Your Customers Are Shopping In ChatGPT — Is Your Brand Ready For It?
The global AI market is projected to reach $757.6 billion USD in 2025 and expected to surpass $1.8 trillion USD by 2030. The e-commerce and retail sector accounts for a significant portion of this already – the global AI in e-commerce market size is estimated to reach approximately $8.65 billion to $9.12 billion USD by the end of 2025. By 2030, the market for AI-powered e-commerce solutions is expected to reach ~$16.9 billion, with AI projected to handle 80% of all customer interactions online, significantly impacting customer service efficiency.
AI has proven to be a significant revolutionary element of the digital era. Platforms like ChatGPT, Perplexity, Gemini, and Claude are functioning as personal assistants living in people’s pockets. Users are confidently relying on these AI models for day-to-day tasks such as (but not limited to) planning travel, completing work-related tasks like writing emails, preparing presentations, or analysing statistics, managing personal finances, engaging in creative projects like planning social media posts, and — most interestingly for us in e-commerce — shopping: generating product comparisons and finding deals online before purchasing.
AI Search is quickly becoming the go-to for product discovery and recommendations over influencers, ads from brands and traditional search.
AI as the Next Evolution of Brand & Product Discoverability
Consumers are now more empowered than ever when it comes to making informed purchase decisions and AI is playing a huge role in enabling that.
Brands like yours can no longer afford to be vague when it comes to online store content. You need to be as transparent as possible when educating customers about your brand promise, unique selling points, product descriptions, and specifications. Most importantly, you should showcase genuine customer reviews and user-generated content wherever possible.
Why? These AI models have access to information you may not even know exists in relation to your brand, your suppliers, your customers opinions — anything that exists on the WWW, from any source that mentions you, and it's going to use those sources to answer your customers search query as best it can.
If the information you provide on your online store isn't detailed enough, AI will go elsewhere for a more accurate answer. So unless you want to leave it up to chance — having customers learn information about your brand, your products and the way you operate from external sources that may not always be accurate — you need to take as much control over the results they're served as possible, and the only way to do that is by making sure your own website is the main source for information around any possible query your customers may have.
How AEO (Answer Engine Optimisation) differs from traditional SEO (Search Engine Optimisation).
In short, SEO is all about optimising your content so that your pages show up as high as possible in the list of search results provided by a search engine like Google in response to a user query. These results pages list one single page/source at a time. SEO favours popular keywords in content: the pages with the most relevant keywords that are also considered high quality sources will be listed semantically in search results featuring a sentence or two from each, giving the user options to go deeper in search for the answer to their query.
The goal for AI models is not to list pages that may have potential answers to a query, but rather answer the query in full itself, pulling from multiple relevant sources. Its job is to find and consolidate content from multiple web pages/sources to produce a unified answer to a search query, favouring contextual relevance as well as trusted, 'quality' sources when trawling the web for its references.
A user, if satisfied with that answer, doesn't even need to click through to the sources referenced. Descriptive, consolidated and 'to the point' copy is what will likely be used to make up an AI generated result.
Popular Generative AI tools being used by consumers in their shopping journey include ChatGPT, Perplexity and Gemini. What makes these models particularly powerful is their conversational interface, their ability to mimic human conversation, and how deeply contextual their responses are. ChatGPT, when trained for long enough will adopt your tone of voice, use common slang and colloquialisms of your generation and location, speak with personality and empathy, and even tailor responses to your prompts based on things it has learned about you and your situation in the past. For many, it has become the ultimate companion and side kick.
When it comes to the accessibility of AI, there’s no shortage of options. The majority of these platforms are web-based and accessed through a browser, while some of the larger models offer downloadable apps for quick mobile access. Others are being integrated into third-party platforms, and you can even see AI working its magic within Google’s search engine — these are called AI Overviews.
You've most likely experienced Googles AI Overviews already: where Google's Gemini pops into your search results pages with a curated answer to your query, positioned beneath Google Ad (Sponsored) listings, and above organic listings. These overviews are made available to you without you having to switch from normal Google search results to AI Mode.
