Social Listening Report Synthesizer

Example output

Social listening synthesis — Glimmer kombucha, 30-day export

Headline: mention volume nearly tripled, but the growth is concentrated in a single-day spike, not a sustained lift — treat this as one viral moment to capitalize on, not yet a durable trend shift, until the post-spike baseline is confirmed.

Volume read
Total mentions: 2,400, up from 900 in the prior 30 days (a genuine increase even excluding the spike day). Of the 1,500-mention increase, roughly 800 mentions (53% of the total increase) landed on day 19 alone, tied to the TikTok video you flagged. Subtracting the spike, the underlying daily mention rate still grew meaningfully — this is not purely a one-day artifact, but the headline "nearly tripled" figure is doing more work than the underlying trend supports on its own.

Sentiment read
62% positive / 24% neutral / 14% negative is a healthy split on its face. What the topline hides: check whether sentiment on the spike day itself differs from the surrounding 29 days — a viral moment can carry disproportionately positive or polarized sentiment that skews the 30-day blended number. Recommend re-running the sentiment split with day 19 excluded to see the "steady-state" sentiment your brand carries outside of viral moments. Flagging as an assumption to validate: whether the 14% negative cluster concentrates around one specific complaint or is spread thin across many small ones, since those call for very different responses.

Theme clusters
1. Gut health / functional benefit — the most positive and most frequent theme; this is your strongest organic asset in the conversation right now and likely worth leaning into deliberately rather than leaving to chance virality.
2. "Too fizzy" — a recurring product-experience complaint. This is specific and actionable enough to route to your product or QA team rather than treat as generic negative sentiment; it is a formulation or carbonation-consistency signal, not a brand-sentiment problem.
3. New can design — mixed mentions; the data as pasted doesn't clearly separate positive versus negative reaction to the design itself. Recommend pulling a sentiment-tagged view of just the "can design" keyword cluster before concluding shoppers like or dislike it.

Platforms and voices
The export doesn't specify a platform breakdown beyond noting the day-19 spike was TikTok-driven. Before briefing the exec team, pull the platform split for the full 30 days — a gut-health conversation living mainly on TikTok versus spread across Instagram, Reddit, and TikTok changes both the durability read and where you'd invest to sustain it.

What this means for Glimmer
The gut-health association is real, organic, and worth amplifying deliberately. The "too fizzy" theme is a concrete product signal, not just noise, and should go to product/QA this week regardless of the broader trend question. The can-design reaction needs its own clean read before you treat it as validated or rejected.

Flag: this synthesis is built entirely from the export numbers and keywords you pasted; it does not independently verify mention authenticity, bot activity, or the actual content of individual posts beyond what the keywords suggest.

Recommended actions
1. Re-run sentiment with day 19 isolated to see steady-state versus spike sentiment.
2. Route the "too fizzy" theme to product/QA as a concrete signal, independent of the trend question.
3. Pull a clean can-design-only sentiment view before drawing a conclusion either way.
4. Get the full platform breakdown before the exec brief, since TikTok-driven spikes behave differently than sustained cross-platform conversation.

Want a one-slide version of this for the stand-up, or a draft brief for the exec team once the day-19-isolated sentiment comes back?