A practical guide: Using a Zendesk conversational bot to pre fill issue type for agents

Kenneth Pangan
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Kenneth Pangan

Amogh Sarda
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Amogh Sarda

Last edited October 29, 2025

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We’ve all seen it. A new ticket lands in the queue, and the first thing an agent has to do is play detective. They read the message, try to figure out what the customer actually wants, assign an issue type, add some tags, and then maybe, finally, route it to the right person. Each one is just a small, repetitive task, but multiply that by hundreds of tickets a day, and you’re looking at a huge chunk of your team’s time just vanishing into thin air.

Shouldn't a support bot make life easier for everyone, agents included? It’s not enough for a bot to just deflect simple questions. It should be smart enough to gather the right info and get the ticket ready for a human, setting them up to solve the problem faster.

Let's walk through how Zendesk's own tools try to tackle this, the roadblocks you'll likely hit, and a much cleaner, more powerful way to get this workflow automated for good.

What is a Zendesk conversational bot to pre-fill issue type for agents?

Zendesk's main AI tool is called the AI Agent (you might remember it as Answer Bot). It’s built right into the Zendesk Suite, and its primary job is to help customers find answers on their own. It hooks into your Zendesk Guide (your help center) and uses those articles to answer common questions before a human has to step in.

You set up its behavior using the "bot builder," which is a visual editor where you drag and drop steps to map out a conversation. You can make it send a message, offer a few buttons, or point to a help center article. For basic Q&A, it gets the job done.

But what about the trickier stuff, like automatically categorizing a ticket or filling in fields based on the conversation? While the bot is decent at deflecting FAQs, its ability to actually perform actions within a workflow is where things start to get a little messy.

Native methods: Using Zendesk's bot to pre-fill issue types

If you want to get a Zendesk bot to classify tickets for you, you'll soon discover there's the "official" way of doing it, and then there's the workaround that everyone ends up using. Spoiler: neither is a perfect solution.

The intended method: 'Ask for details' and 'transfer to agent'

On paper, the process in Zendesk's bot builder looks pretty simple. You'd use two main steps to make it happen:

  1. First, you'd add an "Ask for details" step. This is where you’d ask something like, "What can I help you with today? Is this a billing issue or a technical problem?"

  2. The customer's reply gets stored as a variable in the bot's memory.

  3. Then, in the "Transfer to agent" step, you map that variable to your "Issue Type" custom ticket field.

That’s the textbook approach, but it often falls apart in practice. Many support teams have found that while this works okay for simple text fields, it can be buggy or just plain fail when you try to populate custom dropdown fields, which is exactly how most of us manage issue types. This little snag forces most people to hunt for another way.

A common workaround: A clunky dance of tags and triggers

Because of the dropdown field issue, a clever but messy workaround has become the standard. It involves making the bot and Zendesk's automation engine work together in a multi-step process.

Here’s the breakdown:

  1. In the bot builder, you set up the conversation so that if a user picks a certain path (like saying they have a billing question), the bot slaps a specific tag on the conversation, for example "issue_billing".

  2. When the conversation gets handed off to an agent, a ticket is created with that tag already attached.

  3. Now, you have to go to a completely different part of Zendesk and build a Trigger. This is an automation that runs separately from the bot. You set this trigger to watch all incoming tickets.

  4. When a ticket shows up with the "issue_billing" tag, the trigger kicks in and sets the "Issue Type" dropdown to "Billing."

It works, technically, but it's far from a clean fix. You're basically using one system to leave a breadcrumb for another system to (hopefully) find and act on. It's a fragile setup.

Limitations of the native Zendesk bot

This workaround might seem manageable for one or two issue types, but it quickly spirals into a massive headache as your support operation grows.

  • Reddit
    It’s a nightmare to scale: As one Reddit user neatly put it, managing this system is 'a pain when you have many branches.'
    Every time you want to add a new issue type, you have to create a new tag in the bot and a whole new trigger to go with it. Soon enough, you're drowning in a sea of tags and triggers that are nearly impossible to keep track of, let alone troubleshoot.

  • Your logic is split all over the place: The conversational part is in the bot builder, but the part that actually does the work is hidden away in the Triggers menu. This makes it incredibly hard to see how your workflow actually functions from end to end. If you change a tag in the bot but forget to update the trigger, the whole thing just breaks without warning.

  • It has no real-time context: The Zendesk bot only knows what the user tells it in that moment. It can't quickly check an order status in Shopify or look up a customer's subscription plan in your database to figure out how to best classify the ticket.

These headaches are why many teams start looking for tools that can handle these actions directly, without relying on a rickety bridge of tags and triggers. An AI agent that can just update ticket fields on its own is a much more stable solution.

A better way: Using a dedicated AI platform

Instead of wrestling with a bot that was designed for deflecting simple questions, a more modern approach is to use a dedicated AI platform that plugs right into your helpdesk.

What is an AI agent integration?

An AI agent integration is a specialized AI tool built to connect directly with the software you already rely on, like Zendesk. The real beauty of this is that you get powerful new AI features without having to rip out your existing helpdesk and start from scratch.

For example, a platform like eesel AI connects to Zendesk in a few minutes. It doesn't replace your helpdesk; it works inside of it, giving it a fully customizable workflow engine that’s built for exactly this kind of automation.

Key capabilities that improve on the native bot

A truly useful AI integration doesn't just chat, it acts. Here’s what a more capable solution brings to the table, solving the very problems Zendesk's native bot creates.

