Nala Veli was already visible. The problem was what happened after guests found it: low rates, high cancellations and too much dependence on discount-led distribution.
We rebuilt the rate structure, distribution strategy, website and photography. In the same 90-day Booking.com period one year later, booked revenue rose — even though fewer room nights were sold.
Booking.com extranet · Same 90-day period, year over year · Nala Veli Beach & Spa
Visibility was not the main problem. The commercial weakness appeared after the guest discovered the property.
Top three on the island — better than 97% of it. Two point three million people saw the listing.
Just 0.37% of page views became a booking, against an OTA benchmark near 1%.
More than half of the bookings that did arrive were cancelled before check-in.
The nightly rate sat under a market averaging $100 to $110, and long-lead demand was mispriced.
| Stage | Count | Rate |
|---|---|---|
| Search views | 2,384,965 | — |
| Property page views | 17,792 | 0.75% of search views |
| Bookings | 65 | 0.37% of page views |
| Survived to check-in | ~31 | 52.9% cancelled |
Between September 2025 and early 2026 we rebuilt four parts of how Nala Veli reaches a guest. They happened together — no single one can be credited with the whole result.
Season bands rebuilt around real demand. Long-lead bookings priced to carry their own cancellation risk. The cancellation-policy mix rebalanced so flexible, non-refundable and length-of-stay rules work together instead of one blanket policy.
Rate parity set deliberately: the direct website rate protected as the best available, OTA rates below it, and wholesale-agent rates structured so long-term B2B partners stay profitable without undercutting the property's own channel. Inventory shared across channels in proportion, so nothing leaks — and rate plans checked against real source markets: Italy first, then Germany, Russia, UK, Spain.
A bilingual property site — English and Italian, matching the real guest mix — structured so Google and AI assistants can read, verify and quote it. Direct enquiry in one tap.
The property reshot by Miruppe and Accko, on the island: rooms, beach, spa, dining, drone. Shot to Booking.com's preferred 4000×3000 specification.
Long-lead bookings carried the highest rates and cancelled the most — the property was pricing for demand that rarely arrived. The rebuilt structure prices that risk in.
| Lead time | Cancellation rate | Average daily rate |
|---|---|---|
| 0–1 days | 29.3% | $63.99 |
| 2–7 days | 41.0% | $78.00 |
| 8–30 days | 58.0% | $104.00 |
| 31–90 days | 71.0% | $128.00 |
| 90+ days | 83.0% | $145.10 |
Owner-shot phone photos gave way to a full property shoot by Miruppe and Accko — on the island — at Booking.com's preferred 4000×3000 specification, sequenced in listing order.
Same property. Same 90-day window. One year apart. The platform's own figures.
Cancellations fell 27 percentage points — from two-thirds of bookings vanishing before check-in to under half.
| Metric | Change |
|---|---|
| Booked revenue | +17.7% |
| Implied ADRderived: booked revenue ÷ room nights | +40.5% |
| Revenue per booking | +32.1% |
| Booking window88 → 116 days | +32.4% |
| Cancellation rate67.7% → 40.7% | −27 percentage points |
| Room nightstraded down deliberately — see the trade-off | −16.2% |
Booking.com extranet · Same 90-day period, year over year · Nala Veli Beach & Spa
Booking.com Analytics · 44-property comparison set · Nala Veli Beach & Spa · 11 Jul 2026
Separate from the Booking.com comparison: a single direct advertising campaign returned more than four times what it cost — in bookings that came straight to the property, with no OTA in the middle.
Direct advertising campaign · bookings confirmed direct · figures the property's own
The property now sells fewer room nights than it did — that is real, and it was the point. We traded churn-prone, discounted volume for fewer, higher-value, stickier stays. Revenue quality matters more than occupancy alone.
We analyse your rates, cancellations, promotions, booking windows and market position before recommending what should change. You get the findings in plain language with the evidence attached — and you decide what to do with them. We recommend; you approve.