If you’re attempting to generate a report and see the following error:

“Unable to create this chart because the selected break down has more than 10,000 unique values. Please select a different break down or choose a shorter date range.”

This means you’re attempting to group the results in the chart by more than 10,000 unique values, and should choose a different attribute under “View by”.

When filtering a report based on ‘Team replied to’ this is based on the current teams that your teammates are members of. This means the results shown in a report can change if the members of your teams are updated.

When you filter or group a report with user data, this is based on a ‘snapshot’ of the user at the time when the conversation started, so it does not change over time as the user is updated.

This means conversations that would no longer match the filters for a report, will still be included if they did match the filters at the time when the conversation was created.

When viewing a report, all charts are affected by filters applied at the report level:

However, when editing an individual chart, only those filters applied to it specifically will take effect. As you can see in this example, there’s a report level filter for “channel is chat” but when editing the chart, all channels are shown with no filtering:

The conversations you can see in a report are limited based on your conversation access permissions. Read more about limiting conversation access in this article.

Some data attributes can have multiple values per conversation, like:

If you group conversations by one of these attributes, the same conversation may be represented in more than one group, leading to a higher number of conversations in total.

For example if you break down a chart by ‘Conversation tag’, a single conversation with two unique tags will appear in 2 columns:

Customer satisfaction is the overall percentage of your conversations rated with 😁 or 🤩. For example, If 90 out of 100 conversations received a positive rating, customer satisfaction is 90%.

If you apply a filter based on ‘Conversation rating’ you may end up with an incorrect value for Customer satisfaction:

Example: