Analyst Perspectives

Verint is operating in quite a different marketplace for contact center and agent management technology than existed five years ago. We have seen tremendous innovation and expansion of the available technologies for running centers and optimizing the performance of the human labor pool, as well as an explosion of tools built to automate customer interactions.

Agent management tools that were considered fundamental just a few years ago, like call recording, quality monitoring, and even workforce management software, are now heavily commoditized. They have moved into the background as software providers and buyers focus on understanding and deploying much more complex tools built around artificial intelligence. These new offerings are starting to change the way humans and automated systems interact and how enterprises manage both of those labor pools.

At its recent analyst conference, Verint laid out the latest steps in its strategy for coping with marketplace changes, including its efforts to pivot from traditional AM tools to software components reflective of its innovations around AI, automation and analytics. Verint noted several important multi-million-dollar deals revolving around its bot products. These are a series of automated “agents” that each focus on a narrowly defined function and slot easily into the overall platform that controls how Verint customers organize data and workflows.

Verint’s strategy for bots has been evolving. Two years ago, when bots were new and conversations around AI were fever-pitched, Verint was one of the first providers in the space to separate AI-as-a-platform from AI-as-applications and to discuss contact center AI as a means to achieving specific performance goals on specific tasks.

For most of the two years since AI became an industry disruptor, conversations have focused on the best way to implement AI tools for customer experience. Software providers differ in approaches, with some primarily talking about AI as a platform service that enables smart applications and others focusing more on the applications themselves. That is a false duality because buyers can’t be expected to deploy meaningful AI applications without having a solid underlying platform. So, the conversation is really about how to express to buyers the realizable value of the new tools without forcing them to overhaul a sizable portion of operations, which is disruptive.

At that early stage, Verint’s approach was to identify specific use cases that could benefit from AI-based automation, and incrementally developed bots as a definitive solution to those problems. That was a smart approach competitively because it indicated to buyers that Verint’s development efforts were focused on problems that were important to contact center managers in the short term: interaction containment, summarization and self-service.

As bots were developed, deployed and improved, Verint took its initial argument about identifying specific, immediately helpful use cases and added the critical element of ROI. The provider began to detail exactly what customers were expected to see when using the bots. Verint was among the first to put hard-dollar savings numbers to the potential scenarios.

What we saw at the recent conference was the result of this strategy playing out. Verint used real-world examples to describe the experiences of actual contact center customers, who were able to cite actual dollars saved. This authority about customer service outcomes is exactly what buyers need to hear from software providers about these technologies. Verint has also started to differentiate between “copilot” bots and those used for self-service. This distinction got lost in early discussions around contact center AI.

Verint and some of its key competitors are now much more up-front about how human labor and automated systems work in tandem, with some applications focused on human productivity and others on interacting with customers. They share common elements, including enabling data and platform solutions, but they are now seen as having different goals expressed in different outcome metrics. (Self-service bots focusing on containment, for example, and copilot bots on boosting human awareness of context and procedure.)

In one example, Verint described a sequence of copilot bots working in tandem to support human agents: a Smart Transfer bot, followed by one enabling knowledge automation, then Coaching, plus a bot helping with Wrap-Up. In Verint’s telling, this sequence could significantly reduce average call duration. That helps alleviate fears that improved self-service containment means humans are left with the hardest and longest interactions that machines can’t handle.

Verint also demonstrated a new bot called Genie (one of the few to have branding). Genie is an impressive bot focused on advanced business analytics which is aimed at expanding the roster of workers who can get insights without deferring to a dedicated business analyst for data processing. This opens the analysis space to people who wouldn’t necessarily have the time or skills to work with the data but can now get real answers to questions they don’t even know how to ask. Verint executives described the need for this tool in terms of a bottleneck: There are not enough analysts to fill the need for insights. I think it may also be true that there’s too much data touching too many different activities in and around contact centers. It will be interesting to see how Verint quantifies Genie’s value in ROI terms, as it does for the rest of the bot portfolio.

Viewed with a longer lens, agent management technology will continue to be upended by AI-focused development. AI applications can dramatically increase human agent productivity and reduce the number of interactions that need to reach those agents. The result has been a shift in the focus of technology away from long-term fundamentals like scheduling and monitoring and towards tools that use more automation to do things like evaluate interactions in bulk looking for performance anomalies. Ventana Research asserts that by 2026, agent training and skill development will be primarily self-directed, using automated scheduling and AI assessments. Agent management in 2024 is more focused on analytics and automation than on enabling shift trading or optimized scheduling.

Verint performed very well in ISG Research’s 2024 Agent Management Buyers Guide, with an Exemplary rating and overall leader. The company has considerable capability to provide centers with the core foundational tools while expanding the boundaries of the AM segment with tools that guide, coach and inform agents and then better measure their success.

All contact centers are facing dramatic changes in how they structure the labor component of operations. Verint is one of the key software providers capable of helping buyers transition to a more complex model of human/automated hybrid work, including better measuring outcomes and understanding the costs and ROI involved in that transition.

Buyers should consider Verint’s contact center platforms, notably the data platform, the array of AI-based bots and the core agent management tools. The core tools are time-tested and well regarded; the new ones come with vendor assertions about ROI. Enterprises should include Verint in any exploration of these systems.

Regards,

Keith Dawson