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What this is

A sentiment dashboard that scores your brand across multiple dimensions and lets you drill into negative (or positive) mentions.

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Why it matters

  • Sentiment shapes whether you’re recommended (especially in “best X” prompts).
  • Dimension-level weakness (e.g., Fees) can suppress your rank even if you’re cited.
  • It helps you prioritize which narratives to fix.

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Where to find it

Analytics → Prompt Analytics → Sentiment

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How it works

  • Meridian extracts sentiment signals from responses.
  • It summarizes:
    • Overall Sentiment Score
    • Dimension scores (Security, Reputation, Fees, etc.)
    • Breakdown by Positive/Neutral/Negative per dimension
Sentiment overview showing score tiles and sentiment breakdown Caption: Sentiment shows overall score and dimension-by-dimension breakdown.

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How to use it

  1. Set timeframe and compare to Prev. Period.
  2. Review overall Sentiment Score and its delta.
  3. Scan dimension cards for weak points (lowest scores or biggest negative deltas).
  4. In Sentiment Breakdown, hover a dimension to see positive/neutral/negative counts.
  5. Click to open Mention Details for deeper inspection.

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How to interpret results

  • If one dimension has high negative counts → it’s an active narrative problem → address it explicitly in owned content.
  • If overall sentiment is flat but “Fees” drops → pricing narrative is shifting → add transparent pricing explanations and comparisons.
  • If “Security” is strong but “Customer service” is weak → you may need proof points (SLA, support channels, response times).
  • If sentiment improves but visibility doesn’t → your issue is likely citations/rank, not narrative.
  • If sentiment drops on one platform → content sources differ by platform → optimize for that platform’s sources.

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Common questions / troubleshooting

  • “Why are some dimensions missing?” → only dimensions present in responses appear.
  • “Why does it say click to see negative mentions?” → drilldown opens the response table filtered to that dimension.
  • “Why is my score changing a lot?” → small sample size; expand timeframe.