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AI Search for the Fashion and Tech reseller industry – How to stay visible
This whitepaper explores the recent changes to SERPs and what this means for the fashion and tech reseller industry today. We cover the advancements of AI search, LLMs, and generative features, analysing how they play a hugely influential role in visibility for e-commerce brands. Using real-world examples from established brands, we explore how resellers appear in AI and what this means for attracting customers. We also take you through some best practices to help you stay ahead of the competition online.
Abstract
Even a year ago, the typical customer journey looked drastically different from how it looks today. Now, the customer journey is more fragmented, and before readers make a purchase, they may use sources such as social media, forums, AI overviews, or AI mode to research and find their product.
If you are a fashion or tech reseller, it is important to understand how to be visible in today’s search landscape, so you don’t fall behind brands that are already on top of this. Let’s look at how you can stay visible to buyers today, and how the recent changes in SERPs may impact tech and fashion resellers.
How have SERPs changed, and how does this impact e–commerce brands?
During the past year, there have been some hugely volatile changes for SERPs, as well as many new features being introduced. Let’s start with AI overviews; in 2025, Google’s AI Overviews (AIOs) continued to spread across SERPs all over the internet, with the feature reaching 2 billion monthly users. Additionally, OpenAI also introduced ChatGPT Shopping to provide users with a deeper comparison experience. Google AI Mode rolled out across the world to compete with ChatGPT’s growing influence, allowing users to complete detailed searches and offering deeper answers, reasoning and more personalised responses than AI overviews.
LMM (large language model) platforms allow users to ask complex, natural-language questions. In return, coherent, summarised answers are generated, rather than just a clear list of blue links. For instance, as shown below, when a user searches for “vinted jacket reseller UK”, they are not only faced with a list of relevant website links, but they also come across an AI overview, summarising the top second-hand fashion resellers for jackets, and providing an overview of what to expect from each.
The progression of LLMs
LLMs like ChatGPT, AI Mode, Perplexity and Copilot have played a huge role in how the search landscape has changed over the past year. Back in September 2025, ChatGPT released single-cart checkout for US Etsy shoppers; and in January 2026, it was announced that Shopify merchants can opt-in to sell directly on all major LLMs, including AI Mode, ChatGPT, and Microsoft Copilot, in addition to the Gemini app (with ChatGPT interestingly being the only one to add a 4% on sales – yet).
Once opted in, this allows users to make purchases directly in the conversational interface without redirecting. This feature drastically transforms the user experience and removes intermediate steps from the traditional buying journey. Unlike traditional search engines that link to relevant results pages, LLMs can present product carousels enriched with images, prices, real customer reviews, and direct purchase links.
In the UK, ChatGPT’s shopping capabilities have also advanced to a sophisticated personal assistant model that simplifies complex consumer queries and purchase decisions. Launched globally in November 2025, the Shopping Research feature allows users to describe specific needs, such as “the best child-friendly Nintendo Switch games for a long car journey”. Users then receive a tailored buyer’s guide featuring UGC content such as recent reviews, useful comparisons, and a clear summary.
The launch of in-platform shopping on Gemini in the US
Launched in the US in January 2026, the in-platform shopping on Gemini helps retailers connect with high-intent shoppers and drive sales. As part of Gemini Enterprise for CX, shopping agents can understand user preferences, compare products, and potentially facilitate transactions directly on the platform. Targeting specific, long-tail queries, this tool ultimately makes the process faster for high-intent shoppers.
“Long-tail conversational keywords are particularly important to consider for in-platform shopping. In-market shoppers are likely to be looking for something specific. In this fast-moving AI world, it’s best to be prepared and stay ahead!” – Lizzie Lewington, Head of SEO Performance at Connective3
Google’s new “try it on” feature
Users can now see how they look in an item of clothing without even having to leave the house with Google’s new “try it on” feature. When using this feature, users can upload just a single picture of themselves and see how something looks on them, removing the guesswork of online shopping. While initially available for tops, bottoms, or dresses, this AI visualisation system now handles footwear in addition to clothing, generating realistic images within seconds.
