Analytics
Build saved charts over your mentions—metrics, grouping, breakdowns, chart types, and filters.
Analytics in SnitchFeed means saved reports: explore trends in your workspace’s mentions—volume over time, splits by platform or intent signals, 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.
Create or update a report
- In the left sidebar, choose New report or select an existing saved report.
- Enter a Report name (for example “High Fit Score LinkedIn”).
- Adjust Query and chart and Filters—the chart preview updates as you change settings.
- 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 Intents”).
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. Fit Score — Average Fit 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.
- Fit Score — Fit Score bands from your data.
- Intents — AI-detected intent signals (for example Buying 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, Fit Score, Language, Listener, Intents.
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):
| Filter | Purpose |
|---|---|
| Include listeners | Only mentions from selected listeners. |
| Platforms | Restrict to specific networks. |
| Include keywords | Mention must match at least one of these keywords. |
| Exclude keywords | Drop mentions matching these keywords. |
| Seen vs New | All, only unseen (new), or only already seen. |
| Fit Score | Restrict to mentions in chosen Fit Score bands. |
| Sentiment | Restrict to chosen sentiment buckets. |
| Include intents | Mention must include one of these intent signals. |
| Exclude intents | Remove mentions with these intent signals. |
| Include subreddits | Reddit-only: allow listed subreddits. |
| Exclude subreddits | Reddit-only: remove listed subreddits. |
| Languages | Keep 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 idea | Query | Filters (typical) | Why it helps |
|---|---|---|---|
| Buying-conversation pulse | Mentions, Group by: Day, Breakdown by: Intents, Stacked bar | Include intents: Buying Intent (and related signals your workspace uses); optional Fit Score for high bands only | Week-over-week view of intent-tagged chatter without digging the feed. |
| Intent by listener / motion | Mentions, Group by: Listener, Breakdown by: Intents or Platform, Stacked horizontal bar | Include listeners: one per ICP, competitor, or “jobs to be done” motion | Compare which listening lines produce the most actionable volume. |
| Quality of inbound (not just volume) | Avg. Fit Score, Group by: Day, Line or Area | Include listeners focused on commercial keywords | Spot drift: lots of matches but Fit Score trending down means tuning listeners or keywords. |
| Who is entering the conversation | Unique authors, Group by: Day, Breakdown by: Platform, Stacked area | Same listeners you use for outbound or ABM | Growth in distinct people talking—not duplicate threads from the same accounts. |
Marketing (brand, campaigns, and narrative)
| Report idea | Query | Filters (typical) | Why it helps |
|---|---|---|---|
| Brand vs competitor noise | Mentions, Group by: Day, Breakdown by: Intents, Stacked bar | Intents like Brand Mention vs Competitor Mention, or separate reports per Include listeners | See whether competitor spikes correlate with campaigns or PR. |
| Channel mix | Mentions, Group by: Platform, Bar (grouped) or Donut | Optional Include listeners per product line | Decide where to spend creative or community time (LinkedIn vs Reddit vs X). |
| Sentiment trend | Avg. sentiment, Group by: Day, Line | Include listeners for brand or campaign keywords | Track whether narrative is warming or cooling after launches. |
| Themes by keyword | Mentions, Group by: Keyword, Horizontal bar | Tight Time range (e.g. launch window) | Which tracked phrases show up most—good for messaging and SEO hooks. |
| LinkedIn executive motion only | Mentions, Group by: Day, Breakdown by: Intents | Platforms: LinkedIn; optional Fit Score | Marketing 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: Intents to see how intent signals 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. Fit Score or Avg. sentiment with Group by: Day or Listener to track quality over time, not just volume.
Saved reports complement the live feed: use the feed for individual posts and analytics for aggregates and trends.