The starting point for a lot of companies is to build a self-service culture; set up a knowledge base of frequently asked questions and help customers find answers without raising support tickets. This minimises the load on the service team who can now focus on resolving complex issues more efficiently. Training the service team to use filters and views to organise their tickets is the next step in increasing productivity. It helps the team prioritise their work and see only the tickets that matter to them. This is a point where teams start using smaller utilities like keyboard shortcuts and response templates to save even more time. But there’s a whole lot of things that AI can do to help agents focus on the most important tasks. Zia in Zoho Desk is built to do just that.
Zia is an AI-driven support assistant who makes your customer support team more effective through data mining and machine learning. She provides support agents with analyses, customer forecasting, alerts and suggestions through a pre-configured system of performance analysis and metrics.
Zia also constantly learns and improves.
The more data she has to go on, the smarter she gets. Some of her capabilities are predicting anomalies and trends, analyzing customer sentiments, offering solutions and more.
Zia is a context-aware candidate we've hired for your team. Powered by AI, she can perform crucial tasks like sentiment analysis and anomaly detection. She also doubles as a conversation assistant to help customers find solutions through ASAP, Zoho Desk's in-app customer support tool.
6 Things that Zia can do for your Customer Service team:
1. Zia can talk.
Customers can speak or chat with Zia from your website or mobile apps. Zia processes customers questions and automatically answers them based on content in your knowledge base. Using a skill builder, Zia can also be trained to perform actions for customers like placing or editing an order.
2. Zia reads between the lines.
When you receive countless tickets on a day, it's not enough to reply “I understand how frustrating this can be.” Understanding whether a customer is happy or not is key to a good response that takes the conversation forward. What if you could figure out the temperament of the customer and accordingly plan your responses. Zia will help you do this.
3. ZIA plays tag.
4. She is one step ahead.
Zia acts as a smart reply assistant for tickets that makes the task of replying to them seem like a walk in the park. Zia intercepts the incoming ticket to identify the key terms from each conversation and suggests the most appropriate solution from your knowledge base. You can add these suggestions to a response with a single click and send the same to the customer. Zia is smart enough that even when an article is long and has many headings, she suggests specific paragraphs and sentences to use in a tailored response. Before an agent can start drafting their response, Zia has one typed out and ready for them. All it takes is a single click to send this out.
5. Nothing escapes ZIA.
A sudden spike or a dip from what is normal to your help desk is called an anomaly. Anomaly prediction is an effective means of identifying unusual or unexpected events that happen within Zoho Desk. Zia - your data intelligence assistant, relies on a broad spectrum of measures and methodologies to detect significant events that affect customer service experience and therefore require your attention. Zia analyses and identifies anomalies in your team's performance 24*7. When there's a sudden surge in incoming tickets, Zia warns you so you can get more hands on deck. Multiple irritated responses on a ticket? You'll hear from Zia. She even identifies issues that get the most tickets, and helps you improve the strength of your Knowledge Base.
6. Teach ZIA the skills you need.
Through a Skill Builder interface, you can teach Zia to perform actions that are relevant to your customers. This could be placing or editing an order, checking order status, or just about anything else she needs to be familiar with.
Zia brings together predictions across anomalies, sentiment, trending ticket tags, and more into a common dashboard for decision-makers to consume. They can drill down further into the details from the same dashboard to investigate further.
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