For a topic as hot as Customer 360 is, it’s strange that the web is so devoid of helpful information.
Sure, plenty of vendors have documents that claim they can deliver it. But apparently few are willing to provide information that helps you wrap your head around exactly what Customer 360 is and how to make it happen.
We’ve been focused on the research, development, and delivery of the technologies required for a complete, 360-degree-view of customers for a long time now.
So I’d like to use our experience to start filling that void, and share a few of the most important things you need to understand about Customer 360 if you’re considering starting—or are currently struggling with—a Customer 360 project.
#1: CRM does not deliver Customer 360.
Customer Relationship Management (CRM) software like Salesforce and Siebel can be a great tool for organizing your sales, service, or marketing efforts. The features of a CRM system, however, are dependent on underlying data like provisioning, order, and touchpoint data. And in a large organization, that data is largely outside the CRM system’s control.An effective Customer 360 strategy takes control of that data and provides it to the CRM app, so CRM has the
full view of the customer and how they interact with an organization. Supported by Customer 360, sales and support staff can rely on CRM to get the best information when engaging with a customer.
#2: Customer 360 is not a unified database.
Customer 360 is about delivering timely information assembled from all relevant data sources, internal and external. Databases don’t come with this functionality.
To be timely, Customer 360 can’t be just a one-time integration into a single database. New and future sources of data, and the data lake paradigm, will cause the unified database to become stale.
An effective Customer 360 strategy takes into account that there will always be multiple sources of information that will always be changing. It then synthesizes those sources continuously to provide an up-to-date understanding of each customer.
#3: Customer 360 is not an application.
This point is similar to my point about CRM. In a generic sense, applications designed to meet business goals, like customer service support or sales quotation tools, can utilize Customer 360 information. But applications can’t assemble the contextual view of the customer from many and sometimes unrelated data sources, evaluate the data for quality problems, or resolve the issues introduced by data inconsistency.
You first need holistic data technologies that are designed for achieving these goals to get Customer 360. Only then can an application focusing on the sales process, service case management, marketing campaigns, and other CRM functions deliver its full value.
#4: Customer 360 is not MDM.
Master Data Management (MDM) is an important part of Customer 360, but MDM alone will not deliver it. A good MDM program can help ensure you understand what master data is required for your particular Customer 360 implementation, where to get the data from, and how to link some of it together.
MDM will not, however, perform the real-time analytics you’ll need as data about and related to your customers changes throughout your systems. For Customer 360, you’ll need a way to constantly reevaluate your understanding of your customer and your understanding of the state of all your customers.
#5: Customer 360 is understanding the current state of your customer, at the moment of your current interaction.
The current state of your customer can depend on every single interaction you’ve had with that customer in the past. And it’s almost certainly contextual in nature: your customer’s state depends not just on their direct interactions, but on surrounding and related events that touched the customer in some way.
Advanced (predictive) Customer 360 lets you know what the customer is seeking support or sales information about before they even contact you. But achieving this level of understanding about your customer’s state is no easy task.
Just think about all the possible sources of data! This alone deserves its own blog post. Predictions will be better with everything from social media interactions to free-text notes from service tickets, and well beyond.
Industries like telecommunications, which offer services that are backed by physical infrastructure, even need to include infrastructure status that relates to the customer’s services: think information about outages, maintenance, and upgrade schedules.
To understand your customer, you need to understand what is important to them. But you also need to understand the impact of the customer on your business. For most industries, this is important—but for some, like insurance and banking, it is essential.
An insurer must understand a customer’s personal relationship data, incorporating the customer’s beneficiary information, real house-holding information, and more. This is the only way to achieve a viable sense of which customers and services might be important to the individual currently interacting with you.
When done right, Customer 360 even allows you to proactively initiate customer interactions. A current-state understanding when a customer reaches out is the minimum you should expect.
#6: To build Customer 360, you need a way to reconcile fragments of information.
Achieving Customer 360 requires you to use entity resolution to figure out which data fragments belong to the same individuals and to enrich your data.
But you also need to decide what information is relevant and correct through data synthesis. And you need to discover the relationships between individuals and other “objects” like bills, service tickets, policies, contracts, locations, and businesses.
This is where some real magic—in other words, data intelligence—is needed. Because entity resolution, data synthesis, and relationship discovery are all essential to making sure that your complete “picture” of the customer is always up-to-date and reflects all the data you have available.
But for any company that’s been around for more than a few years, this is a major challenge. There are years of technical and business decisions that you need to understand to properly use historical information.
Even with good MDM (and without any complicating information gaps or internal politics), you’ll likely find data or edge cases from the organization’s history that you have to explain.
That’s why an effective Customer 360 tool starts with the data first, then creates an implementation that the specification is derived from. This is the reverse of the approach that many big data tools use, so you should always seek a data-first tool for Customer 360 projects.
#7: Customer 360 is almost always a big data project.
Don’t let anyone tell you that Customer 360 is old hat. We’ve talked to companies that have spent close to a billion dollars over a decade and have not achieved Customer 360.
We live in an amazing time where data on just about everything is becoming available. But you probably don’t even need to look outside the walls of your own organization’s systems to see real velocity, variety, and volume—cornerstones of the definition of big data—come into play.
To deliver true 360-degree customer information, you need to make use of that data. That means your Customer 360 project becomes, almost inevitably, a big data project.
#8: For Customer 360 to be useful, you have to trust the data.
Your sales and customer service folks want to be competent in front of a customer—there’s nothing more frustrating for the customer or the representative than a disconnect between your organization’s data and the real world.
But to do that, your employees have to trust that the information they get from their computer is more reliable than their intuition or word-of-mouth rumors. And poor data quality will erode that trust quicker than you’ll be able to rebuild it.
After only a few failed interactions, your employees will second-guess the computer every time. That introduces less effective service and increased inefficiencies, with the potential for increased customer dissatisfaction.
But when your employees trust that your systems accurately reflect reality, they can work effectively to deliver top-tier customer service.
Customer 360, therefore, requires high-quality, trustworthy data. And if you don’t have more than 99% data quality already in your systems (which most companies won’t), you’ll have to create and maintain it.
The most misleading Customer 360 articles out there are placed by companies that want to sell you “easy button” solutions.
The truth is that Customer 360 is hard. Achieving Customer 360 will require you to overcome technical and political challenges and to conquer organizational inertia.
But you shouldn’t settle for anything less. Without Customer 360, a company struggles to scrape value out of an incomplete picture of their customers. Customer 360 positions you for success by putting you in sync with your customers and their current and future needs.
So when you get started on your Customer 360 project, keep our tips in mind. Ask a prospective Customer 360 vendor how they’ll address each of these points, and make sure that you get a real Customer 360 solution that can deliver tangible business value.