E-commerce
June 28, 2026
When customers contact support for information that should be visible on the site, the ticket reveals an information gap. This can concern a product sheet, a delivery page, a return policy, a size guide, or the checkout.
The chatbot can help group these requests and identify the pages that need to be corrected. The objective is to reduce avoidable contacts and help customers before they get blocked.
This guide shows how to detect information gaps on your website using support tickets.
Summary
What is an information breakdown?
An information gap appears when the customer seeks an answer but cannot find it in the right place, at the right time, or in understandable language. Support then becomes the fallback solution.
The problem is not always the complete absence of information. Sometimes, the information exists but it is too low on the page, too technical, or contradictory.
A recurring ticket is often the symptom of misplaced information.
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Which tickets should be monitored?
Monitor questions regarding delivery, returns, size, compatibility, package contents, payment, promo codes, subscription, warranty, availability, and installation.
Pre-purchase tickets are particularly useful, as they highlight the doubts that might block conversion.
How to locate the page in question?
Each ticket must be linked to a page or a step: product page, category, cart, checkout, account, FAQ, email, or policy page. Without localization, the fix remains unclear.
The chatbot can ask where the customer was blocked or detect the navigation context when the data is available.
How do you prioritize corrections?
Priority depends on volume, conversion impact, return risk, support cost, severity of the error, and ease of correction.
How to check the correction?
After updating, it is necessary to measure whether the number of questions actually decreases. Otherwise, the information might still be poorly placed, poorly phrased, or not visible on mobile devices.
Agents must also be informed of the new source to respond consistently.
Which flow to follow?
The flow must connect the ticket and the content.
Group tickets by question, product, page, step, channel, and frequency.
Identify if the information is missing, misplaced, too technical, or contradictory.
Prioritize based on volume, impact, support cost, return risk, and ease of correction.
Update the help sheet, FAQ, checkout, email, or guide with a validated response.
Measure the drop in tickets, conversion, returns, and satisfaction after correction.
Which examples should be used?
Repeated questions about “free returns ?” may signal that the policy is too far from the shopping cart. Inquiries about “which size to choose ?” can justify a more visible size guide.
Tickets regarding “where is my invoice ?” can reveal that the account area or the confirmation email do not explain the next steps clearly enough.
When not to edit the site?
It is better not to modify a page for an isolated request, an exception, or unverified information. The site must meet frequent needs, not accumulate all special cases.
The chatbot can handle exceptions or transfer to support.
Which KPIs should be monitored?
Track avoidable tickets, corrected pages, reduction in queries, conversion after correction, feedback, clicks on help, satisfaction, and resolution time.
These indicators show whether the site is becoming more self-sufficient for the customer.
Which mistakes should be avoided?
Avoid treating tickets as solely a support issue, publishing unverified answers, forgetting about mobile, or never measuring the effect of fixes.
Tickets should feed into a clearer website, not just a larger knowledge base.
How can Qstomy help?
Qstomy can connect the chatbot to orders, carriers, delivery slots, deposit rules, support tickets, website content, and escalation procedures to answer clearly, then transfer sensitive cases with an actionable summary.
The chatbot helps the customer move forward without inventing proof of delivery, a guaranteed slot, a carrier timeframe, a deposit refund, or product information that still needs to be confirmed by a reliable source.
Explore AI support, the AI sales agent, or request a demo.
Key takeaways
Takeaways
Support tickets reveal information that is missing, misplaced, too technical, or contradictory on the site.
What the client needs to understand
The client must find key answers before contacting support.
The right limit of the chatbot
The chatbot can detect breakdowns, but corrections must be validated, placed in the right spot, and measured.
Enzo
June 28, 2026
