reporting and analysis. Sounds easy and straightforward, but it isn’t.
As we all know, new customer data is being produced continuously. Customers buy new products, call the call center with questions and complaints, tweet about our products, search for products on our website, return products, and so on. Because the customer data is not continuously copied but periodically before it’s integrated, it’s never up to date. Don’t be surprised if the latency is a full day. This is not a big problem for reports and dashboards showing overall views of customer data.
The Need for Zero-Latency 360-Degree Customer Views
Although users may have been content with working with yesterday’s unified view of the customer data, for many this is not acceptable anymore. Increasingly, they want to see what’s happening right now. This high data latency issue can be an insurmountable problem for many forms of customer data usage, such as the following ones:
- An app running on a mobile device that allows customers to see all the data we have on them, must show up-to-date data. For example, it’s not desirable when a customer orders a product via the website and doesn’t see that order appear in his app a few seconds later. He will wonder whether the order came through.
- Analyzing Twitter messages together with internal customer data allows us to detect whether the company or one of the brands is poorly assessed on Twitter. We can react as quickly as possible to minimize damage. If the only option we have is to access a customer database in which the data contains yesterday’s data, we may be too late.
- Call centers probably want to see the most up-to-date view of all the customer data to be able to answer questions from customers related to actual issues.
Using Data Virtualization to Create a 360-Degree Customer View
Data virtualization servers have all the features on board to present an integrated and zero-latency view of all the customer data without the need to physically copy data first:
- Customer data from all the different data sources can be integrated on-demand resulting in business users seeing zero-latency customer data. If zero-latency data is not needed or when data cannot be integrated from a specific source live, data can be cached.
- Data security features are supported to specify in detail which customers and business users are allowed to see which part of all that sensitive customer data.
- Data virtualization servers can expose customer data through all kinds of APIs and languages, allowing a wide range of technologies to access the data, from traditional reporting tools using SQL to Java apps running on mobile devices using JSON/REST.
- Complex integration operations can be specified in the virtual tables, allowing data to be presented in almost any form. Additionally, for different business users different views of the customer data can be developed. Note that no physical data duplication is required.
- With all the new regulations for data privacy and protection, and especially for customer-related data, storing customer data in a multitude of systems is strongly discouraged. Don’t forget that customers have the “right to be forgotten”. The less we store, the easier it is to conform to these new regulations. Data virtualization means less physical copies.
The business value of a 360-degree view of customer data is not in doubt, by no one. The question is what the right architecture and technology is to create this 360-degree view out of this heterogeneous myriad of systems all containing customer data. Data virtualization is a strong contender. The old approach works, but shows out-of-date data and is unacceptable for more and more forms of customer data usage. Data virtualization supports on-demand integration making it possible to show zero-latency data, in other words, it allows to show what’s happening now and not what happened yesterday.
In the third article of this series [link to next article], we focus on the use case of data virtualization that’s is receiving a lot of attention lately, namely the logical data warehouse architecture. This architecture is a more flexible alternative to the more traditional data warehouse architecture.