Unlocking the Power of AI in Contact Centers: The Future of Intelligent Contact Centers
The Future of Contact Centers: How AI is Revolutionizing Customer Experience
In January, prominent CX futurist Blake Morgan made a bold prediction: 25 percent of AI agent-assist deployments will fail in 2024. One critical reason for this failure is the inability of many contact centers to unlock the necessary data or discipline to truly benefit from AI. This challenge extends beyond agent-assist and across the entire spectrum of contact center AI.
Zeus Kerravala, Founder and Principal Analyst at ZK Research, has also highlighted the importance of connecting communication data with CRM data. However, the reality is that not many companies truly love their CRM data. This lack of enthusiasm for CRM data can hinder the success of AI deployments in contact centers.
Despite these challenges, contact centers have started to leverage AI as an input mechanism to overcome these obstacles. By utilizing AI to listen to calls, summarize conversations, and automatically update CRM records, contact centers can generate better data, leading to improved AI in the future.
The intelligent contact center of the future is one that leverages AI to enhance its data sets and uses those enhanced data sets to improve AI outcomes. This powerful cycle has the potential to transform customer experiences and drive business success.
AI Training AI: 4 Fabulous Examples
1. AI Performance Insights Inform Contact Center Routing
Predictive routing models can analyze contact center data to predict which agent is most likely to deliver a positive outcome for a specific customer. By leveraging AI-augmented QA systems, contact centers can surface new agent performance data to inform a triage system that routes contacts based on the likelihood of resolving the customer’s query.
2. AI Knowledge Management Enables Next-Level Agent Assist
AI agent-assist models can leverage the content within a contact center’s knowledge base to draft customer replies or recommend next best actions. New NLP and GenAI models can identify knowledge improvement opportunities and draft new knowledge articles for review and publication, ensuring that agents have access to accurate and up-to-date information.
3. AI Troubleshooting Automates Virtual Agent Designs
GenAI-driven solutions can evaluate successful customer conversation transcripts to define optimal troubleshooting steps. Virtual agent platforms can automatically develop conversation flows based on these steps to automate future queries or guide agents through troubleshooting processes.
4. AI Sentiment Analysis Prompts Automated Outreach
AI models can gauge customer sentiment during interactions and feed that data into the contact center’s CRM system. This sentiment data can inform various AI models, such as HubSpot’s Customer Health model, which categorizes customers based on their sentiment and other insights. Automated outreach strategies can then be devised to engage with customers based on their “health status” and drive positive customer interactions.
Intelligent Contact Centers Are Cloud-Native, Model Agnostic
To fully realize the potential of AI in contact centers, businesses must work with a cloud-native CCaaS provider that understands and works towards the vision of the intelligent contact center. Zoom is one such vendor that offers a next-gen CCaaS platform designed to support AI-driven customer experiences.
By embracing AI and leveraging data-driven insights, contact centers can revolutionize customer experiences, drive business growth, and stay ahead of the competition in an increasingly digital world. The future of contact centers is intelligent, data-driven, and AI-powered – are you ready to embrace it?
