Customer Service and Support (CSS) software is about more than case tracking and trouble tickets. Many organizations view the service call as an opportunity to solidify a positive customer relationship and perhaps enhance the loyalty and value of the customer. That has propelled interest in the emphasis on workflows and automation that now/currently drives CSS, particularly when it comes to managing self-service and field service, and the ability to provide agents with contextually relevant information during interactions.
The technology underpinning customer experience (CX) is a hodgepodge of tools that have been developed for niche use cases and then expanded to fill broader roles. Examples include the old (CRM, help desk software and speech analytics) and the new (customer data platforms and conversational AI). This is because CX is a set of very specialized processes that happen in different parts of the enterprise, managed by people who often do not connect with peers handling related processes. Service-related activities are focused in the contact center, personalization and loyalty in marketing departments, and so forth.
Topics: Customer Experience, Marketing, Marketing Performance Management, Voice of the Customer, Contact Center, Product Information Management, Digital Marketing, agent management, intelligent marketing, Customer Experience Management, Field Service, Conversational Marketing, Digital Experience Platform, customer service and support
In a previous Analyst Perspective, we discussed some of the big-picture trends that are bringing cost control back as a core driver of contact center operations. In this report we will tackle some of the practical ramifications: how those trends affect decision-making and operations.
Contact centers have always been very cost-centric and attuned to the kinds of constraints that they have to operate in, but many organizations were diverted from that kind of focus when the pandemic first hit. In 2020, there was a sudden need for new tools and equipment just to keep centers running, and the costs involved in enabling agents to work from home — equipping them and their supervisors with the tools they needed to collaborate and stay in sync — were unavoidable.
A formal Voice of the Customer (VoC) program is a necessity for any organization that wants to grow its customer base and differentiate from its competitors. Unfortunately, many organizations have not updated their notion of “formal” in quite a few years.
Topics: Customer Experience, Marketing, Voice of the Customer, Contact Center, Digital Marketing, agent management, Customer Experience Management, Field Service, Conversational Marketing, customer service and support
Ventana Research recently announced its Market Agenda in the expertise area of Customer Experience. For the past several years, many organizations have found it challenging to provide excellent customer experiences in the face of drastic technology changes and the ongoing pandemic. These challenges have highlighted for many decision-makers how strategic CX can be in differentiating from competitors. But it can also be a complex and disjointed effort that requires continuous investment in people, processes and technologies.
Any organization that relies heavily on a large labor force looks to automation to reduce costs, and contact centers are no exception. They handle interactions at such large scale that almost any effort to automate some part of the process can deliver measurable efficiencies. Two factors have ratcheted up attention on automating customer experience workflows: the dramatic expansion of digital interaction channels, and the development of artificial intelligence and machine learning tools to facilitate workflow deployment.
Topics: Customer Experience, Analytics, Data Integration, Contact Center, Data, AI and Machine Learning, agent management, data operations, Customer Experience Management, Field Service, customer service and support, digital business, Experience Management
When NICE acquired inContact in 2016, it began a transformation that saw it broaden its product offering and positioned itself to play a larger role in the contact center and customer experience industries. It was a prescient move, creating a firm that could supply end-to-end contact center functionality in the cloud. And it anticipated today’s market dynamic, in which NICE and its competitors are racing to define (and capitalize on) the post-contact center future.
Topics: Customer Experience, Voice of the Customer, Business Continuity, Analytics, Contact Center, Data, Digital transformation, AI and Machine Learning, agent management, Customer Experience Management, Field Service, customer service and support, digital business, Experience Management
In part one of this Analyst Perspective on the use of artificial intelligence within contact center applications, we focused on the evolution — and resulting benefits — of tools embedded with AI, including ease-of-use for non-data-scientists.
When artificial intelligence emerged from the labs and vendors started offering it as a component of their software, many contact-center buyers shied away from it. From their point of view, AI and machine learning tools were new, expensive, relatively untested and had an uncertain use case. This stance was understandable, as contact center professionals are traditionally expected to be risk-averse when deploying technology into their operations. Contact centers are, by design, supposed to be hardened, mission-critical sites of high reliability. There has historically been a bias towards avoiding new technology, deploying only when it has been thoroughly vetted across the industry.