Audience Health Report
Snapshot preview · last 20 posts
One-page summary
This snapshot summarizes patterns across your recent posts — not individual performance in isolation.
Audience health
Mixed Signals
Drift
Potential drift
Confidence
Moderate
Key takeaways
- Signals suggest audience behavior may be shifting relative to your baseline.
- Feedback strength moved unevenly across the set.
- Early response patterns are mixed, limiting interpretability.
Verdict map
Here’s what changed across your last posts, relative to your recent norm (this snapshot).
Feedback strength
Feedback stayed close to your baseline.
What this means
This reflects how much meaningful feedback your audience provides per view, relative to your recent norm. When feedback strength stays close to baseline, it becomes harder to tell whether changes are driven by audience preference or by distribution effects.
Response stability
Early response patterns are mixed.
What this means
This looks at whether early interest sustains or fades as a post reaches more viewers. Stable responses make early feedback more trustworthy, while volatile responses can signal attention that doesn’t convert into lasting interest.
Audience mix
Audience mix is estimated from limited data.
What this means
This reflects whether feedback is coming from a similar audience across posts or from varying viewer groups. Consistent audience mix strengthens comparisons between posts, while fragmented mix makes interpretation less certain.
Audience drift
Signals suggest audience behavior is shifting.
What this means
This evaluates whether audience behavior appears to be changing relative to your recent baseline. Drift doesn’t imply improvement or decline by itself — it indicates that past patterns may no longer apply as reliably.
Audience health lenses
Lenses that clarify how interpretable your signals are.
Escape rate
Some early interest fades.
Why this matters
Escape Rate reflects how quickly attention drops after initial exposure. Higher escape makes early engagement less informative, while lower escape suggests that initial interest aligns more closely with sustained audience attention.
Audience stability
Audience behavior is present but uneven.
Why this matters
Audience Stability indicates whether feedback patterns remain consistent across posts. Stable audiences make it easier to learn from experiments, while unstable audiences increase the risk of drawing conclusions from noise.
Returning engagement (RER)
Returning engagement is inferred.
Why this matters
Returning Engagement (RER) estimates whether interaction is coming from a familiar, repeat audience versus transient viewers. Higher repeat engagement generally produces clearer, more interpretable feedback signals.
Signal breakdown
Labels are primary; numbers are supporting detail.
Feedback strength
Helps distinguish passive consumption from meaningful response.
How to interpret this signal
This signal helps distinguish between posts that generate passive consumption and those that prompt meaningful audience response. Stronger feedback per view increases confidence that reactions reflect genuine audience interest.
Response stability
Assesses whether interest sustains over time.
How to interpret this signal
This signal helps assess whether engagement represents durable interest or short-lived curiosity. When response stability is unclear or unavailable, conclusions drawn from early performance should be treated cautiously.
Audience mix
Contextualizes feedback by audience consistency.
How to interpret this signal
This signal helps contextualize feedback by identifying whether reactions come from a consistent audience base. Changes in audience mix can alter how comparable posts are, even when engagement levels appear similar.