Australian retailers warned on AI search as duplication soars

A national analysis of over 800 Australian online retailers has revealed that 85 percent of product pages do not meet baseline standards for search performance, resulting in significant challenges as AI-driven systems become central to product discovery.

AI search influence

With platforms such as Google, ChatGPT and Perplexity increasingly shaping online retail journeys, the quality of product information has become a key determinant of visibility. The review found that there are widespread issues with product titles, incomplete or inconsistent attributes, repetitive use of descriptions, and an erratic brand voice across many retailers' web pages.

Duplication concerns

The analysis discovered that 49 percent of product descriptions were duplicated verbatim across rival sites. Industry benchmarks indicate up to 10 percent duplication is typically tolerated due to generic terminology, but the study found nearly five times that rate across Australian retailer catalogues.

"Search engines and AI systems can only work with the information they receive. When almost half of a retailer's catalogue is duplicated across competitors, the algorithms cannot determine which version is authoritative. That leads to lost visibility and missed opportunities, even when retailers have strong brands or high-quality ranges," said JP Tucker, Co-founder and Retail Data Specialist, Optidan.

Resource limitations

The survey highlighted a growing workload problem, with most retail teams lacking the capacity, search engine optimisation expertise and industry-specific content writing skills needed to manage and enhance large product catalogues. The reliance on supplier-provided content and basic copy-paste tactics results in fragmented branding, inconsistent terminology, and missing or incorrect product features, hindering AI agents from effectively matching products to customer needs.

"Teams are trying to optimise thousands of products with workflows designed for a different era. The scale alone makes it impossible to maintain accuracy or consistency. Most retailers simply do not have the time, or the depth of SEO and category expertise, to manually rewrite content at the pace AI search now requires," said Tucker.

PIM system challenges

Product Information Management systems, designed to streamline and centralise supplier data, have also contributed to the duplication problem. These systems often distribute identical content across multiple retail sites, making it more difficult for search algorithms to identify and reward unique or highly structured content.

The report noted that the shift towards AI search elevates the importance of on-site product content optimisation, as algorithms now prioritise uniqueness, consistency, and proper structuring-qualities not always supported by supplier-sourced data alone.

Responsibility debate

There remains an ongoing dispute between retailers and suppliers over who is responsible for optimising product data. Tucker, drawing on his background in fast-moving consumer goods and national account management, described persistent ambiguity about content ownership.

"In my days working with large suppliers, head office teams would insist it was the supplier's responsibility to deliver rich content. On the supplier side, brand managers argued it was the retailer's website, so optimisation was their responsibility. Both sides were pointing at each other, and the problem never moved," said Tucker.

The evolving landscape of AI-driven shopping, however, is changing this dynamic.

"The truth is that retailers have the greatest opportunity here. They have the most to gain from accurate, structured, unique product data, because it directly lifts category performance. Category growth beats brand growth every time. When retailers take ownership of their product data, the entire ecosystem benefits," said Tucker.

Operational pressures

The move to AI discovery adds urgency to the need for retailers to overhaul manual editing processes, streamline approval cycles, and upgrade fragmented tools. Inefficient systems cost both time and competitiveness, especially as AI increasingly favours well-maintained and unique digital catalogues.

"When retailers eliminate unnecessary steps, reduce manual rework and build more efficient data processes, the impact is immediate. We've seen up to 99 percent time savings across thousands of product pages when organisations modernise their workflows. That operational speed is becoming a strategic advantage, not just a back-end improvement," said Tucker.

AI readiness

The study asserts that online retailers who invest in structured, unique and accurate data will be best placed to attract visibility in new AI-powered shopping environments. Developing consistent brand voice, enriching product details, and reducing duplication are now described as essential for modern retail catalogues.