With 46% of Australian online shoppers now using AI to research products, this Black Friday rewards the retailer with the cleanest, most machine-readable product feed. AI answer engines read structured data, not advertising, and a messy catalogue quietly fails to surface at the moment of highest intent.
The Take: Black Friday is not a traffic problem this year. It is a data problem. When shoppers ask an AI what to buy, the retailer with the cleanest product feed wins the recommendation and the one with a messy catalogue is never named at all.
The detail: New Commerce and PayPal research found 46% of Australian online shoppers now use AI tools to research products, 43% to compare options and 43% to hunt for the best price. The answer engine now sits between your shopper and your shelf, and it reads structured data, not billboards. If the machine cannot parse your catalogue, it recommends the competitor whose data it can.
What breaks: The weak point is consistency. University of Pennsylvania researchers found that simply changing the order in which product reviews were shown to an AI changed which product it recommended. The tool is confident and it is fickle. If your catalogue runs tens of thousands of messy, unreadable SKUs, those products quietly fail to surface at the exact moment buying intent is highest. You will not see the sale you lost, because it was never counted as a visit.
Australian online shoppers now using AI tools to research what to buy
On the ground: This is the rare part of AI search you can actually control. Feedonomics APAC director Tim Stratford points out that clean, machine-readable product data is directly manageable, and that feed consolidation has driven return-on-ad-spend gains as high as 95%. Australian retailers who fix the feed before November are buying visibility the rest cannot, at the one time of year when traffic is guaranteed and margins are already thin.
For Australian operators: Treat your product feed as Black Friday inventory, not back-office plumbing. Audit titles, attributes and descriptions for machine readability now, before the sales window opens. Fill the gaps in the structured data that AI models read to build recommendations. Test how the major assistants describe your top products today, then fix what they get wrong. The brand named in the answer wins the sale, and that brand is decided by data quality weeks before the shopper ever asks.