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Modern virtual call centers offer a wide range of tools to make agents’ lives easier. From detailed caller IDs to integrations with customer relationship management (CRM) systems, they save time and boost your business’ efficiency.
In 2021, more and more of these tools are based on artificial intelligence (AI) and machine learning algorithms. Natural language processing (NLP), in particular, forms the basis of handy functionalities available on Contact Center as a Service (CCaaS) platforms.
Here are three of the most useful AI features that can assist your agents during calls, record and supply information, and take care of routine tasks.
Interactive virtual assistance for callers
First off, NLP algorithms can help callers either reach the right agent, or even take care of their issues directly.
Interactive Voice Response (IVR), for example, allows callers to state the purpose of their call using their own words. Then, the algorithm will route the call accordingly, to the currently available agent best equipped to deal with it. This is a huge step up in terms of customer experience – they no longer have to navigate through a complex menu of choices or listen to countless iterations of “press one for”.
More advanced, self-service assistants can help callers deal with routine tasks, freeing up agents for more complex issues. For example, booking or cancelling appointments or signalling malfunctions can easily be handled by modern AI-based assistants. These also come in particularly handy in emergency situations. For example, a website outage can easily result in a spike in call volume. The AI algorithms analyzing the conversations will register an accumulation of key issues and send up a red flag to management.
Real-time call support for agents
One of the main jobs of AI-based CCaaS tools is to make agents’ lives easier. Real-time call support assistants do just that by recording and delivering crucial information.
For example, when the caller ID of a customer who previously complained about a particular issue shows up, the AI assistant gives the agent a heads-up. Then, the algorithm automatically pulls the relevant information from the CRM database. Consequently, the customer is spared the trouble of re-explaining their problem, and the interaction can begin on a good basis.
In addition, features such as sentiment analysis can help defuse difficult situations. AI algorithms analyze real-time transcripts of the conversation in progress, and identify callers’ pain points and moods. Then, they can offer assistance to agents, such as pre-approved lines of company messaging.
Post-call analytics and insights
Finally, AI tools can help during the post-processing of calls, and offer insights into the behavior of both customers and agents.
For instance, automatically generated transcripts and summaries of calls can be saved in your CRM database for future reference. This data can also be processed automatically to assess customer satisfaction and agent performance. Consequently, the system can propose follow-ups for customers who were left frustrated, or advice for agents who tend to struggle during particular types of conversations.
At the end of the day, CCaaS tools based on AI and machine learning can be an invaluable productivity-boosting support to help take your business communications to the next level.
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