  • Direct ticket actions: The AI should be able to set any field on a ticket, whether it’s a dropdown, text field, or checkbox, as a normal step in its workflow. This gets rid of the tag-and-trigger workaround completely. All the logic lives in one single, easy-to-manage place.

  • Custom API calls for context: A smart AI agent can ping other systems in real time to get the context it needs. It can check a subscription status, find an order in Shopify, or verify a user's details in your internal database. It then uses that info to accurately classify the ticket before an agent even lays eyes on it.

  • Unified knowledge sources: To understand issues correctly, an AI needs to learn from more than just your public-facing help docs. The best platforms can be trained on your past tickets, internal wikis like Confluence, and shared Google Docs. This helps them grasp the nuances of your customers' problems and your brand's voice.

  • Risk-free simulation: You shouldn't have to launch a new automation and just hope for the best. A critical feature is the ability to test your AI on thousands of your past tickets in a safe environment. This lets you see exactly how it would have classified them, giving you a solid forecast of its accuracy before you ever show it to a live customer.

This image shows an AI agent directly adding an action block, a key capability for a Zendesk conversational bot to pre-fill issue type for agents, eliminating the need for complex workarounds.
This image shows an AI agent directly adding an action block, a key capability for a Zendesk conversational bot to pre-fill issue type for agents, eliminating the need for complex workarounds.

With the workflow engine in eesel AI, you could build a single rule that says, "If the user mentions 'refund,' call the Shopify API to check the order date. If it's within 30 days, set the Issue Type to 'Return Eligible' and tag the ticket for the returns team." This entire process is built and managed in one spot and can be safely tested before you flip the switch.

Zendesk AI pricing

To get access to Zendesk's AI, you usually need to be on one of their "Suite" plans. While some AI features are included, unlocking the more powerful stuff needed for real automation often means upgrading to a more expensive plan or buying add-ons.

Here’s a quick look at their AI-inclusive plans:

PlanPrice (per agent/month, billed annually)Key AI Features Included
Suite Team$55AI agents (Essential), Generative replies, 1 help center
Suite Professional$115Everything in Team, plus up to 5 help centers, CSAT surveys, skills-based routing
Suite Enterprise$169Everything in Professional, plus up to 300 help centers, custom agent roles, sandbox environment
Add-onsVariesAdvanced AI agents, Copilot, Quality Assurance, Workforce Management

The main catch here is the potential for costs to climb quickly and unpredictably. To get the functionality you need for solid automation, you might find yourself on a pricey enterprise plan plus a few add-ons, which can turn into a serious investment.

This is a big contrast to the clear, predictable pricing you see with integrated platforms. eesel AI, for instance, includes its core AI Agent and AI Triage products in every plan. The pricing is based on a straightforward number of AI interactions, with no surprise per-resolution fees, making it much easier to budget for.

Moving beyond Zendesk's native bot

While Zendesk's native bot is a decent first step for handling simple questions, it just wasn't designed for heavy-duty workflow automation like pre-filling ticket fields. The workarounds are flimsy, a pain to manage, and just don't hold up as your business gets bigger.

A dedicated AI integration like eesel AI gives you the control and flexibility needed for true automation, all while fitting neatly into the Zendesk setup your team already uses every day.

Instead of just deflecting tickets, you can start preparing them intelligently. This saves your agents a ton of time and lets them focus on what they’re best at: solving tricky customer problems. You can go live in minutes, not months; keep total control over your workflows; and test everything with confidence using powerful simulation tools.

Take the next step: Upgrade your Zendesk automation with eesel AI

Stop making your agents do the bot's cleanup work. See how easily you can automate ticket classification in Zendesk with a self-serve AI platform built for the job. You can connect your helpdesk in minutes and start building smarter workflows today.

Start a Free Trial of eesel AI or Book a Demo.

Frequently asked questions

Its primary goal is to automate the initial classification of incoming support tickets. By gathering information from the customer during a bot conversation, it aims to automatically set the correct "issue type" field, saving agents from manual categorization.

The native bot often struggles with populating custom dropdown fields directly, which are commonly used for issue types. This limitation frequently necessitates relying on a workaround involving tags and separate Zendesk triggers, which can be buggy and complex to manage.

Scaling becomes a nightmare because each new issue type requires creating a specific tag in the bot and a corresponding trigger. This leads to fragmented logic spread across multiple systems, making it hard to maintain, troubleshoot, and keep track of as your support operation grows.

Zendesk's native bot primarily relies on information provided by the user in the conversation or from your help center. It lacks the built-in capability to perform custom API calls to external systems for real-time contextual data, such as checking order status or subscription details.

Dedicated AI platforms offer direct ticket actions, allowing them to set any field on a ticket without relying on workarounds. They can also make custom API calls for real-time context and learn from a wider range of knowledge sources, centralizing all workflow logic for easier management.

To unlock more powerful automation features with Zendesk's native AI, you often need to upgrade to higher-tier "Suite" plans or purchase additional add-ons. This can make the total cost unpredictable and significantly higher for achieving comprehensive solutions.

With Zendesk's native bot, robust pre-deployment testing for complex workflows is limited. Dedicated AI platforms, however, often provide simulation tools that let you test the bot's accuracy on thousands of past tickets in a safe environment, offering a solid forecast of its performance.

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Kenneth Pangan

Writer and marketer for over ten years, Kenneth Pangan splits his time between history, politics, and art with plenty of interruptions from his dogs demanding attention.