As many consumers show a willingness to engage with self-service options or chatbots to avoid long wait times, many contact centres are considering investments in automation and AI. Contact center leaders have the opportunity to explore various technologies to find what best aligns with their objectives and meets their customers’ needs.
Although the call and contact center industry faces unique challenges when adopting AI-based innovations, those who swiftly embrace new automation technologies are likely to experience a significant increase in productivity compared to their competitors.
In this blog post, we help you discover specific AI applications tailored for contact centers, which, when used judiciously, not only save time for agents and callers but also enhance overall operational efficiency.
Call rerouting helps direct customer inquiries to the most suitable department or agent by analysing and categorising their requests. The categorisation is based on the content of the request, often identified through keywords or the nature of the inquiry. For example, a customer query about a billing issue is routed to the billing department. This eliminates the need for transferring a customer between multiple agents and departments, which reduces the wait time and frustration. This system helps with organisational problems of the call center, allowing agents to avoid misdirected calls, thereby improving productivity.
AI serves as an assistant to agents in their conversations with customers, by analysing them in real time and providing instant and relevant suggestions and solutions.
Additionally, in instances where agents confront complicated queries, the AI system can provide guidance on the most effective line of questioning. It might also suggest transferring the call to a more specialised department or expert for a more comprehensive resolution.
This approach extends further to recommend relevant cross-sell or up-sell opportunities based on the customer’s history and ongoing conversation. This not only addresses the immediate issue but also enhances customer engagement.
Answering all calls timely and with full attention is a great challenge for a human workforce. Conversational AI solutions, which are capable of understanding customers and engaging in natural conversations, can on the other hand handle this task rather efficiently. It is for that exact reason that many teams are turning to them for basic tasks and questions, so that they can handle other more complex inquiries.
Although it might seem weird knowing that an AI-based voicebot is conversing with your callers, this can be rather useful in many cases. After all, IVR (Interactive Voice Response) was one of the first automations ever introduced in the call center industry, and using a voicebot as part of the setup is just another step in its development.
Putting together an IVR system and AI offers more self-service options through the keypad like choosing to connect with a live agent that is specialised in the customer’s issue. More often than not, customers will prefer getting a quicker response from a bot to waiting a long time for an answer from a live agent.
While most contact centres record customer calls in order to improve their services, without utilising machine learning the sentiment and tone analysis can not be performed. With these AI can identify cues in the call that have contributed its success or failure, therefore being able to offer better recommendations in the future. Additionally, they can perform lie detection on the call recordings, pointing to the potential signs of fraud and deception.
Conversion Between Speech & Text
Incorporating AI-powered text-to-speech (TTS) and speech-to-text (STT) capabilities can significantly enhance the flexibility of your contact center. These technologies allow for the automatic and real-time conversion between speech and text, offering a wide range of applications.
Conducting surveys and questionnaires using dynamically updated scripts, which the system verbally communicates to the caller, eliminates the need for pre-recorded messages. Similarly, STT technology facilitates the effortless transcription of customer calls without requiring manual input from agents. This not only useful I terms of time-saving but also helps gather extensive customer behaviour and preference data.
Although there are many security guidelines in place, verifying caller’s identity is process susceptible to fraud which also requires extra time. AI handles this task using voice recognition, offering a faster and more secure process. While matching the customers voice with an existing sample, AI reduces the risk of identity theft through false verification outcome, but also helps speed up the whole process while keeping it equally secure.
AI offers agents personalised training by utilising data-driven insights from their performance metrics and customer feedback. This approach tailors training programs to help them improve in specific areas or train them to better respond to the types of queries that they get often. This ensures highly relevant and effective training, accommodating each agent’s individual strengths and weaknesses, fostering the development of essential skills. For instance, if an agent consistently receives negative feedback on response speed, AI will concentrate on enhancing their time management skills. The outcome is a more capable and self-assured workforce, better equipped to meet customer needs efficiently.
While the implementation of AI in your call center may not seem crucial yet, moving in that direction could significantly boost competitiveness. Automation can help in resolving tasks faster and more effectively, allowing the agents to dedicate more time to complicated tasks that require human problem solving skills.