Report Metrics

Statusbrew supports over 230 reporting metrics and KPIs. Explore this section to discover the available metrics

Tag Insights In Statusbrew

With the Tag Insights Report, you can view a breakdown of applied tags on sent and received conversations. You can also gain insights into trends, sentiment, and daily volume.

Configuring The Report

You can create a Tag Insights Report using a template in Reports.

  1. Go to Reports.

  2. Click Create a new report from the sidebar.

  3. Select Use a template.

  4. Find the Tag Inbound report template. You can use the search bar for it or find it in Brand Insights > Inbound Analysis section.

  5. Click Use template under the Tag Inbound template. The New Report window will open.

  6. By default, the Report name pulls the name of the template. You can modify it and even change the icon.

  7. Add a Report description.

  8. Select Data sources. By default, all the Data Sources have been selected. You can deselect the ones whose data you don’t want to pull.

  9. Include Collaborators by clicking Add collaborator and select the user/user group. You can give me either Edit or View permission for the report.

  10. Click Create.

Or you can also create a custom report.

Report Widgets

The Tag Insights Report contains multiple widgets:

Summary widget

The Summary widget gives you a quick snapshot of how tags are being applied across your conversations within the selected time period.

The widget displays three key metrics:

  • Total Tagged Conversations (Sent and Received): Shows the overall number of tagged conversations, along with the percentage increase or decrease compared to the previous period.

  • On Received Messages: Highlights how many inbound messages were tagged.

  • On Sent Messages: Reflects how many outbound messages were tagged.

Breakdown

The Breakdown widget provides a visual “bird’s-eye view” of which tags are being applied most often to conversations. Tags with higher message volumes appear in larger, bolder text, while tags with lower usage appear smaller.

This widget makes it easy to spot recurring themes and common customer feedback categories at a glance. For example, if “Pricing Query” appears prominently, it indicates that a large portion of customer conversations relate to this topic. The visual weight of each tag helps you identify trending topics that may require immediate attention.

Daily Tagged Messages

The Daily Tagged Messages widget tracks the number of tagged conversations by date, giving you a timeline view of tagging activity across the reporting period. Each point on the chart represents the total number of sent and received conversations that were tagged on that day.

This widget helps you identify spikes or dips in conversation topics.

By Volume (Table View)

The By Volume widget breaks down tagged conversations in a sortable table format, displaying the total number of messages associated with each tag. Alongside message counts, you’ll also see percentage increases or decreases compared to the previous reporting period, helping you track growth or decline in the usage of each tag.

This structured view is especially useful for drilling into the most frequently applied tags, spotting trends in conversation, and understanding which topics are gaining or losing relevance with your audience. For example, an increase in “CX Feedback” tagging signal growing engagement with customer experience, while a drop in “Product Bug” tags indicates fewer user issues.

Tagging Trend

The Tagging Trend widget shows how different tags are applied across conversations on a day-to-day basis. Each colored area represents a tag, with the height of the area showing the number of times that tag was used on a given day.

This view helps you spot patterns in specific topics over time.

By Network

The By Network widget breaks down tagged conversations by the social network or channel they came from (e.g., Facebook, Instagram, LinkedIn, X/Twitter, TikTok, App Store, etc.). The visualization uses a treemap, where the size of each block represents the total number of tagged messages from that network.

This makes it easy to see where the bulk of your conversations are happening, which channels drive the most tagged activity, and where your team should focus resources. For example, if Facebook dominates the chart, it means most customer interactions are happening there.

By Type

The By Type widget breaks down tagged conversations by message format (e.g., Facebook Comment, Instagram Message, TikTok Message, LinkedIn Comment, Web Article, YouTube Video). Each bar represents the number of tagged conversations of that type.

It helps your team evaluate how tagging usage differs between conversation types and prioritize responses accordingly.

By Sentiment

The By Sentiment widget categorizes tagged conversations by sentiment: Positive, Neutral, Negative, or Mixed. The pie chart visualization gives you a quick understanding of the overall audience sentiment and how it shifts over time.

Monitoring this distribution helps you assess customer satisfaction, detect risks, and measure improvements in customer experience. For instance, a rise in negative sentiment conversations indicates decreasing customer service experiences, something for your support team to think about

By Language

The By Language widget breaks down tagged conversations by the language of the message. The bar chart shows the total number of tagged conversations in each language across your connected profiles.

This insight helps global teams understand which languages dominate customer interactions and where localized support might be necessary.

Filters

Use the filters to view the most important data in your Tag Insights Report.

For instance, use the Networks filter to select the social or reviews profiles you want to view tag Insights data for. Use the Tags filter to select specific tags you want to view performance data for.

You can also select a date range to analyze tagging activity for a specific time frame — whether that’s a week, a month, a quarter, or a custom timeframe.

You can also compare and analyze how the tagging performance for the current reporting period compares to the preceding period.