At Your Service: Turning Customer Service Data Into New Revenue Streams

The shift in value from products to services has been ongoing for several years now, and has opened up a whole new world of professional services and Managed Support Services. It’s the strategy of some of the world’s most innovative companies: IBM, for instance. And yet there are many areas that are still untapped, and have the potential to impact the true customer experience.

In his book Complexity Avalanche, J.B Wood, President and CEO of the Technology Services Industry Association, suggests that the growing gap between technology’s value as a solution with the potential to deliver better productivity and what customers actually achieve is growing rapidly. This is becoming the major bottleneck to the adoption of new technologies. Wood shows that the technology service life cycle today focuses on the implementation phase—how to sell, install, and train customers. Post-implementation service is often delivered through a separate customer service organization. It is set up as a cost center, focusing on problem resolution and measured by time to resolution. There is no mandate to engage with the customer in order to understand his usage behavior and provide guidance on how to improve the operational experience of the customer.

There are exceptions, of course. We have seen Apple break away from the competition and recognize the need to bridge the consumption gap. The initial experience Apple offers in its stores is to familiarize potential buyers with its devices is far ahead of the competition, allowing customers to try out the Apple hardware as much as they want within the store or to attend free workshops on how to use software. Apple has extended this experience with its Genius Bar service, which provides personalized service to customers after they've bought and implemented their Apple products. The takeaway: Users want to be educated on advanced features/capabilities so they will have better experiences with their new purchases. The value of the products increases with the value of customer-care service.

Today, everyone talks about customer experience management. But most efforts in this area are centered not around the actual customer experience, such as those so palpable in any Apple Store, but around aggregating data. These data are culled from large networks, internal corporate operations, and users of all types. Usually, managing customer experience is merely an attempt to analyze usage patterns. There is huge potential in expanding the knowledge and practice of better customer experience management, as Apple is showing the world with its ever-increasing sales, market share, and profits.

But we shouldn’t write off the potential of the data we are gathering on device and network usage. The monetization of this data is in its infancy. Most early attempts are indirect, and generally focus on building feedback cycles into network optimization and operational efficiency plans at corporations. But this approach typically leads to an indirect impact on customer experience, with such efforts of analyzing data rarely resulting in new revenue streams. Rarely do such efforts of analyzing usage data result in new revenue streams.

We have been working with various customers who are going through the services innovation cycle on new ways to better use these data. We’ve gathered data from multiple network and IT tools and systems (e.g., fault and performance tools, Policy Control Frameworks, and other CRM & BI systems, as well as real-time data extracted from network nodes and user devices). We have also developed analytics tools for KPI/Event Analysis & Trend Forecasting, managed innovative knowledge management systems, automated responses through rules/engines, and then integrated all of these elements into a holistic experience management framework. Most exciting: We’ve collected smart, or metered, data from users’ devices to predict, and then pre-empt, technical problems.

All of this information is helpful on a practical, day-to-day performance level, but I believe there are ways to directly monetize this data. One of the possibilities is to create a new service offering focusing on continuous operational improvement. I recently came across an early version of such a service, at Philips Healthcare. Philips has launched an MRI Utilization Service that collects metered data proactively from live MRI and CT scanner units, analyzes the data, and compares this information with that from other units. Based on actual usage data, algorithms then provide guides for optimizing workflow. The result is increased productivity in hospitals in terms of the number of patients that can be scanned, as well as quality control. This represents a new space in the services life cycle, and provides a good new revenue stream model focused on operational improvement.

Although the idea is gaining some traction with the industry, turning customer service data into new revenue streams remains a largely unexplored concept. We’re just starting to scratch the surface.

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