Hotel review management
- intercept detractors, protect your star rating
Hotel review management that intercepts 0-6 NPS scorers on WhatsApp + Instagram DM check-out morning - before the 1-star Tripadvisor, Google, Expedia, Hotels.com, or Booking.com review fires. Routes 9-10 Promoters to Day-2 Tripadvisor or Google review ask with per-guest throttling for first-time leisure / repeat / corporate MICE / wedding-party cohorts. AI drafts multilingual brand-voice responses in 30+ languages with full PMS stay context. Multi-platform dashboard across Tripadvisor + Booking.com (monitor-only - never an integration) + Expedia + Hotels.com + Google. GDPR-aware guest data retention, region-pinned storage. The Day-2 Promoter cohort doubles as a Day-60 OTA-direct win-back - boutique pilots shift 18-32% of repeat business OTA → direct. Star rating lifts 0.4-0.9 stars in 90 days because only happy guests see the public ask.
Casa Lumière · Lisbon
Replied in 2 min · 11:15 Sat
Powered by seekadu
Tripadvisor + Google rating stuck at 4.0-4.3
Every noisy AC, every breakfast miss, every wifi gap converts into a 1-star public review - no intercept layer between the bad night and the public ask
Post-stay email NPS opens at 12-18%
Standard post-stay confirmation email surveys hit the same dismal open rate - most happy guests never see the ask, the public review base stays thin
1-star sits unanswered for 4-9 days
Manual monitoring across Tripadvisor + Booking.com + Expedia + Hotels.com + Google means complaints stay public for nearly a week - weekend rank slides, festival-season bookings bleed
OTA commission 15-30% on every repeat stay
Booking.com + Expedia keep taking the same guest at 15-30% commission every time - no Day-60 win-back loop, no margin recovery on Promoter cohort
Trusted by businesses already using Seekadu
What a guest stay looks like with hotel review management on the line.
The same arrivals, in-stay touches, and departures happen. The difference is what fires between check-in Day 0 and the Day-60 OTA-direct win-back when a guest's experience lands off - or perfectly.
Without Seekadu
Late arrival, noisy night ahead
Mews check_in fires for Room 312 at 23:18 Fri. Guest is tired, finds the AC unit hums loudly. Tries to ignore it, can't sleep. No in-stay capture. Saturday morning the property goes silent.
Without Seekadu
Late arrival, noisy night ahead
Mews check_in fires for Room 312 at 23:18 Fri. Guest is tired, finds the AC unit hums loudly. Tries to ignore it, can't sleep. No in-stay capture. Saturday morning the property goes silent.
With Seekadu
In-stay sentiment scan armed
AI primes the in-stay sentiment loop - if any operational signal (noise, housekeeping, wifi, breakfast) hits via WhatsApp, IG DM, or website widget, it captures + routes to the night manager in real-time.
Without Seekadu
Guest stews in silence
Guest mentions noisy AC to housekeeping in passing on Day 2 - slip never reaches engineering. Day 3 the guest is exhausted, considering not coming back. Decides they'll post on Tripadvisor at check-out.
Without Seekadu
Guest stews in silence
Guest mentions noisy AC to housekeeping in passing on Day 2 - slip never reaches engineering. Day 3 the guest is exhausted, considering not coming back. Decides they'll post on Tripadvisor at check-out.
With Seekadu
In-stay WhatsApp captures grievance
Day 2 evening, a soft WhatsApp check-in - "everything good for tonight, Marco?". Guest replies about the AC. AI routes to night manager + engineering, room visit at 21:00, AC reset. Day 3 guest sleeps well.
Without Seekadu
Email NPS opens at 14%
Mews schedules the standard post-stay email NPS for Day 3. Email lands in promotions tab. Guest never sees it. Day 5 the guest opens Tripadvisor and posts the 2-star anyway from residual frustration.
