Increasingly, traditional call centers are falling short in providing the level of service today’s customers demand. Customers have to contend with long wait times and multiple calls for their queries to be addressed, and have limited options of self-service. The agents too face an uphill task as they have to access different enterprise systems to get the relevant insights. The result: poor first-call resolution rates and CSAT scores.
Improving agent performance in such call centers poses another range of challenges. Agents do not have any self-help tools to evaluate their call handling performance and rely on information provided by their manager. Managers provide feedback at the level of agent group reporting to them and not for individual agents.
Since the advent of COVID-19, about 80% of the agents have been working from home and about 20-80% of the agents would still be working remotely over the next two years. The agent workforce is now distributed and needs a better collaboration tool that is suited for remote work environment.
Tools powered by artificial intelligence (AI) can address all these problems and more. AI-enabled conversational agents or chatbots can eliminate the initial wait time and support customer self-service. The bots use natural language for communication, providing an always-on self-service option to customers and reduce the call volume handled by agents. Chatbots are expected to handle 20% of all customer service requests by 2022.
Another plus for AI-powered customer experience (CX) is that they are omnichannel. Customers can interact with the agents through digital channels of their choice including social media. About 58% of customers in the US use digital channels and e-mail to contact the call center. Multichannel customer service, however, requires an omnichannel CX collaboration space for agents, with a single unified interface using voice, video, and chat across multiple social media channels like Facebook, WhatsApp, and Slack. This collaboration space must also integrate with CRM systems enabling the agent to create tasks and use AI assistance for having the after-call work (ACW) notes populated automatically without having to leave the collaboration interface. It should also provide facility for agents to initiate video calls with customers for face-to-face contact when required.
Context aware: AI-powered call context-aware solutions give agents information about the customer, the relevant product, the interactions with virtual agent and call centers up to the point of call transfer as soon as the voice or chat lands on the agent’s panel without having to switch between applications.
Real-time search: AI-powered agent self-service function integrates disparate knowledge management sources and provides accurate AI-assisted search results to the agents. The AI-enabled searches can be real-time and show relevant results during the interaction, reducing hold time and idle time during the call.
Performance insights: AI and machine learning can also provide performance insights by analyzing the call data. This would provide feedback to the agent through overall sentiment analysis for the call along with sentiment analysis enabling the agent to visualize the point at which the customer had become unhappy. Agents can use this information to improve their call handling skills.
Anytime, anywhere: A CX collaboration space that is available on cloud lowers the total cost of ownership and improves operational efficiency. This also means that the agents can log into the call center from any place that has internet connectivity. This allows for a distributed agent workforce and gives companies the freedom to recruit best-in-class talent irrespective of location.
Enterprises require a trustworthy partner knowledgeable about solutions such as Amazon Connect and advanced AI services of Amazon. The partner should have deep contextual knowledge to understand their challenges and establish a customized AI-powered CX collaboration space in cloud.