Editor's note
As technologies grow more sophisticated and plentiful, the meeting areas where customers connect with businesses have evolved as well -- from simple call centers to multidimensional contact centers to all-encompassing customer experience centers under the umbrella of customer service.
No doubt the COVID-19 pandemic disrupted and accelerated by several years corporate infrastructure and workforce planning for the contact center of the future. The once unthinkable scenario of contact center agents working almost exclusively from their homes became the norm and has since manifested into the reality of remote and hybrid workforces.
Cloud-based software and hyper-converged services are simplifying and unifying what could have been fractured workflows if businesses continued to operate their contact centers totally on premises. Artificial intelligence and advanced analytics are enabling businesses and their contact centers of all shapes and sizes to process and monetize multitudes of customer data collected from multiple channels of communication. All these technologies support initiatives to improve agent performance and scheduling, smooth workflows, upgrade call routing capabilities, shorten handle times, personalize interactions with customers and improve ROI.
This essential guide examines how AI, analytics, natural language processing, cloud-based tools and workforce management software empower large enterprises and SMBs to meet the heightened expectations of their customers, shape the future of their contact centers and transform them from cost centers into profit centers.
1Technologies transform contact centers into a multidimensional force
Contact centers are constantly inundated with inquiries of all sorts, ranging from the simple to the complex. Technologies like AI, NLP, advanced analytics and the cloud help monitor, measure, analyze, personalize and monetize customer engagements with contact center agents over multiple channels of communication.
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Article
How emotion analytics will impact the future of NLP
Conversational agents and chatbots struggle to understand complex human speech, including sarcasm. But that could change as NLP increasingly incorporates emotional understanding. Read Now
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Moving beyond NLP to make chatbots smarter
Machine reasoning could help chatbots better understand context, which is crucial to understanding human emotions and formulating emotionally relevant responses. Read Now
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How to improve customer satisfaction during supply, labor crisis
Transparency, minimizing returns and collecting customer insights from call center reps are some ways businesses can improve customer satisfaction. Read Now
2Agent skills, performance and productivity are key challenges
Before the COVID-19 pandemic, the concept of contact center agents working almost exclusively from their homes wasn't even considered a remote possibility. But hybrid and remote workforces are the new reality confronting many contact centers as they consolidate workflows, unify communications, measure agent performance, personalize customer engagements and maximize ROI.
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Article
Contact center agents' post-pandemic future
The pandemic changed how contact centers operate and the technologies used to provide customer service. In this Q&A, ICMI's Brad Cleveland predicts what's next. Read Now
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Automating customer service empathy a work in progress
Bots and AI tools can help clean up customer service texts, emails and chats -- and make them more consistent. But finding empathy is still mainly the purview of humans. Read Now
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How bad writing, templates and chatbots kill customer service
Leslie O'Flahavan, a writing coach specializing in contact center communications, discusses how humans, AI and bots can work together to provide good customer service. Read Now
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How to calculate call center utilization rates
Customer service leaders use metrics like call center utilization rates to track performance and CX. Leadership must learn the effects of these rates and how to calculate them. Read Now