Without Seekadu
Email NPS opens at 14%
Mews schedules the standard post-stay email NPS for Day 3. Email lands in promotions tab. Guest never sees it. Day 5 the guest opens Tripadvisor and posts the 2-star anyway from residual frustration.
With Seekadu
WhatsApp check-out NPS, 3-min reply
Check-out-morning WhatsApp NPS lands 11:15 Sat. Guest replies 4 by 11:18. AI captures noisy-AC grievance, offers €40 future-stay credit, opens maintenance ticket. Public review ask suppressed.
Without Seekadu
Repeat guest goes back to Booking.com
Without the intercept + Promoter tag, the guest would book the next stay via Booking.com at 17% commission. €200 stay × 17% = €34 commission paid. No relationship, no margin recovery, no review-driven loyalty.
Without Seekadu
Repeat guest goes back to Booking.com
Without the intercept + Promoter tag, the guest would book the next stay via Booking.com at 17% commission. €200 stay × 17% = €34 commission paid. No relationship, no margin recovery, no review-driven loyalty.
With Seekadu
Promoter cohort → direct-booking flow
Promoter who posted the 5-star Tripadvisor at Day-2 gets a WhatsApp DM at Day-60 with a small direct-book incentive (8% off rack, no commission). 28-31% accept the direct route - permanent margin recovery on the LTV cycle.
Want this post-stay cadence for your boutique property?
What your hotel review management actually knows.
Plug into Mews, Cloudbeds, Opera Cloud, Little Hotelier, Clock PMS, RoomRaccoon, or Hotelogix. Hotel review management reads check_out_completed, late_check_out, folio_posted, and complaint_logged events - runs check-out-morning post-stay NPS, intercepts detractors with GM resolution + future-stay credit, routes Promoters to Tripadvisor or Google, drafts multilingual brand-voice responses to every incoming public review. Monitors Booking.com / Expedia / Hotels.com read-only. Hard-codes Tripadvisor cooldown + Google response delay rules. Ties every NPS score and review back to the PMS guest profile + repeat-guest cohort.
PMS stay events
Live read from Mews / Cloudbeds / Opera Cloud / Little Hotelier / Clock PMS / RoomRaccoon / Hotelogix - check_in, check_out_completed, late_check_out, folio_posted, complaint_logged.
Post-stay NPS cadence
Check-out-morning post-stay NPS DM. 0-6 detractor → private GM resolution with future-stay credit, 7-8 passive soft-touch, 9-10 Promoter routed to Day-2 review ask. Per-guest throttling for first-time / repeat / corporate MICE / wedding-party cohorts.
Review platform connections
Tripadvisor + Google Business Profile via the Google Reviews integration. Booking.com + Expedia + Hotels.com monitored read-only - never an integration claim. Auto-request via connected widget on Tripadvisor + Google.
Multilingual response engine
AI drafts brand-voice responses with PMS stay context (room type, rate plan, repeat-guest status, in-stay complaints) in 30+ languages - never folio detail or guest identity in public. GM or ops-lead approval required on every negative review.
GDPR + escalation rules
Region-pinned storage, encrypted at rest + in transit, GDPR DPA on file for EU/UK properties. Tripadvisor cooldown (90d between asks), Google response delay (24h reflection window before auto-publish). Maintenance ticket auto-open on operational grievances (noise, wifi, housekeeping, breakfast).
Seekadu AI
Trained
PMS stay events
Mews + 6 more
Check-out NPS
Day-0 cadence
Review platforms
Tripadvisor + 5
GDPR-aware data
DPA on file
Per-guest throttle
Leisure / MICE / repeat
Multilingual draft
30+ languages
Detractor → repeat
GM resolution
OTA-direct shift
Day-60 win-back
Every post-stay moment - intercepted + asked + responded + recovered.
From a check-out-morning NPS intercept on a noisy-AC complaint to a multilingual Tripadvisor response in PT to a Day-60 OTA-direct win-back on a 5-star Promoter - hotel review management handles every reputation moment with full PMS sync and GDPR-aware guardrails.