The tool seems to have been perceived by many as a place to have fun and “try on” clothes previously worn by pop culture icons (for instance, this user tried on some famous outfits Elvis once wore). Other reviews question how realistic it is, and certain outfits do not work well with the tool. However, it will be interesting to see how it develops, and whether it can, in fact, come close to replacing trying clothes on in-person.
Why does the changing of SERPs matter for fashion and tech resellers?
Fashion and tech resellers should stay aware of changing SERPs, because purchase decisions now often involve comparison, looking into detailed specifications and analysing reviews. Today, modern user journeys have evolved into deeper research loops, often involving numerous platforms. For example, a consumer might discover a vintage dress on Instagram, but instead of immediately visiting a brand’s website or clicking a direct link, they use an LLM to aggregate reviews and compare price points across various UK resellers.
AI search is already changing how consumers discover fashion products, compare options and decide what to buy. E-commerce brands that take this seriously now will strengthen visibility, improve engagement and stay ahead of the game, rather than risk being overshadowed by those who are already adapting.
Staying visible in today’s search landscape
So, with so many changes to SERPs, how can you stay visible? Starting with the basics, adopting a clear structure across product landing pages is vital for getting featured in LLMs. This means implementing descriptive headings, short paragraphs, including clear answers early in the content, and bullet points that help LLMs to understand your content contextually.
The progressively complex shopping environment gives marketers a perfect opportunity to build consumer confidence. It’s important not to forget about Google’s E-E-A-T framework — experience, expertise, authoritativeness, and trustworthiness when it comes to GEO. Google’s AI systems assess credibility when choosing which sources to cite, and clearly signposted EEAT signals are therefore extremely important in staying visible today. Transparency and trust are crucial; ensure the price is displayed, include trust signals, like return policies, warranties, certifications, and brand credentials. Encourage detailed customer reviews by asking mandatory questions when someone is leaving a review. Reviews that explain what they liked about the seller, how a product was used, and discuss product features provide the context LLMs need.
Lastly, AI models prioritise fresh, accurate data. Brands that inject real-time inventory changes back into their public-facing metadata, so users don’t see recommended sold-out items, are perceived as being more trustworthy, increasing their “trust score” in the LLM’s logic.
“AI search platforms consider many, many signals to ensure they’re delivering a reliable and credible response to a user’s in-platform prompt. So, ensuring your site is considered trustworthy, your content is engaging, and you’ve built topical authority is essential if you want to appear within results.” – Alex Nayler, Head of Content Strategy at Connective3
You can find out more about building your visibility in our future of search whitepaper.
Examples from top fashion and tech resellers
– Vinted
Cited sources
Vinted offers optimised product landing pages, up-to-date shopping listings, and excellent detail on product pages. For example, the following listing of some Dr Marten boots provides information on product price, condition, size, shipping cost, colour, and includes a selection of clear images, providing transparency and a quick, easy way to scan a listing.
The “item verification available” addition also provides trust in the seller and the authenticity of the item, whereas the option of buyer protection provides extra peace of mind.
Vinted maintains high visibility in AI results largely because of its high “Listing Velocity.” AI models prioritise “fresh” data over static pages. Vinted power sellers maintain visibility by relisting items every 7–10 days and adding 1–3 items daily. This signals “activity” to both the internal recommender and external AI crawlers.
Vinted performs exceptionally well across AI Overviews and AI Mode for citations. The retail reseller appears consistently across AI-led search results that span the full user journey, from early exploration through to practical action. This spread indicates that AI systems reference Vinted not only when users are deciding whether the platform is right for them, but also when they are actively using it to buy or sell. Because Vinted provides clear, persistent guidance around selling, pricing, postage and platform rules, large language models can reliably surface it across both research and decision-led queries.
Topics featured in AI Overviews
Explore our future of search whitepaper for more advice on getting featured in AI overviews.
– Vestiaire Collective
Cited sources
Vestiaire Collective dominates “high-trust” AI queries for luxury goods, such as Louis Vuitton items, by using its Item Verification status. AI search models in 2026 are trained to filter for “authenticated” products to reduce misinformation risks. Their integration of Digital Product Passports (DPPs) provides a machine-readable “truth” that LLMs use to verify authenticity, pricing, and sustainability claims.
