From a standing start to A$1M in turnover, in under 12 months.
An Australian online liquor challenger launched into a brutal, thin-margin category against entrenched national retailers. We treated price as data, conversion as a system, and spend as a portfolio, and turned a brand-new store into a million-dollar business inside its first year.
Win a price-led category with no brand, no history, and almost no room to be wrong.
Online liquor is one of the harshest corners of Australian retail. Margins are thin, shoppers are ruthless price-comparers, and a handful of national chains own the shelf and the search results.
Cheapest Liquor was brand-new. There was no purchase history to learn from, no audience to retarget, and no reservoir of organic demand to fall back on. The promise in the name, that this was the cheapest place to buy, also raised the bar: every dollar of media had to convert against competitors who could absorb a loss on a hero SKU just to win the click.
Two problems compounded each other. First, the catalogue ran to thousands of SKUs, and spreading a small budget evenly across all of them meant being competitive on none. Second, the store's conversion rate sat at roughly 0.3%, so even the traffic that did arrive mostly left without buying. Paid media alone could not fix that. Pouring spend into a leaky store would only have manufactured expensive proof that the category was unwinnable.
Treat price as data, conversion as a system, and spend as a portfolio.
We did not start with the ad account. We started by building a clear, quantified picture of where this store could actually win, then pointed media at exactly those pockets and rebuilt the store to convert the traffic it sent. Three disciplines, run in sequence.
We collected data wide and then segmented it. Every SKU was scored on margin, demand and how the store's price compared against the market, so the thousands of products resolved into a ranked map of where the brand was genuinely competitive. That analysis told us to stop spreading budget thin and instead concentrate spend into roughly the top 1,000 products, the ones where price advantage, demand and margin lined up. The long tail stayed live but stopped consuming media it could never pay back.
In a category where the buying decision is mostly price, knowing the competitive position of each product is the whole game. We built continuous competitor-pricing intelligence so the priority list reflected real market position rather than a guess, and so media leaned into the products where the store's price genuinely beat the alternative. Spend followed evidence of advantage, not hope.
A 0.3% conversion rate is a structural problem, not a traffic problem. We rebuilt the path to purchase: tightening the user experience, removing friction and abandonment triggers in the checkout, and answering the objections that stop a first-time buyer from trusting an unknown store with a card. Only once the store could hold a sale did we scale hyper-performance product campaigns on the concentrated SKU set. Better conversion compounds with media: the same clicks now produced many more orders, which made the unit economics fundable and let spend scale without scaling waste.
A new store became a million-dollar business in its first year.
Concentrating spend on a quantified set of winnable products, with conversion fixed underneath it, produced a step change rather than an incremental lift. The store crossed A$1M in turnover in under 12 months from a standing start, and the work was recognised with an APAC award for the campaign.
The pattern is what makes this repeatable. The growth was not bought by simply spending more into a category that punishes weak conversion. It came from deciding where to compete using data, making the store worth sending traffic to, and then scaling media only behind products and a checkout that could carry it. Revenue scaled because the unit economics held, not in spite of them.
A new market entrant taken from A$0 to A$1M turnover in under 12 months, with conversion rate rebuilt from 0.3% to 3.16% so traffic could monetise, then spend concentrated into proven SKUs to scale on thin margins. Turnover reached A$1.85M within 16 months.
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