The Unified Agent Desktop Call Center: A View of the Total Customer

The Unified Agent Desktop Call Center: A View of the Total Customer
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Customers are fed up with being put on hold when calling customer service and, let’s face it, it’s frustrating finding yourself in a situation where you’re forced to re-explain the problem as you’re transferred from one person to another. I can’t count how many times I have been asked to hold because “our systems were running slow.” There’s also that common line of, “can I put you on hold for a few minutes while I look up the information on your account?” Seriously? A few minutes? The net effect is a big disconnect between the actual quality of your customer service and the company’s brand identity.

Isn’t This What CRM Was Supposed to Fix?

Call center productivity can seem like an intractable problem. This is especially true if you’ve spent a lot of money on customer relationship management software (CRM). It can be disappointing if you’re stuck at a plateau or seeing metrics drop despite that CRM investment. However, simply having the right CRM software won’t help you achieve your goal of establishing a single view of the customer. Yes, you have a system in place, but it won’t automatically create a central place to stow data from a range of different sources. What’s more, your CRM interface may not show everything an agent needs to handle a call; that information may be scattered throughout several systems. So even a robust CRM implementation may not provide the single customer view that you need to improve call center efficiency. In fact, some companies have multiple CRMs, resulting from M&As or just from growth with multiple lines of business “doing their own thing.” Companies in this position should consider master data management(MDM).

How a Unified View of Your Data Helps Improve Customer Service

To avoid multiple windows, incomplete information, and a frustrated customer, agents need a single view of the customer. This single view will help companies gain a deeper understanding of the customer relationship and the customer’s precise needs. Agents need insight into which products and services the customer uses, whether the customer has submitted any complaints and the overarching contact history. With a single view, you may see improvements in areas such as increased first call resolution, decreased average call duration and decreased escalation rates. Moreover, agents will be equipped to handle higher call volumes with increased customer satisfaction. The objective is to deliver more effective, higher quality customer service. When you do that, you can eliminate nearly any disconnect that exists between your customer service and the customer’s expectations.

At the end of the day, customers want to talk to someone who “knows” them and can quickly solve their problems. Happy customers are loyal customers, and loyal customers are important to every business. That is the promise of the single view.

The Single View Begins with Customer Information

To get a single view of your customer, you’ll need to start by developing an understanding of where your customer data is located, so you can plan how best to integrate that data into a single location. This is called master data management, and it has five key steps:

  • Step One: Identify your customer data and who accesses it;
  • Step Two: Create a common definition of a “customer”;
  • Step Three: Ensure data accuracy and eliminate duplicate data;
  • Step Four: Create a governance program; and
  • Step Five: Implement master data management (MDM).

If your call center agents could use a productivity boost—or if your company is doing well and outgrowing its current systems—let us know. Primitive Logic can leverage extensive experience to help you achieve a single view of the customer at every stage of your company’s lifecycle: during periods of hectic growth, before and after an M&A and beyond. This will help you fulfill your ultimate goal of improved customer satisfaction, customer loyalty and a more efficient call center that can handle high volumes with better metrics.

Kevin Moos, July 2017