A customer asks your website chat: "Can I export reports to PDF?" You cannot, yet. What happens next matters more than most teams realise. The request might be lost. It might be noted in a spreadsheet nobody reads. Or it might become one data point in a clear picture of what your users need.
Feature requests arrive through chat all the time. Handled well, they are some of the most useful feedback a product team gets. Handled badly, they create frustrated users and a pile of unread notes.
Step 1: answer the question honestly
When a user asks for something your product does not do, say so clearly. Vague answers like "that's something we're looking into" without substance frustrate people.
Visitor: Can I export reports to PDF? Assistant: Not at the moment. You can export reports to CSV and open them in a spreadsheet, which some teams use to create PDFs. I can pass your request to the product team. What would you use PDF exports for?
That answer is honest, offers a workaround, and asks about the underlying need.
Step 2: capture the problem, not just the feature
"PDF export" is a solution. The problem might be "I need to send reports to clients who don't have accounts." That problem might be better solved by a shareable link. Capturing the problem gives your product team room to find the best solution.
Ask one question: what would you use it for? The answer is usually more useful than the feature name.
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Step 3: be careful with roadmap questions
Users often ask "is this on the roadmap?" The rule is simple: only share what you have published. If you have a public roadmap, the assistant can refer to it. If not, it should not guess.
Promising features or dates that are not public creates problems. Users plan around promises, and a missed date damages trust more than an honest "not currently planned."
Step 4: capture requests consistently
SpideyChat for SaaS companies can capture requests as tickets or leads with the full conversation attached, so product managers see the context. Whatever tool you use, the key is consistency: every request captured the same way, in one place.
This connects with documentation gaps. Sometimes a "feature request" is actually a feature that exists but is hard to find, a pattern covered in the feature question that means your docs are wrong. Check before logging it as a request.
Step 5: group by problem each month
Once a month, group captured requests by the problem behind them. Count how many users raised each problem, and note whether they were trial users, small customers or large accounts. Requests from buyers mid-evaluation can be especially telling, as described in qualifying demo requests before they reach sales.
This turns a scattered list into evidence for product decisions.
Step 6: close the loop
When you ship something users asked for, tell them. A short message to everyone who requested it turns a feature launch into goodwill. Users who feel heard tend to stay and to keep giving feedback.
Feature requests in other businesses
Every business gets requests for things it does not offer. Online stores hear "do you have this in another colour?", which is essentially a product request, and comparison questions reveal what customers want, as explored in product comparison questions your pages never answer. Property management firms hear requests for services, covered in an AI receptionist for property management. The same capture-and-group approach works everywhere.
Getting set up
Decide where requests will live and who reviews them. Then make sure your assistant knows what the product does, what it does not, and what is publicly planned. The training guide covers adding this information, and the installation guide covers putting the assistant on your site and docs.