Ventana Research Analyst Perspectives

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....

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.

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...

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.

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...

Tools for contact center agent management have changed considerably in the past few years. The suite of software applications has grown from those that perform core functions in scheduling and quality control to include more advanced solutions for agent guidance, integrated desktops, and workflow and automation design. One area of intense investment by vendors has been analytics, specifically for assessing customer satisfaction and hearing the “voice of the customer.”

Customer support operations increasingly rely on automation and complex workflow processes to reduce costs and improve experiences. Automation also allows organizations to make their service processes richer, incorporating information and staff from back offices, for example, or embedding conversational tools into contact center processes.