Know the one thing pulling your score down.
LTR turns every review into a 0–10 recommend score, names the theme that is moving it, and shows whether your fix worked.
One number for the GM. Evidence for every department. A page for ownership.
0–10
Recommend score
1
Main movement
5
Views: overview, drivers, topics, trends, evidence
LTR report
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Click a number. Sample data.
What is an LTR score?
LTR (Likely to Recommend) is a 0–10 score ReputationSystems computes from a property’s reviews across every connected platform. It shows the change versus the previous period, names the single topic with the largest effect on the score (the “main movement”), ranks every topic as a driver with review counts, opens each topic to the reviews behind it, charts the score by month, and generates a one-page PDF report.
Your Rating Moved. Nobody Can Say Why.
A star average hides the reason. LTR names it.
A rating is not a reason
Your average went from 4.6 to 4.4 and nobody can say why.
Too many topics
Hundreds of reviews mention dozens of things. Which one actually moves whether guests recommend you?
Fixes without receipts
You added a second agent at check-in. Did it work? Nothing tells you.
Departments hear it late
Housekeeping finds out about the AC complaints when the rating has already slipped.
Platforms disagree
Google says one thing, Booking.com another. You need one number.
Reports nobody reads
Ownership wants a page, not a spreadsheet.
ReputationSystems LTR Solves All of This
One recommend score, the driver moving it, the evidence behind it, and proof the fix worked — computed from every review, automatically.
One Score, Every Reason
Computed from every review, continuously.
The Result? One Number, Everyone Aligned
Businesses using ReputationSystems LTR find the driver behind a rating drop — and prove the fix worked in next month’s trend.
Start Your Free TrialFour Views, One Question: What Moves Whether Guests Recommend You?
Each view is the real product with sample data.
What Moves the Score
Drivers
Every topic in your reviews, ranked by how hard it pulls on the recommend score — so the week starts with the one that matters.
- 1Topics ranked by impact on the recommend score
- 2Review count beside every driver
The Evidence Behind Each Driver
Topics
Top negative and top positive topics, each with its department, review count, negative share and impact — and each opening to the reviews that created it.
- 1Negative topics with department, count and negative share
- 2Positive topics side by side, so you know what to protect
Did the Fix Work?
Trends
LTR and review average by month, with a platform breakdown underneath. A change you made shows up here — or it doesn’t.
- 1Recommend score month by month
- 2Per-platform LTR and review average
One Page for Ownership
LTR Report
Generate the LTR report from the page; it lands in the Report Library as a PDF you can download or share by link.
- 1LTR report as one of the report types
- 2Saved in the Report Library with period and date
"Our rating moved and nobody could say why. LTR named front desk wait times, housekeeping got the AC complaints the same day, and ownership got a one-page report instead of a spreadsheet."
Illustrative example · General Manager, HotelIllustrative examples based on typical customer outcomes.
1 number the GM owns
Complete Your Reputation Management Stack
LTR works even better with these features.
LTR Across Every Platform
ReputationSystems computes the score from every connected platform — no complicated setup required.
Google
Booking.com
TripAdvisor
Expedia
Airbnb
Facebook
Yelp
Trustpilot
Apple Maps
Instagram
Bing
Google Play
TikTok
LinkedIn
Reddit
Foursquare
Nextdoor
Yellow Pages
Zomato
OpenTable
DoorDash
Uber Eats
Glassdoor
Indeed
G2
Capterra
Zillow
Etsy
Houzz
AngiAutomatic Review Synchronization
Reviews sync automatically from all connected platforms — the score and its drivers stay current without manual refresh.
Research
What is one star worth in your industry?
More than most marketing budgets. Independent restaurants earn 5–9% more revenue per extra Yelp star, and an extra half-star makes a restaurant sell out 49% more often. Hotels can charge 11.2% more per rating point at the same occupancy. 69% of patients won’t consider a provider under 4.0, 70% of car buyers weigh dealer reviews, and 78% of consumers use reviews to choose a bank.
+49%
more often sold out per extra half-star — restaurants (causal)
Anderson & Magruder, Economic Journal 2012+11.2%
room rate per review point at the same occupancy — hotels
Cornell Hospitality Report, Anderson 201269%
of patients won’t consider a provider rated under 4.0 — healthcare & dental
PatientPop, Patient Perspective Survey 202178%
of consumers use online reviews when choosing a bank — financial services
Rivel Banking Research, 2024The case studies on this page are illustrative. These numbers are not — they are why a rating belongs on the same line as rent and payroll.
Published research, not ReputationSystems customer results.
Run the numbers on your own locationsFrequently Asked Questions About LTR
Get answers to common questions about this feature.
Still Have Questions?
Our team is here to help you get started.
Know the Score. Name the Reason.
Join the businesses already using ReputationSystems LTR to know what moves whether guests recommend them.
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