Vestiaire Collective appears across a broad spread of AI-led topics that extend further down the user journey, reflecting both exploratory and decision-led behaviour. The topics featured in AI Mode include high-intent brand and product searches such as “Louis Vuitton sale”, “Valentino bag”, “Chanel bag” and “Louis Vuitton bags”, alongside more evaluative resale-led terms including “vintage clothing”, “thrift”, “go thrift” and “vintage Burberry bag”. This range suggests that AI systems reference Vestiaire not only when users are researching luxury resale more generally, but also when they are assessing specific items, brands or categories.
Topics featured in ChatGPT
– BrandAlley
Cited sources
BrandAlley appears in AI-led search results largely through brand- and sale-led topics that sit at the discovery and early consideration stages of the user journey. The topics featured in AI Mode include high-volume brand queries such as “BrandAlley”, alongside retailer and discount-focused searches like “Paul Smith sale”, “BrandAlley reviews” and “BrandAlley discount code”. Visibility also extends to individual designer and high-street brand sale topics, including “Reiss outlet”, “Sweaty Betty sale”, “Ray-Ban sale” and “Radley”, where AI systems surface BrandAlley as a destination for reduced-price branded stock. These topics reflect how BrandAlley supports exploratory and value-led research, helping users understand where sales and offers are available, rather than guiding detailed product comparison or final decision-making.
Further down the funnel, visibility becomes more limited because BrandAlley does not provide the persistent, product-level detail that supports comparison or justification at the point of decision. Inventory changes frequently, pricing is often time-bound or member-gated, and listings are not structured for cross-retailer comparison, which makes it harder for large language models to reference BrandAlley when responding to more evaluative, purchase-led queries.
Topics featured in AI mode
– CeX
Cited sources
CeX excels in AI Mode by being radically transparent with pricing and condition-based valuations. AI models favour sites that clearly list all variables (Buy, Sell, Exchange prices) because they allow the LLM to complete “comparison reasoning” for the user. CeX also highlights their 5-year warranty in product snippets, again sending out useful trust signals.
Impressively, CeX does very well for non-branded, high-intent search terms in LLMs, such as “sell my phone”, “second hand phones”, and “sell my iPhone”. CeX’s performance demonstrates that LLMs consistently prioritise retailers that reduce ambiguity for the user by clearly surfacing pricing logic, condition tiers, and guarantees. This enables AI models to confidently recommend or compare options without needing follow-up clarification.
Topics featured in AI mode
– Scan.co.uk
Cited sources
Topics featured in AI mode
Scan remains a top source by using a hyper-specific Product Schema that includes technical specifications (clock speeds, TDP, compatibility). This structured data allows AI assistants to answer complex, technical “reasoning” questions that many standard retail sites cannot fulfil.
Scan also sends out various trust signals, including links from the website to Trustpilot reviews, and their 24-hour replacement policy. This information is useful for ensuring they are featured in product comparisons, as well as tech reseller comparisons and summaries.
– Overclockers UK
Cited sources
Overclockers perform particularly well for “best for” queries, as we can see below in their topics featured in ChatGPT. The brand appears in AI-led search results primarily for technical and comparison-led topics that sit further down the user journey, where users are evaluating hardware options and narrowing their choices.
Topics featured in AI mode
Overclockers captures “Shopping Research” traffic in ChatGPT by focusing on specific “Intent Clusters”. Their use of detailed “buyer guides” and forums allows AI to cite them for specific recommendations like “best gaming PC for flight simulators”.
Stay visible and attract customers to your brand
The search landscape today is an exciting time, as it is the perfect opportunity for e-commerce brands to get ahead of the competition and use best practices to ensure visibility across all platforms. As we’ve explored, brands are visible across AI at various stages of customer journeys. Understanding how to stay ahead of the competition by utilising best practices is vital to attracting customers to your brand. Our ‘SEO Everywhere’ approach involves creating an aligned, optimised multi-channel approach to your digital marketing strategy, helping you stay ahead in the competitive fashion and tech reseller industry.
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