AI Overviews are significantly disrupting the state of SEO. According to Semrush, 'Google’s rollout of AI Overviews is arguably the most disruptive change to the search landscape since the introduction of featured snippets.'
Not all search queries are triggering AI overviews in Google search results right now, but the numbers are rapidly increasing.
To understand this more deeply, take a look at the data from this Semrush AI Overviews Study: 'What 2025 SEO Data Tells Us About Google’s Search Shift' from earlier this year detailing what percentage of queries are triggering AI Overviews and what kinds of queries are more likely to trigger them.
Ecommerce Brands No Longer Have the Option to Ignore AI-Assisted Shopping
Google — the world’s highest-traffic website and most popular search engine — is evolving into both a Search Engine (serving traditional results that users can browse and select from) and an Answer Engine (an AI model that delivers a holistic overview drawn from multiple sources).
To stay ahead, you need to optimise your store content for both SEO and AEO — ensuring it’s discoverable by humans and understood by machines.
AI Overviews are reshaping how consumers search. When detailed enough, they often lead to zero-click behaviour — where users don’t visit any source pages because they’re already satisfied with the summary presented.
This largely depends on search intent: whether the query is informational (where users want quick, general answers and no further action is needed) or transactional and exploratory (where users are seeking guidance before taking the next step and plan to navigate through multiple sources to find what they need).
For us in e-commerce, we’re likely to see customers prompting navigational queries — searching for product recommendations that naturally lead to further exploration, ideally clicking through to shoppable pages and making a purchase.
However, it’s important to note that if a customer’s search intent doesn’t indicate readiness to make a purchase and instead reflects a desire for a quick answer to a question that isn’t directly product-related — zero-click behaviour may occur.
For example, a user might ask to compare the customer satisfaction rates of cosmeceutical skincare brands with dedicated customer service teams, or to compare the shipping costs and timeframes of two multi-brand retailers selling the same product. In these cases, if the AI Overview provides a satisfactory answer, the user may not take any further action.
It’s important to understand that it’s imperative to optimise your store content for all types of search queries. Going deep into your product specifications can help AI models prioritise your products in response to product-related searches — but ideally, you want your brand to be considered in every possible context where your ideal customers are looking for solutions.
Every piece of content across your store should demonstrate your ability to deliver. And this extends far beyond product education — think returns and exchange policies, shipping times across different regions, the responsiveness of your customer service team, customer satisfaction rates, your supply chain transparency, and how sustainable your operations truly are (especially if you claim to operate sustainably).
Today’s customers aren’t choosing brands based on great products alone; they’re auditing your entire operation before deciding which brand deserves their loyalty.
How to optimise your store for AI Answer Engines (AEO)
1. Be transparent and descriptive on every page
Your Collection Pages, Product Pages, About Page, and Policy Pages should all work together to paint a complete, trustworthy picture of your brand. AI systems scan these pages to understand what you offer, how you operate, and how reliable you are. Write content that answers the kinds of questions customers are actually asking. Think about search queries like:
- “Does this kid-friendly SPF actually hold up in salt water?”
- “Which women's compression tights are the best for circulation while running and aiding post-run recovery?”
- “Between X and Y, which product has the best, genuine reviews?”
- “How sustainable is X brand, really?”
Each of these queries can be answered naturally through your on-site content in product descriptions, comparison charts, or FAQ sections.
2. Write for Machines, but with a Human Touch
AI readers don’t see your beautiful visuals, elegant animations, or the emotional storytelling that captivate your human visitors. They don’t interpret mood or design hierarchy — they scan information. Storytelling has a place on your online store for the customers who are shopping there, of course — but it's not relevant to an AI reader, so customers shopping through AI won't experience it. Wordy, whimsical copy may woo your audience, but to AI, it offers little value unless it’s backed up with factual, descriptive data.
This is especially important on your product pages. It’s perfectly fine to pair evocative language with stunning imagery that sets the scene and stirs emotion. But remember: while your customers are enchanted by your beautifully merchandised product photography, AI is scanning for evidence — concrete details it can use to answer specific queries.
For example:If you sell a $500 dress with a premium silk outer, but fail to mention the materials used for the lining, both AI and your customers are left guessing. A potential buyer might ask:
“Is this dress worth the price? Is it 100% silk?”
