Zia Actions: AI-powered Workflow Automation for Faster and Smarter Execution

Hello everyone,

Workflows got a notch better with AI-based actions.

Actions such as field extraction, prediction, auto reply, and content generation facilitate quick execution with improved speed and accuracy. Zia can intercept useful details in newly created tickets and accelerate the automation flow.

A typical support ticket contains essential details of the customer, issue they are reporting about, sometimes transaction details and previous conversation with support agents. AI-powered actions can analyze the ticket content and extract the necessary field values, predict severity, and also draft a suitable response for the email and send it to the customer.

This kind of orchestration aims to improve process and team efficiency at a granular level which eventually impacts the overall support quality.

Some common advantages are:

1. The speed at which things are done is significantly higher.
   
2. Accuracy of the resultant actions is better.
3. FRT and ticket reopening rates are considerably low.
4. Consistent replies that follow business guidelines.
5. Agent efficiency is improved as much of the routine work is taken care of by Zia.
6. Improved CSAT with customers getting quick, accurate replies instantly.
7. Better business outcome with processes becoming more agile and efficient.

Field extraction

Zia can extract values such as email, phone number, due date, case type, product code, order number etc. from the ticket conversation and autopopulate them in the ticket.

For example, educational institutions or insurance companies can benefit from this as students or customers usually share essential information in their email. It's quick and error-free when the information is taken directly from the email, reducing inadvertent manual errors.

The image below shows an email from a student seeking assistance for a study material. Zia identifies and extracts the exam code, student ID, contact number, registration date and admission follow-up date from the email and fills the values in the relevant fields.

Field prediction

Zia can analyze the email content, thread replies, subject, description, and several other fields available in the layout to predict values for specific fields. It evaluates the content and automatically maps the values to the most relevant field.

For example, it can analyze the description and the thread replies in the ticket to predict when the student would opt for an admission and fill the correct value in the field Admission on: "Autumn 2025 batch". Likewise, it can predict the VISA status and update the field to"Awaited" or "Delayed". If an email notification is sent to the VISA handling team, they can reach out and provide the necessary assistance.

Content generation

Zia can summarize the customer requirement and highlight the main points discussed in the email in a concise, easy-to-consume text for the agents to take quick appropriate actions. The summary is auto- populated in the private comment, public comment or in a multi-line text field as configured in the workflow.

For example, if a customer sends an email for onboarding with an on-site implementation request and enquiring about a long-term facility to provide a continuous training certification to its employees, Zia can analyze the thread content, ticket subject, description, and prompt, such as: "Summarize the ticket conversation, highlight the list of requirements, and mention the urgency of the request" to generate a summary which can be added as a private comment for the concerned stakeholders to refer.

Auto email reply

Using workflow, automatic emails replies can be sent to customers' tickets with answers that are generated by the Answer Bot along with related article links from the knowledge base.

For example, enquiries about product installation, issues with setting up accounts, and password retrievals can be auto-resolved using Answer Bot's information retrieval and Zia's email composing capabilities.

This significantly reduces the number of tickets that agents handle manually. Smart routing and auto-resolving of tickets can improve agent productivity and overall process efficiency. A wide-range of technical problems, IT related issues, and maintenance glitches can be categorized and easily resolved by AI using the company's troubleshooting tips, user manuals, or best practice guides that are cost-effective ways to improve support operations across the company.

These features are now available for all users in the following DCs: US, EU, IN, and AU.

For information regarding configuration and other details kindly refer to the help doc.

Regards,

Anumita Gupta

Desk User Education

• Topic Participants

• Anumita Gupta

  

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