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Automation

How can I use Chatref insights to improve support for my digital product store?

Chatref Team2 min read / Updated June 17, 2026

You can use Chatref insights by reviewing conversation tags, topic clusters, and digest emails to spot common customer questions, product issues, and content gaps in your digital product store. Then refine your knowledge base and train AI agents to automatically resolve those queries, reducing support load and improving satisfaction.

How Chatref Insights Expose Support Patterns

Chatref insights automatically tags and clusters every customer conversation your store receives. For a digital product store, you’ll see which questions repeat most (license keys, download links, compatibility), which products generate the most friction, and when spikes happen. The weekly digest email highlights emerging themes, so you catch issues before they escalate.

Using Insights to Strengthen Your Knowledge Base

Armed with insight data, you can fill the exact gaps customers are stumbling over. If “how to activate my digital download” appears frequently, add a clear, RAG-grounded article to your Chatref knowledge base. The AI agent then answers that question automatically from your own docs, with no hallucinations. Each update closes a loop: insight → content → resolution.

Automating Responses with AI Agents

Once your knowledge base covers the high-frequency topics, Chatref’s AI agents can deflect those repeat questions entirely. The agents operate in your brand voice, handle license lookups or delivery status checks through custom actions, and hand off to a human only when needed. The insights dashboard then confirms which topics are being fully resolved by the agent, proving the automation works.

FAQ

What kind of insights does Chatref provide?

Chatref provides conversation tags that cluster similar customer questions, automatically detected topic trends, and a weekly digest email that highlights rising issues. You can see which products, pages, or steps in the purchase journey prompt the most support chats, and which knowledge base articles are (or aren’t) resolving those queries.

How to interpret and use these insights?

Start by sorting tags by volume to find your top support drivers. For each high-volume topic, check the agent’s resolution rate. If the rate is low, the knowledge base likely needs a clearer or more specific article. Add that content and monitor the insight data again after a week to see if the topic’s chat volume drops. Use the digest email to spot issues that surfaced overnight, like a broken download link, before support tickets pile up.

Can Chatref insights help in reducing support tickets?

Yes. Insights turn raw conversation data into a prioritised fix list. By closing knowledge gaps and letting AI agents handle routine questions (delivery, activation, returns), you prevent those tickets from ever reaching your inbox. Stores that regularly act on insight data typically see a steady reduction in human-touch tickets, freeing your team to focus on complex or high-value customer conversations.

Put this into practice

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