Reports

Build saved charts over your mentions—metrics, grouping, breakdowns, chart types, and filters.

Reports let you explore trends in your workspace’s mentions: volume over time, splits by platform or AI tags, averages, and more. Each report combines a query (what to measure and how to bucket it), a chart type, and filters so you can reuse the same view later.

Open Analytics → Reports in SnitchFeed to create or edit reports.

SnitchFeed analytics report: stacked bar chart of mentions by day with breakdown by AI tags; Query and chart controls for metric, group by, breakdown by, and chart type; Filters section with time range and filter dropdowns

Create or update a report

  1. In the left sidebar, choose New report or select an existing saved report.
  2. Enter a Report name (for example “High relevance LinkedIn”).
  3. Adjust Query and chart and Filters—the chart preview updates as you change settings.
  4. Click Save report to store a new definition, or Update report after editing a saved one (you’ll confirm before overwriting).

Use Reset to discard unsaved changes back to the last saved version (or the default empty draft). Saved reports also support Duplicate and Delete from the builder toolbar.

Query and chart

These four controls define what the chart shows. The subtitle under the report title summarizes the current combination (for example “Mentions grouped by Day, breakdown by Tags”).

Metric

What is counted or aggregated on the vertical axis:

  • Mentions — Count of matching mentions in each bucket.
  • Unique authors — Distinct authors in each bucket.
  • Avg. sentiment — Average sentiment score per bucket.
  • Avg. relevance — Average relevance score per bucket.

Group by

How the horizontal axis (or primary categories) is built:

  • Day — One bucket per calendar day in the selected range.
  • Platform — Reddit, LinkedIn, X, Bluesky, Hacker News, etc.
  • Sentiment — Sentiment bands from your data.
  • Relevance — Relevance bands from your data.
  • Tags — AI-assigned tags (for example Buy intent, Competitor mention).
  • Keyword — Matched listener keywords.
  • Subreddit — Reddit subreddit (shown when Reddit is part of your data).
  • Language — Detected language.
  • Listener — Which listener produced the match.

Breakdown by

Optional second dimension that splits each Group by bucket into segments—ideal for stacked bar/area charts or comparing series. Choose None for a single series per bucket.

Options: Platform, Sentiment, Relevance, Language, Listener, Tags.

If you pick a breakdown and had Donut selected, the UI switches to a stacked chart style so segments display correctly.

Chart type

Pick how the query is visualized:

  • Line
  • Area
  • Stacked area
  • Bar (grouped)
  • Stacked bar
  • Horizontal bar
  • Stacked horizontal bar
  • Donut

Try stacked bar or stacked area when Breakdown by is set so each segment maps to a color in the legend (as in the screenshot).

Filters

Filters limit which mentions feed the chart—same concepts as the feed, scoped to this report.

Time range sits in the Filters card header. Use a preset (for example Past 14 days) or a custom start/end range.

Additional filters (grid below):

FilterPurpose
Include listenersOnly mentions from selected listeners.
PlatformsRestrict to specific networks.
Include keywordsMention must match at least one of these keywords.
Exclude keywordsDrop mentions matching these keywords.
Seen vs NewAll, only unseen (new), or only already seen.
Relevance scoreRestrict to mentions in chosen relevance bands.
SentimentRestrict to chosen sentiment buckets.
Include tagsMention must include one of these AI tags.
Exclude tagsRemove mentions with these AI tags.
Include subredditsReddit-only: allow listed subreddits.
Exclude subredditsReddit-only: remove listed subreddits.
LanguagesKeep mentions in the selected languages.

Badges on filter chips (for example “1” on Platforms) indicate how many values are active.

Examples for GTM and marketing teams

Use these as templates—rename them, narrow Time range, and tie Include listeners to the workspaces that matter for your funnel or brand.

Go-to-market (pipeline and revenue signals)

Report ideaQueryFilters (typical)Why it helps
Buying-conversation pulseMentions, Group by: Day, Breakdown by: Tags, Stacked barInclude tags: Buy intent (and related tags your workspace uses); optional Relevance score for high bands onlyWeek-over-week view of intent-tagged chatter without digging the feed.
Intent by listener / motionMentions, Group by: Listener, Breakdown by: Tags or Platform, Stacked horizontal barInclude listeners: one per ICP, competitor, or “jobs to be done” motionCompare which listening lines produce the most actionable volume.
Quality of inbound (not just volume)Avg. relevance, Group by: Day, Line or AreaInclude listeners focused on commercial keywordsSpot drift: lots of matches but relevance trending down means tuning listeners or keywords.
Who is entering the conversationUnique authors, Group by: Day, Breakdown by: Platform, Stacked areaSame listeners you use for outbound or ABMGrowth in distinct people talking—not duplicate threads from the same accounts.

Marketing (brand, campaigns, and narrative)

Report ideaQueryFilters (typical)Why it helps
Brand vs competitor noiseMentions, Group by: Day, Breakdown by: Tags, Stacked barTags like Brand mention vs Competitor mention, or separate reports per Include listenersSee whether competitor spikes correlate with campaigns or PR.
Channel mixMentions, Group by: Platform, Bar (grouped) or DonutOptional Include listeners per product lineDecide where to spend creative or community time (LinkedIn vs Reddit vs X).
Sentiment trendAvg. sentiment, Group by: Day, LineInclude listeners for brand or campaign keywordsTrack whether narrative is warming or cooling after launches.
Themes by keywordMentions, Group by: Keyword, Horizontal barTight Time range (e.g. launch window)Which tracked phrases show up most—good for messaging and SEO hooks.
LinkedIn executive motion onlyMentions, Group by: Day, Breakdown by: TagsPlatforms: LinkedIn; optional Relevance scoreMarketing reporting skewed to professional context without Reddit/X noise.

Reddit-heavy programs

If Reddit is core to your motion, add Include subreddits / Exclude subreddits to any of the above, or use Group by: Subreddit with Mentions to see which communities carry the conversation.

Tips

  • Start with Mentions, Group by: Day, and Breakdown by: Tags to see how AI tags trend over time (like the example above).
  • Tighten Time range and Include listeners when you want a report focused on one campaign or brand line.
  • Use Avg. relevance or Avg. sentiment with Group by: Day or Listener to track quality over time, not just volume.

Reports complement the live feed: use the feed for individual posts and reports for aggregates and trends.

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