Check-out-morning post-stay NPS DM intercepts 0-6 scorers before they hit Tripadvisor or Google.
Mews check_out_completed fires for Room 312 at 10:48 Sat. By 11:02, a WhatsApp Business API template message lands in the guest's language with a short NPS - "How was your stay with us at Casa Lumière, 0-10?". The guest scores 4 and types "the AC was noisy all night, hard to sleep". Hotel review management never sends the public Tripadvisor or Google ask. Instead the AI captures the grievance (noisy AC - operational not clinical), offers a private GM resolution (€40 future-stay credit, complimentary upgrade on next visit), opens a maintenance ticket for Room 312 AC unit with the front-desk ops board, and escalates to your CRM with stay context. 40-60% of low-scorers accept the private path. The 1-star Tripadvisor never happens - and the property keeps a future-repeat guest instead of losing one to a public complaint.
- Mews / Cloudbeds / Opera Cloud / Little Hotelier / Clock PMS / RoomRaccoon / Hotelogix check_out_completed → check-out-morning WhatsApp / IG DM NPS
- 0-6 Detractor → private GM resolution within 24h with future-stay credit + room-rate refund options
- 7-8 Passive → soft follow-up, no public review ask sent
- 9-10 Promoter → Day-2 review ask routed to Tripadvisor or Google Business Profile
- 40-60% intercept rate on detractors who would otherwise post a public 1-star - operational grievance opens maintenance ticket auto
Detractor intercepted · 1-star Tripadvisor avoided · €40 credit issued · Maintenance ticket logged
Where does your hotel review management live?
How hotel review management moves star rating + detractor recovery + OTA-direct shift.
Illustrative - outcome ranges modelled on our pilot boutique hotels and published benchmarks (STR, Hotelmize, Tripadvisor, Booking.com transparency). Individual results vary.
Detractor intercept rate - 0-6 NPS scorers who accept private GM resolution over a public 1-star (vs 0% email-only baseline)
Tripadvisor + Google star rating lift in 90 days (vs untargeted post-stay email ask)
OTA → direct shift on repeat-guest cohort over 12 months via the Day-60 Promoter win-back
4 min
Median multilingual draft-to-GM-approval time across Tripadvisor + Google
+25-45%
Detractor → repeat-guest recovery rate inside 60 days when GM resolution accepted
97%
Public-review response rate vs 30-50% baseline without AI drafts
30+
Languages supported for multilingual draft across international leisure properties
What boutique hotels on Seekadu typically see.
Illustrative profiles modelled on real outcome ranges across our pilot hotel cohort - names and exact figures composite, not individual guest quotes.
Elena Marques
GM, Casa Lumière · 18 rooms · Lisbon
We sat at 4.1 on Tripadvisor - every noisy-AC night, every late check-in, every breakfast miss became a 1-star. Layered Seekadu's check-out-morning NPS on top of Mews, didn't touch the post-stay email flow. Caught 51% of detractors privately with a €40 future-stay credit. Tripadvisor rating climbed to 4.7 in 90 days and the public review base doubled in PT, EN, ES, FR, DE.
4.1 → 4.7
Tripadvisor star rating
90 days post-launch
51%
Detractor intercept rate
private GM resolution
+2.1x
Public review volume
Day-2 Promoter ask
15 min
Setup
to first check-out NPS DM
Stefan Becker
Owner, Hotel Mitte · 32 rooms · Berlin
Berlin city-break crowd is unforgiving - one noisy-night review on Booking.com kills your weekend rank. We moved post-stay NPS to WhatsApp at check-out. 48% of low-scorers accepted the private GM path with a complimentary upgrade. 31% came back for a direct booking inside 60 days. Booking.com rating stable, Google + Tripadvisor up 0.6 stars each, and our direct-booking share went from 18% to 31% - a permanent margin win.
