LEADING THOUGHTS weighed down by “ the way it ’ s always been done ,” as many of the larger companies were . This is the era that saw the emergence of software companies like Blue Pumpkin , which redefined the industry ’ s approach to workforce scheduling and managing . There were literally dozens of small companies working to disrupt the customer service industry while the larger companies tried to convince the market that they were actually CRM or e-business companies .
These disruptive contact center companies of 20 + years ago tended to attract customers that were disruptors in their own right – deploying disruptive technology in order to disrupt their own industries . While it was not as in vogue to call yourself a disruptor in the late 1990s as it is today , these contact center industry disruptors were definitely disruptive .
Back to my original premise – the same type of disruption is happening today , but today ’ s disruptors are leveraging artificial intelligence ( AI ) in the same way their predecessors leveraged software back in the day .
The normalization of work-fromhome ( WFH ) and generational expectations of today ’ s employee and consumer are the driving forces behind many of the emerging innovations in the market today . These new solutions are taking a more holistic approach to solving the challenges of both the customer experience and the employee experience today .
THESE NEW SOLUTIONS ARE TAKING A MORE HOLISTIC APPROACH TO SOLVING THE CHALLENGES OF BOTH THE CUSTOMER AND EMPLOYEE EXPERIENCE TODAY .
OBSERVE-AI ( https :// www . observe . ai /)
is a sort-of offspring of the original employee engagement platform , workforce optimization ( WFO ). A self-described Intelligent Workforce Platform , Observe-AI provides a number of AI-fueled solutions , such as real-time monitoring and personalized coaching on the employee engagement side . It can also transcribe and analyze every customer conversation in real time , including sentiment analysis , silence detection , talk-over , and so on . This visibility into , and analysis of , 100 percent of customer conversations is all accomplished using its AI engine . Cutting-edge stuff .
BALTO ( https :// www . balto . ai /)
relies on its AI engine to help agents provide the correct response to callers every time , all in real-time . This looks to me like super-charged agent coaching , done on the spot , during the call rather than after the call . It supports agents , whether in-house or WFH , by providing them with dynamic prompts and the best responses during the call . Beyond that , it automatically scores 100 percent of calls and alerts managers of potential problems , all in real time . Once again , a solution that has the potential to redefine employee engagement , and employee engagement practices .
XAQT ( https :// www . xaqt . com /)
is going beyond the AI-driven point solution to offer a comprehensive approach to addressing every aspect of the contact center ’ s operation , from infrastructure to omnichannel engagement to analytics , and everything in between . Xaqt ’ s management has deep roots in the contact center that includes experience on the operational side as well as the technical side of the industry . Xaqt ’ s CEO is also the founder of Latigent – an advanced contact center reporting platform that was acquired by Cisco .
Xaqt ’ s layered platform approach allows it to work as a new standalone solution in any contact center , or to work in whole or in part with virtually any contact center platform in the industry today . Contact centers with older technologies or with solutions not yet fully depreciated no longer need to be concerned about the AI revolution passing them by . Xaqt can integrate with any platform , migrate existing data from any vendor , and infuse any system with advanced AI capabilities .
As in the past , I see this new generation of disruptive contact center companies appealing to companies that are disruptors in their own industries . The cycle will complete when today ’ s disruptive AI solutions become as mainstream as their disruptive software predecessors of the 1990s have . Until then , expect to see continued disruption from these disruptive disruptors .
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