How to Reduce Support Ticket Volume with AI Automation

The number of support requests (tickets) is one of the biggest challenges a growing business faces. As your customer base expands, ticket volume grows with it, and hiring more staff is expensive and slow. It is rarely practical to keep adding support staff at the same rate that you add customers.

AI-powered automation offers another option. By identifying and automating your most common support requests, you can reduce ticket volume noticeably while also improving customer satisfaction. This article explains the steps.

Understanding Your Support Tickets

Before you automate anything, find out what your team spends its time on. Pull your last 90 days of support tickets and sort them into categories. Most businesses find a predictable pattern:

• Tier 1: Simple factual questions. These have clear, written answers, such as how to reset a password, what your business hours are, whether you ship internationally, and what your return policy is.
• Tier 2: Process questions. These require following written steps, such as how to update billing information, export data, or connect with a specific tool.
• Tier 3: Investigation required. These need a person to look into something, such as an order that has not arrived, an incorrect charge, or a feature that is not working as expected.
• Tier 4: Complex or sensitive. These require judgment, negotiation, or empathy, such as a cancellation where the customer might be persuaded to stay, a billing dispute, or a serious complaint.

Tiers 1 and 2 are the ones to automate. They often make up most of your ticket volume and are the easiest to automate.

Building Your Automation Strategy

Step 1: Document Your Top 30 Questions

List the 30 questions your team answers most often. For each one, write a complete, accurate answer. Do not simply link to other documents. Write the actual answer a customer needs, including specific steps, policy details, and any exceptions.

For a broader overview, read how AI handles a support queue.

Step 2: Set Up a Knowledge Base Chatbot

Add your written answers to a chatbot such as Alma. The answers become its knowledge base, meaning the information it uses to reply. In Alma, you can build them into a drag-and-drop flow (a set of questions, buttons and replies), or paste them into a field for the optional paid AI add-on. With the AI add-on, the chatbot can understand different wordings of the same question without you having to predict each one.

Step 3: Make the Chatbot the First Point of Contact

Make the chatbot the first point of contact for customer support on your website, so visitors with a question talk to the chatbot first. If the chatbot can answer, the matter is resolved without a ticket. If it cannot, it can collect the relevant details and pass them to your team.

Step 4: Review and Improve Each Week

Each week, review the questions your chatbot could not answer. These show gaps in your knowledge base. Add content to cover these topics, and the chatbot will be able to answer more over time. Within a few weeks, you should see a steady decline in the questions that need staff involvement.

Measuring the Impact

Track these measures to see the results of your automation work:

• Deflection rate. This is the percentage of customer conversations the chatbot resolves without staff involvement. Aim for a steady increase over the first few months.
• Ticket volume trend. Your total number of incoming tickets should go down after you add automation.
• Average resolution time. The chatbot resolves conversations in seconds, so your overall average resolution time should drop noticeably.
• Staff time. With fewer routine tickets, your staff should spend more of their time on complex issues. Track the ratio of simple to complex tickets per staff member.
• Customer satisfaction. Monitor customer satisfaction (CSAT) scores for both chatbot-resolved and staff-resolved conversations. A well-designed chatbot often scores as well as staff for simple questions.

Optimizing Over Time

Automation needs regular attention. To maintain and improve your deflection rate, follow these practices:

• Weekly knowledge base reviews. Spend 30 minutes each week reviewing chatbot conversations that were passed to staff. Look for patterns and add content to address them.
• Monthly metric reviews. Review your deflection rate, ticket volume, and customer satisfaction each month, and look into any decline.
• Quarterly content audits. Review your entire knowledge base every three months to make sure it is accurate. Product changes, pricing updates, and policy revisions should all appear in your chatbot's content.
• New feature documentation. Whenever you launch a new feature or service, add information about it to the knowledge base beforehand. This prevents a sudden rise in tickets from customers with questions about it.

What Your Team Gains

The purpose of reducing ticket volume is to give your support team time for their most valuable work. When staff are not occupied with password resets and policy questions, they can focus on conversations that require human skills, such as solving complex problems, building customer relationships, and finding ways to improve the product.

Everyone benefits. Customers get immediate answers to common questions and careful, unhurried help with complex issues. Staff have more meaningful work and less stress. Your business gets more efficient support, with costs that do not rise as fast as your customer numbers.

Start Reducing Tickets Today

The quickest way to begin is with your top 10 support questions. Write the answers, add them to Alma as a flow or as pasted text for the AI add-on, and put the chatbot on your website. You may see results within the first week as the chatbot begins handling those common questions. After that, expand your knowledge base and track how your ticket volume changes.

Related reading: How AI Chatbots Reduce Customer Support Tickets, AI-Powered Help Desk: Modernize Your Customer Support.

To save time, see the prebuilt support flows you can start from.