A strategic guide to configuring and sending a CSAT survey when a conversation is closed

We all know customer feedback is gold, but let's be honest, asking for it the wrong way can backfire. A badly timed or out-of-place Customer Satisfaction (CSAT) survey can feel like just another piece of junk in a customer's inbox. That's the last thing you want right after you’ve solved their problem.

The trouble is, many support teams are still stuck using clunky, manual rules to send these surveys. This approach just doesn't have enough context to be smart about it, which often leads to people ignoring your surveys or giving low-quality feedback.

This guide will walk you through the old-school ways of configuring and sending a CSAT survey when a conversation is closed. We'll dig into their weak spots and then look at a much smarter, AI-powered way to get feedback that actually helps you make things better for your customers.

What is a post-conversation CSAT survey?

Customer Satisfaction (CSAT) is really just a straightforward way to measure how happy a customer is with a single, recent interaction with your team. It’s that quick "How did we do?" question you get after a chat or email support ticket is closed.

That moment right after a conversation ends is the perfect time to ask for feedback. The whole experience is still fresh in the customer's mind, so you’re more likely to get an honest and detailed response. This feedback is super valuable for a few reasons:

• Checking in on performance: It gives you a clear look at how individual agents and the entire team are performing.

• Finding the gaps: A string of low scores might point to a missing help article in your knowledge base or a step in your process that’s just plain confusing.

• Catching trends: You can start to see recurring problems or complaints that could signal a bigger issue with your product or service.

CSAT surveys are usually kept simple: think a 1-5 rating scale, happy/sad emojis, or a thumbs-up/thumbs-down. The whole point is to make it as painless as possible for the customer to give you a quick answer.

The traditional way of sending CSAT surveys

Most help desks, including big names like Zendesk and Intercom, lean on rule-based automation to send out CSAT surveys. In plain English, that means someone on your team has to manually build a workflow that tells the system exactly when to send the survey.

Triggers and manual automations

Typically, a support manager or admin has to dive into their help desk’s settings and build a workflow from the ground up. It usually boils down to a simple command like: "WHEN a ticket status is changed to 'Solved,' THEN send the CSAT survey email."

It sounds simple enough, but platforms like Zendesk and Intercom require you to carefully click through multiple steps to set up the right conditions, triggers, and actions. You have to spell out the exact criteria for when the survey goes out, what it says, and how it’s delivered. It’s a completely manual job that puts all the pressure on you to design the logic.

Problems with manual workflows

This system can get the survey out the door, but it’s not very smart and has some common flaws that can mess with the quality of your feedback.

• It has no clue what actually happened: The system can't tell the difference between a simple "thank you" and a frustrating, multi-day back-and-forth. It just sends the survey anyway, which can feel pretty tone-deaf to a customer who just had a rough time.

• It causes survey fatigue: Sending a survey after every single closed ticket is a great way to annoy your customers, especially the ones who reach out often. Do it enough, and your response rates will plummet.

• The rules are too rigid: Want to set up more detailed rules, like "don't send a survey if the customer got one in the last month"? That often requires complicated workarounds or might not even be possible. You’re forced into a one-size-fits-all approach that doesn’t really fit anyone.

• The data is isolated: The CSAT score often ends up as just a number on a dashboard. It's completely disconnected from the why behind the rating, making it tough to find useful ideas to actually improve your support.

Zendesk vs. Intercom

Let's see how two of the most popular platforms handle their built-in CSAT tools. Both of them rely on you to build and manage these workflows by hand.

Zendesk

Zendesk's CSAT feature is centered around its "Automations" and "Triggers" engine. To get it working, you have to lay out specific conditions, like "Ticket > Status category | Changed to | Solved". While their newer CSAT feature lets you add more questions, it’s still running on the same rigid trigger system. The basic feature is available on most plans, but if you want more advanced customization and reporting, you’ll have to upgrade to pricier tiers like Suite Growth ($115/agent/mo) and Professional ($149/agent/mo). Intercom

Intercom uses its "Workflows" feature to send CSAT surveys. The setup process has you choose a trigger, such as "Conversation closed by teammate," and then add steps like "Ask for conversation rating." It does offer some branching logic (for instance, if the rating is bad, you can ask a follow-up question), which gives you a bit more flexibility. But at the end of the day, every single step and condition is still set up by hand. To even get access to Workflows and CSAT surveys, you need their Pro plan, which starts at $39 per seat per month and goes up from there.