48%
Detractor intercept rate
WhatsApp check-out NPS
31%
Detractor → repeat-direct guest
60-day return rate
+0.6
Tripadvisor + Google lift
in 75 days
18 → 31%
Direct-booking share
OTA-direct shift
Fiona MacKenzie
Manager, Royal Mile House · 12 rooms · Edinburgh
Edinburgh festival season pushes 4,000 stays in 3 weeks - international guests from 20+ countries. Post-stay email NPS opened at 12%. WhatsApp NPS opens at 91%. The AI drafted multilingual responses in 30+ languages - Italian, French, German, Spanish, Dutch, Portuguese. Response rate moved from 28% to 97%. Median draft-to-publish 4 minutes. Festival-season Tripadvisor rating held at 4.7 despite 5x the review volume.
97%
Public-review response rate
vs 28% baseline
4 min
Median draft-to-publish time
Tripadvisor + Google
6
Languages supported
IT · FR · DE · ES · NL · PT
4.7
Tripadvisor rating, festival peak
held across 4,000 stays / 3 weeks
Made Sutrisna
Co-owner, Ubud Lotus Retreat · 24 rooms · Bali
Bali boutique means 80% international leisure - Tripadvisor and Google decide whether we get booked. Google rating was 4.2; we were falling behind 4.5+ competitors on map-pack. The AI ran check-out-morning NPS in EN, sent the Promoter ask to Google for the first 60 days. Google rating moved to 4.8 in 75 days, map-pack queries +44%, direct-bookings via WhatsApp +28%. Detractor intercept on noisy-spa and slow-wifi grievances saved 12-15 1-star reviews per quarter.
4.2 → 4.8
Google star rating
75-day window
+44%
Map-pack queries
Google local discovery
+28%
Direct-booking lift via WhatsApp
OTA share recovery
12-15
1-star reviews intercepted
per quarter
Joan Puig
Group GM, Costa Brava Boutique Group · 48 rooms · Girona
4 properties, 5 OTA review surfaces each, 30+ languages - manual monitoring meant 1-star reviews sat unanswered for 4-9 days. Seekadu's unified inbox routes per property + per platform + sentiment + complaint cluster. GMs respond inside 2 hours. Group Tripadvisor rating moved 4.3 → 4.7 across all 4 properties in 4 months. The Booking.com monitoring-only approach is honest - we never claim to integrate, we just read the reviews and draft brand-voice responses our team posts on Booking.com directly.
4.3 → 4.7
Group Tripadvisor rating
4-month window · 4 properties
<2h
Median first-response time
vs 4-9 days manual baseline
20
Review surfaces monitored
4 properties × 5 platforms
0
Booking.com integration claims
monitoring-only honesty
Elena Marques
GM, Casa Lumière · 18 rooms · Lisbon
We sat at 4.1 on Tripadvisor - every noisy-AC night, every late check-in, every breakfast miss became a 1-star. Layered Seekadu's check-out-morning NPS on top of Mews, didn't touch the post-stay email flow. Caught 51% of detractors privately with a €40 future-stay credit. Tripadvisor rating climbed to 4.7 in 90 days and the public review base doubled in PT, EN, ES, FR, DE.
4.1 → 4.7
Tripadvisor star rating
90 days post-launch
51%
Detractor intercept rate
private GM resolution
+2.1x
Public review volume
Day-2 Promoter ask
15 min
Setup
to first check-out NPS DM
Stefan Becker
Owner, Hotel Mitte · 32 rooms · Berlin
Berlin city-break crowd is unforgiving - one noisy-night review on Booking.com kills your weekend rank. We moved post-stay NPS to WhatsApp at check-out. 48% of low-scorers accepted the private GM path with a complimentary upgrade. 31% came back for a direct booking inside 60 days. Booking.com rating stable, Google + Tripadvisor up 0.6 stars each, and our direct-booking share went from 18% to 31% - a permanent margin win.
