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Select a branch
Choose a location from the dropdown above to see its performance.
What Needs Your Attention
Feedback Pulse
Competitive Position
Category Comparison
Category Fingerprint — You vs Market
Radar shows shape, bars show exact gap in percentage points. Green = you lead, red = you trail.
Category × Brand Sentiment
Where You Win, Where You Lose
Net sentiment per category and brand. Rectangle size = mention volume within that brand. Green = positive, red = negative.
Response Rate
Who Actually Responds?
Percentage of reviews that received an owner response. The single most visible signal of caring.
Review Volume
Average Reviews per Location
Normalized by number of locations to avoid sampling bias. More reviews per location = stronger signal, not just more stores.
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Category Comparison
Category Radar
Radar shows shape, bars show exact gap in percentage points. Green = you lead, red = you trail.
Rating Trend
Rating Over Time
Quarterly average star rating for both entities.
Strategic SWOT Analysis
Your Strategic Position
Brand Perception Map
What Shapes Your Reputation
Bubble size = mention volume. X = net sentiment. Y = impact on brand perception. Each bubble is one category.
Based on all-time data (917 categorized mentions)
Topic Deep Dive
Where Sentiment Comes From
Inner ring = category. Middle ring = positive/negative split. Outer ring = top keywords (colored by category). Hover for detail.
Location Performance Map
Where Are the Problems?
Each bubble = one location. Size = review count, color = net sentiment. Click for detail. Auto-zooms to fit data.
Rating Over Time
Quarterly average star rating — all 4 brands
Sentiment Over Time
Quarterly net sentiment — client vs market
What Customers Talk About
Monthly mention volume per category — client reviews only. Shows which topics are growing.
AI-Detected Signals
Sentiment:
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Response Performance
Competitive Benchmark
Response Rates vs Competition
How often each brand responds — overall and to negative reviews
Response Quality
AI classifies each response: Generic (copy-paste "thank you"), Acknowledging (recognizes the issue but no action), or Actionable (offers solution, contact, or compensation)
Quality Score Benchmark
Composite AI score (0–100) based on personalization, issue acknowledgment, and actionability of responses. Higher = more helpful, specific responses
Venue Performance
Needs Improvement
Critical Gaps
High-impact reviews that haven't been addressed — AI-identified priorities