● Solution · Hotels & serviced apartments
Resource Utilization
Empty rooms are decaying revenue. Agentrika watches occupancy, competitor rates, and live demand signals, then pushes the right price to the right channel for the right date — automatically, with min/max guardrails you set.
Featured example: hotel room dynamic pricing. Same pattern works for serviced apartments, clinics, classrooms, courts, equipment rentals.
+8–15%
RevPAR uplift
15 min
Repricing latency
100%
Decisions auditable
Pricing Pipeline · SISAV
TONIGHT · DELUXE KING
S
Signal
Occupancy 71% · pickup -12 vs forecast
I
Interpretation
Comp set median €189 · soft demand
S
Solution
Recommend €179 · LOS 2+ · direct -5%
A
Action
Push to PMS · OTAs · metasearch
V
Verification
Pickup & RevPAR vs forecast
Not “rate updated”
“+€2,840 RevPAR vs flat-rate baseline”
The yield problem
Spreadsheets and once-a-day rate decisions leave money on the table.
1×/day
most independents reprice once a day. Demand moves by the hour.
5−7
tabs a revenue manager juggles: PMS, channel manager, OTAs, comp set, demand fcst.
12%
of nights end at sub-optimal rates — either too cheap (lost ADR) or too high (empty).
Black box
most legacy RMS tools can’t explain why a rate moved. No audit trail.
How it works — SISAV cycle
A continuous loop. Every fifteen minutes, every room type, every channel.
Signal
Continuous market & inventory feed
Live ingestion from your stack and the open market. Nothing is sampled or batched overnight.
PMS occupancy, pickup, cancellations, length-of-stay distribution
Competitor rates from OTA scraping & rate-shopping APIs
Search demand: OTA wishlists, brand-site search funnel, Google Hotel Trends
Local events, weather, flight load (for airport hotels), holidays
Group blocks, allotments, contracted-rate consumption
LIVE FEEDS
🛏️
PMS
🌐
OTAs
📅
Events
✈️
Flights
🌦️
Weather
🔍
Search
All signals → demand model
DEMAND SNAPSHOT · NEXT 14 NIGHTS
Sat
92%
Sun
74%
Mon
48%
Tue
55%
Wed
71%
Mon & Tue tracking 18 pp below forecast — rate action recommended.
Interpretation
Demand & competitive position
A demand model fits your seasonality, segment mix, and pickup curve. Comp-set positioning explains your gap to peers per stay date.
Demand elasticity per segment (corporate, leisure, group)
Pickup-curve forecast vs same-DOW prior periods
Comp-set positioning — rank & gap-to-median
Cancellation & no-show probability
Solution
Pricing engine with guardrails
A recommendation per room type, channel, date, and length-of-stay. Always inside the floor/ceiling and channel-parity rules you set.
Per-room-type rate ladders (BAR, mobile, member, corporate)
Channel-mix optimization — direct preferred when margin allows
Length-of-stay & min-stay restrictions on shoulder dates
Floor/ceiling guardrails & brand-standard parity rules
Explainable: every rate has a reason chain
RECOMMENDATION · MON APR 27
Deluxe King · BAR
€179
was €209
−€30
Why?
· Pickup -18 pp vs same-DOW forecast
· Comp-set median €189 (was €201 yesterday)
· Floor: €165 · Ceiling: €289 — within band
· LOS 2+ unrestricted, LOS 1 closed
PMS · Opera Cloud
✓ pushed
Channel · SiteMinder
✓ pushed
Brand site
✓ pushed
Past-guest offer
412 sent
Action
Push, offer, backfill
Approved rates flow to your PMS and channel manager in seconds. Soft-window dates trigger personalized offers; cancellations trigger waitlist backfill.
Two-way sync with Opera, Mews, Cloudbeds, Apaleo, RoomRaccoon, custom PMS
Channel manager: SiteMinder, RateGain, Cubilis, D-EDGE, custom
Personalized offers to past guests on low-occupancy dates
Cancellation → waitlist auto-offer within minutes
Auto-approve mode or always-human-in-the-loop — per rule
Verification
RevPAR uplift, audited
Every recommendation is compared against the no-action baseline. Each rate change carries a complete audit trail — signal, model, decision, push, outcome.
RevPAR, ADR, occupancy — vs forecast and STR comp set
Channel-mix margin tracking (direct vs OTA)
A/B testing of pricing strategies on parallel room types
Full audit trail for every rate move
LAST 30 NIGHTS
Occupancy
82.4% +4.6 pp
ADR
€212 +€9
RevPAR
€175 +11.3%
Direct share
38% +6 pp
Everything yield needs
In one platform. Plays nicely with the stack you already run.
Per-segment elasticity
Corporate, leisure, group, contracted — each modeled separately, each repriced separately.
Comp-set monitoring
Always-on rate shopping. Position your gap-to-median per room type, per stay date.
Floor/ceiling guardrails
Brand-standard parity rules. AI never breaks them.
LOS & restrictions
Min-stay, CTA/CTD, closed-to-arrival on shoulder dates — computed alongside the rate.
Past-guest offers
Soft windows trigger personalized offers via email/SMS/messenger to your CRM list.
Waitlist backfill
A cancellation triggers a waitlist offer within minutes — not at the next nightly batch.
Explainable decisions
Every rate move shows the signal chain. Audit-ready by default.
Group & allotment aware
Block consumption, washdown, and pickup are inputs — not afterthoughts.
Beyond rooms
Same engine for serviced apartments, clinics, classrooms, courts, equipment rentals.
Deploy your way
Resource Utilization runs wherever your data lives.
S
SaaS
Hosted, multi-tenant. Connect your PMS & channel manager and run.
P
On-Premise
For chains with strict data residency. Kubernetes-native, your KMS, your LLM.
H
Hybrid
Inventory on-prem, market data in cloud. Policy-as-code routing.
Beyond hotel rooms
The same SISAV pattern applies anywhere capacity is perishable.
Hotels & resorts
Per-room-type rate ladders, comp-set positioning, segment-aware pickup forecasts.
Serviced apartments & STR
Multi-listing pricing across Booking, Airbnb, Vrbo, direct — with min-stay logic.
Clinics & consultations
Slot utilization, no-show backfill, dynamic offers for low-occupancy windows.
Coworking & classrooms
Hot-desk, room, and cohort capacity priced by demand and lead-time.
Courts & venues
Tennis, padel, fitness, event spaces — peak/off-peak rates and member discounts.
Equipment rentals
Fleet utilization (cars, boats, gear) priced per location, day-of-week, weather.
Stop pricing once a day
Tell us about your inventory and stack — we’ll show you the RevPAR ceiling.
Or reach us at info@aglium.com · Telegram
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