48%
Detractor intercept rate
WhatsApp check-out NPS
31%
Detractor → repeat-direct guest
60-day return rate
+0.6
Tripadvisor + Google lift
in 75 days
18 → 31%
Direct-booking share
OTA-direct shift
Fiona MacKenzie
Manager, Royal Mile House · 12 rooms · Edinburgh
Edinburgh festival season pushes 4,000 stays in 3 weeks - international guests from 20+ countries. Post-stay email NPS opened at 12%. WhatsApp NPS opens at 91%. The AI drafted multilingual responses in 30+ languages - Italian, French, German, Spanish, Dutch, Portuguese. Response rate moved from 28% to 97%. Median draft-to-publish 4 minutes. Festival-season Tripadvisor rating held at 4.7 despite 5x the review volume.
97%
Public-review response rate
vs 28% baseline
4 min
Median draft-to-publish time
Tripadvisor + Google
6
Languages supported
IT · FR · DE · ES · NL · PT
4.7
Tripadvisor rating, festival peak
held across 4,000 stays / 3 weeks
Made Sutrisna
Co-owner, Ubud Lotus Retreat · 24 rooms · Bali
Bali boutique means 80% international leisure - Tripadvisor and Google decide whether we get booked. Google rating was 4.2; we were falling behind 4.5+ competitors on map-pack. The AI ran check-out-morning NPS in EN, sent the Promoter ask to Google for the first 60 days. Google rating moved to 4.8 in 75 days, map-pack queries +44%, direct-bookings via WhatsApp +28%. Detractor intercept on noisy-spa and slow-wifi grievances saved 12-15 1-star reviews per quarter.
4.2 → 4.8
Google star rating
75-day window
+44%
Map-pack queries
Google local discovery
+28%
Direct-booking lift via WhatsApp
OTA share recovery
12-15
1-star reviews intercepted
per quarter
Joan Puig
Group GM, Costa Brava Boutique Group · 48 rooms · Girona
4 properties, 5 OTA review surfaces each, 30+ languages - manual monitoring meant 1-star reviews sat unanswered for 4-9 days. Seekadu's unified inbox routes per property + per platform + sentiment + complaint cluster. GMs respond inside 2 hours. Group Tripadvisor rating moved 4.3 → 4.7 across all 4 properties in 4 months. The Booking.com monitoring-only approach is honest - we never claim to integrate, we just read the reviews and draft brand-voice responses our team posts on Booking.com directly.
4.3 → 4.7
Group Tripadvisor rating
4-month window · 4 properties
<2h
Median first-response time
vs 4-9 days manual baseline
20
Review surfaces monitored
4 properties × 5 platforms
0
Booking.com integration claims
monitoring-only honesty
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Boutique hotel + small-chain questions, answered.
Everything GMs + revenue managers + ops leads ask before switching on hotel review management.
Book a demo for your property →Intercept every detractor. Ask every Promoter. Recover OTA margin on every repeat stay.
For 8-22 room boutique hotel GMs running without a 24/7 front desk - Hotel review management - runs natively on Mews, Cloudbeds, Opera Cloud, Little Hotelier, Clock PMS, RoomRaccoon, Hotelogix. Check-out-morning post-stay NPS intercepts unhappy guests on WhatsApp + IG DM before the 1-star Tripadvisor or Google review fires. Day-2 Promoter ask routes happy guests to Tripadvisor + Google with per-cohort throttling. Multilingual brand-voice responses in 30+ languages with full PMS stay context - always GM or ops-lead approved. Multi-platform monitoring across Tripadvisor + Booking.com (read-only - never an integration) + Expedia + Hotels.com + Google. GDPR DPA on file for EU/UK properties. Day-60 OTA-direct win-back captures repeat-guest margin via WhatsApp direct booking. Live in 15 minutes once Meta approves your template set (1-3 business days).
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