AI assistants are closing the gaps in customer service
Oct 10 • 4 min read
According to Gartner, Inc., “25% of customer service and support operations will integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, up from less than 2% in 2017.”
Customers want to feel like they’re being listened to – 84% of customers say being treated like a person, not a number, is very important to winning their business.
Also, they don’t like waiting for responses, they want quick solutions- forgotten passwords, refunds, security concern… these types of queries need quick answers. If a customer is left waiting too long, they might switch to a provider that offers a faster and better customer experience. According to a study, 75% of online customers expect help within 5 minutes and the preferred channels are voice or chat.
And that’s where an AI assistant works well!
An integral part of all businesses, organisations are always working on providing faster and better customer service by automating different customer service activities. By implementing chatbots and virtual assistants a lot of businesses have already strengthened their customer service and as artificial intelligence advances, business integrations with AI assistants are becoming more refined.
The effortlessness and swiftness of these assistants are setting a new standard for customer service. Customers now expect things to be a simple text or voice command away.
Let’s see how AI assistants can add value to your customer service
1. Help Agents Communicate Effectively With The Customers
When sharing a query, the customers most of the times are not sure what details they should share making it the responsibility of the agents to understand the issues faced by the customers.
But for an agent, asking the right questions, noticing customer behaviour patterns, and answering common queries can get repetitive and sometimes the critical details can be missed.
To address this communication gap, AI assistants convert natural language into machine language through Natural Language Processing (NLP). Syntactic analysis and Semantic analysis are used to complete NLP tasks.
2. Fill Knowledge Gaps
Even for support agents, it can sometimes get tricky to keep up with the latest product updates creating knowledge gaps. These knowledge gaps can be filled with the help of automated virtual customer assistants (VCA).
If you’ve ever had a concern regarding some product or services and connected with a support team you must have raised a support ticket. The VCA works on creating and then resolving the support ticket. It receives all information, past and present, related to the customer’s inquiry by using machine learning algorithms and suggests articles to resolve the issues. And, if the VCA does not have the resolution, it works across other supported channels to assist the customer.
3. Leverage Real-Time Insights
The advancements in AI is helping with a better interpretation of unstructured data, from both text and voice conversations. The amalgamation of data and AI has enabled many businesses to understand their customers on a better level. It helps businesses know what their customers want and lets them engage with them in a better way.
Based on the customer conversation, biometrics, voiceprint, businesses are able to make smarter decisions based on real-time insight.
4. Well Equipped Agents For Meeting Customer Expectations
It is the difference between customer expectations and customer perceptions that creates the gap. Customers expect the support agents to be empathetic, and the ones who can give a solution to their problems.
AI across many sectors is helping support agents analyze whether or not the customer expectations are met. AI-powered machine learning can predict if a customer is left satisfied for a particular ticket and it is through this data that you can up your support game.
5. Recommender System
By establishing the context of user search customer experiences can be made swift by leveraging search history, location data, time to determine what the customer is looking for and suggest recommendations accordingly.
6. Prioritize Customer Service Issues
“76% of customers expect companies to understand their needs and expectations.” Salesforce
Humans can’t work 24/7 but AI-assisted machines can. For providing efficient support, it is crucial to detect urgent issues and with AI tools such as the urgency detector model and sentiment analysis, businesses can detect and configure urgent matters.
AI unleashing disruption across various aspects of CX.
With evolving AI, the opportunities to combine customer data to enhance customer satisfaction by creating sophisticated customer journey analytics, simplify customer interactions, deliver meaningful messages is becoming endless.
“Only 38% of U.S. consumers say the employees they interact with understand their needs; 46% of consumers outside the U.S. say the same.” PWC
Customer expectations are increasing and to bridge the gap businesses are looking for advanced technological capabilities equipping their customer service teams with artificial intelligence tools. To craft joyful and memorable customer experiences the paramount qualities remain human touch, empathy and emotional intelligence. It is by combining these human elements with AI that your organisation can further amplify CX.