Web Rate Engine
Scans nearby facilities every day and recommends a price per unit type, folding in occupancy, demand trend and tier logic.
Solutions / Dynamic pricing
Pricing that moves with the market
Bring self-storage rates back in-house. A daily competitor scan sets the optimal price, and scheduled increases grow revenue without pushing tenants out
Competitor scanECRI rate pathIn-house control
9:41
Rate engineprice optimization
daily scan
Self-storage · 70+ facilities · in production
94%
Rate set
$186/mo · 10×10 climate
Facility MSK-N · vs live market
Competitor scan
StorOne · 0.4 mi$179below
CityBox · 0.6 mi$198above
competitor scan
ECRI rate path
+5–10%revenue / year · illustrative
70+facilities, priced daily
100%pricing in-house, testable
What we do
From a black-box operator to pricing you own
A chain of 70+ facilities had its pricing outsourced to an external operator. It was opaque, uncontrollable and impossible to test against. We brought it back in-house as one rate engine
How it works
Three engines, one rate
Scan the market, grow existing tenants on a schedule, and keep a human in the loop: each rate explainable and yours to override
ECRI Engine
Raises existing-tenant rates on a schedule: first near day 120, again after around 270 days on a multifactor score, then recurring. Lift without move-outs.
Manual override & dashboard
Every recommendation is explainable and overridable on one dashboard. Pricing stays in-house, where you can test hypotheses.
Guardrails & limits
Set rate floors, ceilings and max-step limits per unit type: the engine only ever recommends inside the bounds you control.
The challenge
Pricing you don't control
Outsourced operator
Pricing handed to an outside operator: opaque, out of your control.
You can't see how your rates sit against the street.
Raising rates on sitting tenants risks move-outs.
No way to test a pricing idea before committing.
With Zentavor
Web Rate Engine recommends every rate in-house, explainable and yours to override.
Daily scan of nearby facilities prices each unit type against the market.
ECRI lifts existing-tenant rates on a multifactor schedule tuned to tenure, without triggering move-outs.
Pricing back in-house: A/B and adjust, no vendor black box.
FAQ
Your frequently asked questions
Where does the competitor data come from?
A daily scan of nearby facilities' published rates, by unit type, within a radius you set, so each recommendation is priced against the live local market, not a guess.
Won't raising rates push tenants out?
The ECRI engine raises existing-tenant rates on a multifactor schedule tuned to tenure and demand, so increases land where churn risk is low. Every increase is explainable and overridable.
Is pricing fully automated?
No, every recommendation is explainable and you can override it. The point is to bring pricing in-house, not hand it to another black box.
Do the figures in the demo reflect a real client?
The console runs on a real map with illustrative rates. It's grounded in a production self-storage engine (Web Rate Engine + ECRI) across 70+ facilities, but the specific prices shown are examples, not a client's numbers.
How does this fit beyond self-storage?
It's a custom ML pricing build. The same approach (market-aware recommendations, scheduled increases, human-in-the-loop) applies to any business setting prices against competitors and tenure.
Let's talk
Take pricing back in-house
Tell us your portfolio and how you price today. We'll scope a rate engine and a path to measurable lift