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Customer service and support (CSS) is a term with two meanings. Most generally, it refers to the functions of a contact center in handling post-sales customer inquiries that require some effort or action on the part of the business. More specifically, it refers to the elements of the software stack that facilitate those operations, primarily case tracking and trouble ticketing.
These functions are so universal that the software used to manage them has, until recently, seldom been thought of as innovative. In recent years, there has been a flurry of developments in the underlying technologies and in customer service processes that encourages both buyers and vendors to look at this segment with fresh eyes.
Today, CSS is driven by a new emphasis on workflows and automation, particularly when it comes to managing self-service and field service, and providing agents with contextually relevant information during interactions.
Multiple technologies have converged to create a serendipitous moment for software development. Artificial intelligence (AI) has become a standard tool in vendors’ portfolios for many use cases. One of the most promising is that it can examine structured and unstructured information sources and assess the best steps to take to resolve customer queries. Its impact on knowledge management leads directly to agent guidance: features that alert agents to the appropriate next best actions. Other relevant technologies include new forms of customer messaging (particularly consumer-friendly SMS) and incremental development of remote sensor and communications tools for early warnings about problems or equipment failure.
In response to these improvements, the market is segmenting into tools that emphasize the integration of complex functions and processes, and those that focus on speed and simplicity for agents. There are also tools in the marketplace that overlap between those goals.
What appears to be pushing the industry’s buttons is the adoption of automation and workflows as a way of achieving both complex integration and a simplified user experience. Ventana Research asserts that by 2024, seven in 10 customer interactions will include a combination of automated conversational self-service and live agents, reducing costs and time and enabling agents to focus on high-value interactions.
Additionally, by 2022, one-half of organizations will use conversational computing technologies like intelligent virtual assistants (IVA) to enable a more intelligent enterprise that focuses on engaging and satisfying customers. Taken together, these developments imply that those responsible for delivering customer service are in a position to evaluate new technologies and potentially replace less automated systems with more modern, often cloud-based ones.
The market impact of these trends can be seen in how the vendors have expanded their feature sets. Vendors are exploring a wider range of capabilities that incorporate elements adjacent to their traditional areas of case and ticket management, but still related to the overall process of support management. For example, workforce engagement, knowledge management and self-service are gaining attention from vendors. These segments, in particular, are connected to each other by advancements made in underlying technologies like AI, machine learning (ML) and automation or workflow design.
Vendors have introduced low- or no-code tools for designing automated processes that connect service operations to back-office processes. AI produces better knowledge sources that enable customers to self-serve at higher rates and with more effectiveness. It also allows for agent assist and guidance tools that provide focus and speed during support interactions. And while self-service and agent management are not core to traditional CSS platforms, they are likely to become part of core offerings in short order as buyers and sellers view support as more of a set of entwined processes that should all be managed together.
Vendors in this space are also very attuned to the needs of specific industries, which often have variations in the way customers expect to be supported. This is especially true in complex B2B environments like health care or manufacturing, where CSS can include support for expensive machinery that may also include remote sensor data, predictive analytics of potential faults and failures, and field dispatch of highly trained technicians. These specifics make it essential for buyers to assess vendor capabilities within their particular vertical to ensure expertise. <
We expect to see buyers opting to incorporate more separate components into their service tools and platforms, rather than relying on point solutions for elements like messaging, knowledge management and analytics. We also expect that, post-pandemic, many organizations will reassess their service and support needs based on the shift in where their workers and equipment are located. This will push CSS buyers (who are the ones using CSS to deliver service to those organizations) to work with vendors to reassess what components are needed within platforms.
The changes that are underway are slow enough to be manageable for most organizations, allowing them to time to examine processes and explore the effects of new and improved technology on their operations. In the meantime, the next steps for buyers should be to identify the pain points and goals in their service centers. Along with common goals like cost control and interaction deflection, they should be considering how to reduce time to resolution, and how to identify problems before they become critical – or even before the end user is aware that they exist.
Also, buyers should consider how agent skill management and optimization fit into the service equation. Each of these issues will point buyers toward a different set of features to evaluate and will inform the next generation of platform development for vendors. Buyers should also consider to what degree they would benefit from expanding their CSS beyond the core service and support framework by integrating it into a broader customer experience platform aligned with contact-center operations, cross-departmental analytics and even marketing teams. Doing this will help refine the list of vendors and open the door to questions about how support fits into larger organizational goals.
Vendors must face many of the same issues about going broader. In effect, they need to answer the question of where service technology ends and other categories (especially contact center, CRM and IT service) begin. They need to have strategies for how they incorporate vertical market uniqueness into their platforms, especially as the platforms broaden into suites.
And perhaps most important, they need to identify and articulate the use cases and value propositions for the underlying new and improved technologies in AI, knowledge management and agent guidance. Making these obvious to buyers will be an important competitive challenge as the market participants become larger, with vaster feature sets. They need to arm buyers with arguments for these tools that are rooted in ROI, cost control and in identifying service operations with revenue opportunities, wherever they can be found.
Customer Service and Support systems are one focus area in Ventana Research’s Customer Experience expertise. For further reading, see our Analyst Perspectives on Voice of the Customer and the changing nature of the CX buyer.
Regards,
Keith Dawson
Keith Dawson leads the software research and advisory in the Customer Experience (CX) expertise at ISG Software Research, covering applications that facilitate engagement to optimize customer-facing processes. His coverage areas include agent management, contact center, customer experience management, field service, intelligent self-service, voice of the customer and related software to support customer experiences.
Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business,
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