Social listening
Listening lets Sift watch public social platforms for the words that matter to you. You choose keywords, Sift collects every public post that mentions them, and a Listener decides which posts your team sees: keep the real conversations, archive the noise. Every decision is explained in plain English, and nothing is deleted along the way.
At a glance
| Keyword collection on X, Threads, Instagram hashtags, TikTok, YouTube | ✅ |
| TikTok and YouTube match spoken audio and on-screen text | ✅ |
| Keep / skip rules written as chips, no query language | ✅ |
| Every archived post shows the exact rule that archived it | ✅ |
| Volume, keep rate, and sentiment charts in Analytics | ✅ |
| Slack alerts for watch conditions and volume spikes | ✅ |
| One-click promote of an archived post to the inbox | ✅ |
| CSV export of the current view | ✅ |
| History in the Listen feed | Up to 365 days (archived detail kept 180 days) |
| Posts older than 90 days | ❌ never collected, the feed stays current |
What you're looking at
The Listen page shows every post your keywords pulled in. A funnel across the top counts Pulled, Kept, Archived, and Actions for the current filters. The gallery view leads with the media; the stream view shows one row per post with the Listener that matched it, the matched term, the intake decision, sentiment, and tags.
Open any post to see the full text, the AI media summary, and the listening context: which Listener matched it and why it was kept or archived. An archived post names the exact rule it failed, as a sentence. If the filter got it wrong, promote the post back to the inbox with one click.
How a Listener works
A Listener is a small program around your keywords, in three steps:
- Collect: the keywords Sift sweeps for, per platform.
- Keep: rules that separate signal from noise. Keep posts that mention your product, skip the stock chatter, require a minimum follower count, or filter by source or channel. Skipped posts go to a reviewable archive, never to trash.
- Watch: alert conditions that run after AI analysis. When a kept post matches (for example, negative sentiment), Sift sends a Slack alert. Volume spikes alert on their own: if a Listener suddenly pulls far more than its usual volume, your team hears about it within the hour.
Before a Listener goes live, Check setup validates every rule and previews expected volume from posts Sift has already seen. Publishing is always a human decision.
Analytics
The Listening tab in Analytics charts the feed: mentions over time split by kept and archived, volume by platform, sentiment of kept mentions, and a per-Listener breakdown with keep rates. Sift AI can chart the same data in chat: ask it for listening volume over the last 30 days.
Who can do what
- Managers can view the Listen feed, promote archived posts, and export CSVs.
- Sift configures Listeners with you: rules, sources, and alert delivery are set up by our team so collection volume stays intentional.
Tips
- Skip rules are the fastest cleanup: three or four words (like "stocks" or "giveaway") remove most noise.
- Review the archive during the first week of a new Listener. Promoting a false positive also tells you which rule to loosen.
- Ask Sift AI "why was that post archived?": it reads the same rules the dashboard shows.