Pattern launches tools to boost brands' AI visibility

Pattern has launched two tools in Australia designed to help brands assess how visible they are within generative AI services used for product discovery and research. It is positioning the release as an end-to-end framework for "generative engine optimisation", reflecting a shift from search-based discovery to conversational interfaces.

The offering combines an LLM Access Audit with a Generative Engine Optimisation (GEO) Scorecard. Together, they aim to help retailers and brands confirm whether AI systems can access their online content and assess how those systems present their products when consumers ask for recommendations or comparisons.

The launch comes as consumer use of AI tools for shopping-related queries rises. A Capgemini survey cited by Pattern found 58% of consumers now use AI to discover and research products, up from 25% in 2023. The shift is raising new questions for marketing and eCommerce teams about what content AI models see, how they interpret it, and whether the information shown to shoppers is accurate.

Merline McGregor, Managing Director at Pattern Australia, said the changing pattern of discovery has implications for how brands manage digital content and visibility.

"AI is fundamentally changing how consumers discover brands online," McGregor said. "For the first time, brand visibility is being shaped by conversational engines rather than search algorithms. Our new GEO framework gives Australian retailers a way to understand, measure and optimise their presence in this new AI-driven landscape."

Access and crawl

The LLM Access Audit focuses on whether AI bots can reach and interpret a brand's online footprint. It checks discoverability across major AI platforms and identifies which services are actively crawling a company's website for information that may appear in conversational results.

In practical terms, the audit aims to surface technical or structural barriers that may prevent AI services from seeing product pages, brand information, or supporting content. Brands have long managed site visibility for traditional search engines, but generative AI introduces different behaviours and routes to discovery, including chat interfaces and summarised answers that may not lead users through a conventional list of links.

Scorecard approach

The second tool, the GEO Scorecard, is positioned as a free assessment of how AI platforms such as ChatGPT showcase products and brands. Pattern said it provides recommendations for improving performance against competitors.

Pattern said the scorecard draws on its proprietary technology, AI and data spanning more than 46 trillion commerce data points. Those inputs are used to report how large language models perceive, rank and describe a business, according to the company.

The output includes a score intended to reflect a brand's current presence in AI-driven commerce, a competitive benchmark against named rivals, and a prioritised set of recommended changes. Recommendations may cover content, sentiment and ranking within chat-based AI experiences.

For marketers, the emphasis on sentiment and description introduces new risks alongside opportunity. Product detail pages, customer reviews, third-party articles and marketplace listings can all shape how an AI model summarises an offering. That summary can influence a consumer's next step-whether they click through to a retailer, seek a competitor, or stop searching.

McGregor said the tools address a lack of visibility into how brands appear in generative AI services.

"Many brands don't yet realise how their content appears (or doesn't appear) inside generative AI tools today," she said. "Our new LLM Access Audit and GEO Scorecard tools make that critical information visible for the first time. It gives marketers a clear roadmap to ensure their products are accurately represented and easily discoverable through AI-powered search."

Market context

Generative AI has moved quickly from experimentation into everyday consumer use through widely available chat services and embedded assistants. As a result, brands are reassessing how product information is structured and distributed across the web-and how it might be reused in responses that are not controlled by the brand or the retailer.

Pattern's approach reflects a broader effort by eCommerce advisers and agencies to build measurement frameworks around AI-driven discovery. Search engine optimisation has long provided tools for keyword research, crawling diagnostics and rank tracking. Generative systems require different tests, including whether an AI service can access a site, what it chooses to cite, and how it frames a brand relative to alternatives.

Company footprint

Pattern operates as an eCommerce and marketplace services provider. It describes itself as the number one reseller on Amazon globally and says it sells more than USD $3 billion of product each year into 60 countries. It also says it acts as an authorised Amazon seller for more than 200 brands, buying stock and managing their marketplace presence.

The business has operations in Australia across Melbourne, Sydney and the Gold Coast, as part of a wider global footprint it says spans 24 locations and more than 2,000 employees.

The LLM Access Audit and GEO Scorecard are now available to Australian brands and retailers looking to assess how AI platforms surface their products and brand information.