Feature	Zendesk	Intercom
Setup Method	Triggers & Automations	Workflows
Flexibility	Moderate (based on ticket properties)	High (branching logic)
Context Awareness	Low (relies on ticket data only)	Low (relies on ticket data only)
Pricing Model	Included in most Support plans	Requires higher-tier plans

A smarter, AI-powered approach to CSAT surveys

So, what's the alternative? This is where AI starts to look pretty interesting. It offers a way to make the entire feedback process more intelligent, contextual, and, well, useful.

Moving beyond rigid triggers with AI

Instead of just relying on a simple "ticket closed" trigger, an AI agent can analyze the content and feeling of the entire conversation before it decides what to do next.

For example, an AI can tell the difference between a genuine "Thank you so much, that fixed it!" and a sarcastic "Sure, whatever." It would know to only send a survey in the first scenario, helping you avoid those awkward follow-ups with customers who are already annoyed.

This is where a tool like eesel AI shines. It trains on all your past tickets to deeply understand your specific customer conversations and brand voice. This lets it make these kinds of smart decisions on its own, so you don't have to build dozens of complex "if-then" rules.

Automating the full feedback loop

A truly intelligent system doesn't stop at just sending a survey; it actually closes the loop on the feedback it gets. An AI-powered workflow can analyze what the customer says and take a meaningful next step.

Picture this: a conversation is closed, and the AI reads the sentiment. If it’s positive, it sends a CSAT survey. If it’s negative, it can automatically pass the ticket to a manager and tag it for review. When a customer leaves positive feedback on the survey, the AI can tag them as a 'Happy Customer'. But if the feedback is bad, the AI can analyze the comment to figure out the root cause, flag a potential gap in your knowledge base, and even draft a new help article to stop the same problem from happening again.

A workflow diagram illustrating how eesel AI automates the customer support and feedback process from ticket analysis to resolution.

This is exactly what eesel AI is built to do. It turns feedback from a static number into an active, automated system that helps you get better over time.

How eesel AI simplifies CSAT surveys

Think about the complicated, multi-step setups in other tools, and then compare it to eesel AI's more direct approach.

• Get started in minutes: With one-click help desk integrations, you can get set up on your own without having to sit through sales calls or mandatory demos. You don't have to ditch your current tools, either; eesel plugs right in.

• You're in the driver's seat: The easy-to-use prompt editor lets you define exactly how you want the AI to handle post-conversation follow-ups. You can customize its tone, persona, and the specific actions it takes, giving you full control over the process.

• Test it out without any risk: eesel AI has a powerful simulation mode that lets you test your feedback workflows on thousands of your actual past tickets. You can see exactly how the AI would have performed and get accurate predictions on response rates before you ever turn it on for live customers. This takes away the guesswork and the fear of annoying users with a poorly set-up workflow.

A screenshot of the eesel AI simulation mode, showing how users can test feedback workflows on past tickets before activation.

Best practices for CSAT surveys

Whether you're sticking with a traditional system or moving to an AI-powered one, here are a few good habits to get into for your CSAT strategy.

Timing your surveys for maximum impact

Sending the survey right after closing a ticket is usually the way to go since the interaction is fresh. But for more complicated or sensitive issues, waiting an hour or two might give the customer a chance to cool off and leave more thoughtful feedback. An advanced tool like eesel AI can even learn the best timing based on the type of conversation.

Asking more than "How did we do?"

Your CSAT survey should always have an optional, open-ended question like, "Anything else you'd like to share?" This is especially important for negative reviews because it gives you the story behind the low score. While platforms like Intercom let you do this with manual branching, an AI agent can dynamically ask a more relevant question based on what was actually discussed.

Acting on feedback

Collecting feedback is a waste of time if you don't act on it. Make it a regular habit to review your CSAT scores and, more importantly, the comments that come with them. That's where the real gems are hidden. Tools like eesel AI make this easier by looking past the scores to point out knowledge gaps and trends, giving you a clear to-do list for what to fix next.

Start understanding your customers

Manually configuring and sending a CSAT survey when a conversation is closed is a decent starting point, but it's held back by inflexible rules and a serious lack of context. It treats every customer conversation as if it's the same, and we all know that's just not true.

An AI-driven approach turns feedback from a simple number into a smart, automated loop that helps you continuously improve. It lets support teams stop worrying about manual setups and start focusing on what their customers are actually telling them. By understanding the context of each conversation, you can ask for feedback in a much smarter way and turn those insights into real, meaningful changes.

Ready to build a smarter feedback loop? See how eesel AI can automate and improve your CSAT process with a risk-free simulation on your own tickets.