Ratings matter less as a score and more as a filter. Nobody should be chasing a rating percentage as a target. The real value is that ratings tell you which conversations are worth reading, which turns an impossible task, reviewing everything, into a fifteen-minute weekly habit of reading only the ones that went wrong.
Reading them well takes a little care. Only a minority of visitors rate anything, so the sample is skewed toward strong reactions in both directions. A thumbs down does not always mean the answer was factually wrong; sometimes it means the answer was correct and the visitor did not like it, such as a price or a lead time. Group ratings by topic rather than counting them in aggregate, because a cluster of negatives on one subject is actionable in a way that an overall percentage never is. A rising negative rate on a specific topic often shows up weeks before a drop in captured leads.
Clerkzo saves conversations with thumbs up and down ratings attached and connects them to a corrections loop, so the route from a visitor's negative signal to a fixed answer is short. Used weekly, that loop is what keeps a chat widget getting better instead of quietly drifting out of date.
Related terms
Browse all 142 terms- Conversation FlowConversation flow is the path a chat takes from the opening message to a resolution, including the order questions are asked, the branches available and the points where the conversation can end or transfer to a human.
- Conversation ContextConversation context is the complete set of information a chatbot has available when composing a reply, including the earlier messages in the conversation and any content retrieved from its knowledge base for the current question.
- First-contact resolutionFirst-contact resolution (FCR) is the share of customer enquiries that are completely resolved during the first interaction, without the customer needing to follow up or be called back.
- Customer satisfaction scoreCustomer satisfaction score (CSAT) is a metric that measures how satisfied a customer was with a specific interaction, collected by asking them to rate the experience immediately afterwards.