REGIONAL CASE · TOURISM & RENTAL

Building a repeatable booking engine in the rental car market

CLIENT
YES Rentals NZ
SERVICES
Search & performance marketing
Full-funnel media planning
Retargeting & multi-market account structure
INDUSTRIES
Tourism & vehicle rental
SECTOR
Travel

New Zealand's passenger vehicle rental market is worth an estimated NZD 2.3B a year (IBISWorld, 2026), and most of that demand is seasonal, tied to tourism peaks and people who decide to rent a car days, sometimes hours, before they need one. YES Rentals needed a system that could catch that demand reliably, not just during peak season but as a steady, repeatable source of bookings across both Australia and New Zealand.

The category is search heavy. Someone planning a self-drive trip or a business visit searches with intent long before they land on a specific rental company, which makes the keyword layer of the campaign as important as the creative.

The strategy

We built the campaign around high-intent search terms tied to travel, self-drive trips and business visits, so YES Rentals showed up at the exact moment someone was deciding whether and where to book. Meta ran as a full-funnel layer underneath that, covering everything from first awareness to the final booking decision, rather than treating paid social as a brand-awareness add-on to search.

The execution

A retargeting structure brought back users who had shown intent but hadn't booked, closing the loop on people who needed a second or third touch before converting. Australia and New Zealand were run as separate account structures rather than one combined campaign, because demand patterns, seasonality and competition differ enough between the two markets that a shared structure would have diluted performance in both.

The results

The full-funnel structure gave YES Rentals a scalable booking engine across both markets, built on high-intent search rather than one-off seasonal pushes, with the separate AU and NZ account structures allowing each market to be optimized on its own terms instead of averaging performance across two very different demand curves.

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