Keith Dawson's Analyst Perspectives

Artificial intelligence (AI) has become ubiquitous in discussions of contact center technology. Vendors are rushing to incorporate it into platforms and applications. And end users have understandably mixed feelings about where it makes sense to use and what its impacts will be. No one should be surprised that AI has arrived, especially for customer support: Software companies have been working on customer experience (CX)- -related AI applications for many years, and the fruits of those efforts...

Ventana Research recently announced its Market Agenda in the expertise area of Customer Experience. CX has emerged as a way for organizations to demonstrate value and stand out in the marketplace. The technology underlying modern CX is transitioning from tools that are based on communication to those centered on data analysis and process automation. This allows organizations to build great experiences and reap the benefits in customer loyalty and value. It also forces companies to reckon with...

Zoho presented analysts with a deep look at its strategy and roadmap at its July analyst conference, describing how it intends to meld its many business applications together through integration at the level of the platform. The company, which is privately owned and funded, has generally sought to build its own tools rather than buy or partner. This approach has allowed the firm to create a suite of tightly linked tools that share a common interface.

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...

When migrating their communications stacks to the cloud, many organizations come face to face with a quandary: do they emphasize the business phone system and gravitate toward a unified communications vendor? Or should they focus on the specific applications needed for running their contact centers and seek out a CCaaS vendor?

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...

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.

Dialpad provides contact center and business phone services, a market that is in transition due to a convergence of technologies and business conditions.