Filter, slice, and pivot every data point Crescendo collects. Drill into any cell to re-slice the dashboard. Everything below — chat, competitor radar, recommendations — stays in sync.
Sentiment
Star range
Platform
Time range
Search review text
Top themes (948 unique)
Reputation pulse
MONO+MONO — 4.2★ across 1,000 reviews
Rating, sentiment, volume over time
Last 10
4.50★
Recent cohort
Lifetime
4.16★
All-time
Trend
+0.34
Up
Category × sentiment
Click any cell to drill in — the chart on the left re-slices.
Your line is bold; each competitor is a dashed overlay. Look for spokes where a competitor juts past you — those are the stealable wins, ranked by gap size in the Reputation tab.
PERSONA BREAKDOWN
Who's actually leaving these reviews
Cohorts derived from review patterns, sorted by share. Each row shows persona size, avg rating, estimated LTV, and churn risk.
Persona matrix — volume vs rating
X-axis: % of reviews · Y-axis: avg rating · Size: review count. Full detail on the Reputation tab.
7 cohorts derived from review patterns — sorted by share. LTV and risk model how much each cohort is worth, and how much you stand to lose if they churn.
The Quiet Loyalist32.7% of reviewers 4.3~$1,560 LTVlow risk
The Delighted Regular17.9% of reviewers 5.0~$3,851 LTVlow risk
The Conflicted Critic11.4% of reviewers 3.3~$820 LTVmed risk
The Content Casual11.3% of reviewers 4.7~$3,621 LTVlow risk
The Disappointed Optimist10.5% of reviewers 1.9~$517 LTVhigh risk
The Satisfied Explorer10.0% of reviewers 4.4~$3,683 LTVlow risk
The Devoted Fan6.2% of reviewers 5.0~$3,934 LTVlow risk
STRATEGIC RECOMMENDATIONS
What we'd build if we ran this business
Five to seven projects, ranked by estimated annual dollar impact. Regenerate any project for a different angle — Crescendo won't repeat what's already in the list.
Projects · ranked by dollar impact
Scope · outcome · why now · expand any card for the full detail
1Growth·$8-12K effort·4-5 weeks
What we'd build
Value Perception & Upsell Intelligence Engine
AI that analyzes 'overpriced' complaints to optimize menu positioning and creates targeted upsell opportunities.
Expected outcome
Increase average ticket by 12-18% while reducing price-related complaints by 50%
Why now
10 'overpriced' complaints despite strong food quality scores suggest a value communication problem, not a pricing problem - customers love the food but feel misled about expectations.
Cost of inaction
Price sensitivity complaints compound over time and drive down conversion rates. Each month without addressing value perception, MONO+MONO loses ~15% of price-conscious diners who would otherwise return if expectations were properly set.
~$194k/yr lift
2Visibility·$5-10K effort·3-4 weeks
What we'd build
Korean Fried Chicken Discovery Content Pipeline
AI-powered content engine that generates SEO-optimized content around signature dishes customers love but aren't finding.
~$145k/yr lift
3Reputation·$10-15K effort·4-6 weeks
What we'd build
AI Service Recovery & Response Automation Engine
Custom AI that monitors reviews, auto-responds to complaints, and triggers proactive service recovery workflows.
~$113k/yr lift
4Operations·$10-15K effort·5-6 weeks
What we'd build
Predictive Staffing & Service Quality Monitor
AI system that predicts busy periods and alerts management to service quality risks before they become complaints.
~$81k/yr lift
5Operations·$5-8K effort·2-3 weeks
What we'd build
Voice AI Table Management & Wait Experience
Intelligent phone system that handles reservations and transforms wait times into positive experiences.
~$81k/yr lift
6Intelligence·$7-10K effort·3-4 weeks
What we'd build
Customer Sentiment & Return Visit Predictor
AI dashboard that scores every diner interaction and automates targeted re-engagement campaigns for at-risk customers.