If the only information available is a vague description like:
“The Petra Dress is the perfect summer event statement piece, draped in luxurious silk for an effortless, chic look, lined for coverage and comfort.”
AI has little to work with. Its response might look something like:
“The outer layer of this dress appears to be 100% silk, but there’s no information provided about the other materials used. It’s possible that a cheaper synthetic fabric was used for the lining.”
By being too vague, you’ve inadvertently told both the AI and your customer that something is missing. A competitor who clearly lists fabric compositions and care details instantly appears more transparent and therefore more trustworthy. Transparency doesn’t just improve your ranking with AI models; it reinforces credibility and earns lasting customer loyalty.
3. Write informative blog content
Create blog articles that position your brand as a trusted authority within your category. Focus on topics your ideal customers are curious about — care guides, ingredient or material breakdowns, product comparisons, sustainability practices, styling advice, or brand storytelling.
Not only does this build trust, but it also helps AI models recognise your site as a reliable source for detailed, factual information.
4. Include relevant FAQs
Integrate FAQ sections wherever it makes sense — on product pages, policy pages, or within blog articles. Phrase your questions in the natural language your customers use (the way they’d type them into search or an AI chat).
Use clear, concise answers written in full sentences. This format helps AI models easily extract accurate information, increasing your likelihood of being referenced in AI-generated responses.
5. Implement and maintain structured data
Ensure your store uses structured data (JSON-LD schema) correctly to describe products, reviews, FAQs, and articles. This helps AI engines understand context and relationships between different types of content on your site.
Keep your structured data clean, consistent, and accurate — especially across global or multi-brand setups.
6. Monitor external sources for consistency
AI models cross-reference multiple sources when forming answers. If external sites (press articles, retailer listings, affiliates, or review platforms) display information that conflicts with what’s on your own site, it can undermine your credibility.
Conflicting information signals unreliability, which may lead AI systems to exclude your content entirely. Where you can control it — keep your messaging, product specs, and pricing consistent across all public channels to reinforce trust.
7. Think beyond product education
AI looks at your entire ecosystem, not just your catalogue. Optimise content around logistics, sustainability, brand values, and customer experience — topics that often surface in AI-driven questions.
Include details about:
- Return and exchange policies
- Shipping timelines and regional delivery info
- Customer service responsiveness
- Ethical sourcing and supply chain transparency
By addressing these broader touch points, your store becomes more semantically rich and more likely to appear as part of comprehensive, trustworthy answers.
A bonus boost:
Register your Shopify Product Catalogue with OpenAI for an AI Shopping Appearance Boost
Shopify merchants are able to sell directly through ChatGPT conversations — no links or redirects, just seamless commerce. ChatGPT customers to tap “Buy,” confirm payment and shipping, and complete the purchase inside the chat.
To submit your catalogue, the process involves registering your brand as an OpenAI merchant and creating a formatted product catalog according to the Product Feed Spec and updating it regularly so OpenAI can ingest, validate, and index your product information for retrieval and ranking in ChatGPT. As a Shopify Merchant, you do not need to go through this application process manually – Shopify is working alongside OpenAI to streamline the process and ensure that when someone asks ChatGPT for recommendations, they access inventory from Shopify merchants for immediate purchase.
Note: This integration is live only in the US for selected US merchants and is being rolled out slowly, but the goal is to expand user and merchant geographies in 2026.
Register your interest as a Shopify Merchant and stay in the loop to be the first to know when this feature is available to your brand.
To close, AI models are already gathering information about your brand — your products, reputation, market position, and the way customers and your community perceive you. If your site doesn’t provide detailed, trustworthy information, AI will look elsewhere, sourcing content from external platforms that may not reflect your brand accurately.
You can’t control exactly what AI includes in its summaries, but you can influence it by being the most credible, structured and comprehensive source available. Optimise your Shopify store, structure your content, fill in the gaps, and make it seamless for AI to understand and represent your brand correctly.
I'm here to help you get ahead of the game — get my help to implement AEO on your Shopify store ahead of the Holiday Season with a Shopify Shorts Session.