Honest proof, not curated quotes
Live aggregates from the product, composite scenarios per vertical, and a recoverable-margin estimate you can run in 30 seconds. We'll add named customer stories as they go live — not before.
Pattern stories
How Luska shows up in each vertical
Composite scenarios drawn from how the product is actually used. Numbers are typical, not guaranteed. Click into any scenario to see it live in a sandbox.
A multi-category online retailer with a few hundred SKUs, monitoring 3–5 competitors per product across daily price moves.
+2.4%
Gross margin lift on monitored SKUs
Typical 30-day result after enabling the approval queue and psychological rounding.
Challenge
Manual spreadsheet checks meant pricing decisions lagged competitor moves by 24–48 hours, eroding margin on price-sensitive lines.
How Luska handles it
Luska watches the competitor median, surfaces only the SKUs where the gap exceeds the configured threshold, and queues a recommended price for human approval.
Price vs. competitor median
IllustrativeLuska features used
A 50-room independent hotel running three room types across direct booking and one OTA channel.
+9.1%
RevPAR uplift vs. baseline
Composite based on a 30-day window with autopilot in advisory mode.
Challenge
Static rate plans missed weekend lifts and event-driven demand surges, leaving 8–12% RevPAR on the table.
How Luska handles it
Luska forecasts demand 30 days out, layers in known demand drivers (events, holidays), and proposes per-night rates that the autopilot can apply within configured guardrails.
Baseline vs. optimized
IllustrativeLuska features used
An intercity coach operator running two routes with multiple daily departures and 60-day booking windows.
+6.7%
Yield per seat
Composite scenario across peak and shoulder departures, 30-day window.
Challenge
Flat fare ladders meant peak departures sold out cheap while shoulder slots ran half-empty.
How Luska handles it
Luska tracks load curves per departure, compares against historical pace, and recommends bid-price ladders that protect inventory for late-booking high-yield demand.
Baseline vs. optimized
IllustrativeLuska features used
A mid-size venue selling tiered tickets across early-bird, general, and door windows for repeat events.
+4.8%
Average ticket revenue
Composite scenario across 4 ticket tiers in advisory mode.
Challenge
Early-bird tiers over-discounted because operators feared slow sell-through, leaving cash on the table when demand spiked.
How Luska handles it
Luska watches sell-through pace against the demand forecast and recommends tier shifts before discounts compound.
Baseline vs. optimized
IllustrativeLuska features used
A B2B SaaS company with three plan tiers, monitoring direct competitors and willingness-to-pay signals.
+11%
Mid-tier ARPU on new accounts
Composite scenario over the first 90 days after a tier-pricing refresh.
Challenge
Annual price reviews missed shifts in competitor positioning and left mid-tier underpriced versus willingness-to-pay evidence.
How Luska handles it
Luska tracks competitor pricing-page changes, blends willingness-to-pay signals from analytics, and produces tier-by-tier recommendations a human still approves.
Price vs. competitor median
IllustrativeLuska features used
Estimate
What could this look like for you?
A conservative band based on typical Luska usage patterns. Estimate, not a guarantee.
Recoverable margin per month
Annualized typical
€8,820
Estimate, not a guarantee. Real recoverable margin depends on catalog mix, competitor density, and how aggressively you act on Luska's recommendations.
Customer voice
Words from real Luska customers
See it on your own catalog
14-day trial, no credit card. Or submit your existing results and we'll feature them here.