If the notion of a rich, reliable customer profile has existed for decades, why do so few companies actually reach a single source of truth about customers?

The trouble is, most customer experience initiatives falter because they think it’s only about the customer. The data is an afterthought. It’s not a complete snubbing of data. There’s recognition of how important data is, but companies stumble in two areas.

What's Causing Customer Data Silos?

A Proliferation of Apps

First, brands have invested in hundreds of applications in response to evolving consumer demands and market conditions. The digitalization of processes has compounded technological complexity as more applications are used to automate (and for good reason) what had typically been manual. The result, however, has been the creation of even more fragments of data about customers.

acceleration of app adoption causing internaldata silos

Silos are a natural outcome of the speed of digitalization, leading to technology sprawl. It's no longer an issue of not enough data. We've got more data than ever. Too much, in fact, and it's coming from new digital applications.

Department-Centric Approaches

Secondly, efforts focus on creating a single source of truth for customer data within a department. If everyone builds a single customer view for their own purposes, then no one has a single customer view. What is created instead are multiple views of a single customer: one in marketing, one in sales, one in services, one in operations and so on. Which only recreates the problem we were trying to solve.

It’s nearly impossible to keep those multiple views consistent without the data that forms them being fed from a single source. And when there are multiple views without a central place to manage across them, it further amplifies the issue.

Simply, data in one system is often at odds with data in another system, unless it’s centrally managed. And creating a single source of truth for customers within an operational application, like CRM, restricts what data can be paired and connected to the customer profile.

Once you come to realize that silos will always be there, and applications will continue to proliferate, you start to realize that what’s necessary to solve the problem is technology that syncs the data across the organization, much like an atomic clock that synchronizes the time across all of our digital devices.

There's so much opportunity to use data — and that potential continues to grow. It is truly an exciting time to be in a data role in an organization, whether you’re part of the business or part of IT. To capitalize on the possibilities of your data — and support your customer engagement strategy, deliver improved marketing outcomes, streamline your service calls, or maximize your sales resources — you need a modern data management approach.

Related Article: The Road to Recovery Is Paved With Data

The 3 Pillars of Modern Data Management

Three pillars of modern data management can turn your massive data assets into a treasure trove: data maturity, a single all-in-one data management platform, and the ability to scale your data management capabilities.  

3 data management pillars

Learning Opportunities

Data maturity is a progression of capabilities that allows you to leverage data to its fullest extent. With data maturity, you can create a deep understanding about your customer data which leads to a deep understanding about your customers and their preferences. With data maturity, you can act on insights and improve outcomes.

5 levels of data maturity

Figure 1: the 5 levels of data maturity for a 360-degree customer view

A single all-in-one data management platform provides all the capabilities to utilize customer data in a seamless, end-to-end environment. It synchronizes trusted data by providing the ability to discover, connect, cleanse, master, secure, govern and share any data from any data domain that’s utilized across departmental silos. The platform proactively improves data quality, enriches customer profiles, and delivers rich customer data to downstream systems, applications, and data scientists.

With today’s data volumes, economically scaling an end-to-end data management system is best in a cloud-native environment that’s supported by artificial intelligence (AI) and machine learning (ML). AI and ML in a cloud-native environment helps brand remain flexible as things continue to move and change at lightning speed. In turn, this leads to faster time to market and greater business impact. The ‘heavy lifting’ of repetitive tasks to connect, cleanse and standardize, catalog, master and secure data is streamlined with machine learning to recognize patterns and types of data, while microservices make the task of managing data easier.

Related Article: Innovate, Pivot or Stay the Course: How Customer Experience Responds to Disruption

The Opportunity Ahead

With a complete understanding of your customer data, you can achieve dramatic business outcomes, like differentiated customer experiences driven by enhanced personalization cross-channel engagement and better service and support.

The opportunity ahead of you is a big one. Get it right and you’ll set your company up with a solid foundation of trusted data and rich, reliable 360-degree customer views that drive your customer experience strategies, with flexibility to grow as you do.

A foundation that can energize the people, processes and applications you need to engage your customers and fuel revenue growth. With hard, smart work, the right tools, and the support of the right stakeholders, none of these challenges are insurmountable.

fa-solid fa-hand-paper Learn how you can join our contributor community.