Welcome to AIVisCity Weekly — a free weekly briefing helping small business owners understand how AI search is changing customer discovery, and what practical steps they can take next.
In this week’s issue:
What’s Happening in AI Search — Google gives web links more prominence, while Cloudflare and OpenAI report progress in discovering useful pages.
Weekly Insight — what OpenAI’s shopping demo suggests about customers who discover what they want through conversation.
Try This Yourself — imagine whether your catalogue could support a complete shopping conversation across several products.
Worth Reading — discount information in AI shopping and a grocery journey that begins with a meal idea.
AIVisCity Answers — what competitors’ AI citations can teach you about your own website.
📰 What’s Happening in AI Search
Google is making links easier to find in AI answers
Google’s 15 October update describes more inline links, placed higher and more frequently in AI responses. It is also testing a prominent section linking to official websites where people can complete a specific task, with explanations of why those sites are useful. For a small business, the opportunity extends beyond having your name mentioned: customers need a relevant page to visit and a clear way to continue. When you check an AI answer about your business, inspect where its links lead and whether that page helps with the customer’s request.
Source: Google
ChatGPT is finding more pages through a discovery pilot
Cloudflare and OpenAI’s 15 October update reports that their research pilot has helped bring previously unknown pages into OpenAI’s search index. The announcement highlights specific, useful information, including local menus, opening hours and product guides. For small businesses, keeping those pages accessible and current remains worthwhile. Site owners’ access choices still apply, so review crawler settings if you want your information available to AI search.
Source: Cloudflare and OpenAI
🔮 Weekly Insight: When Shopping Becomes a Conversation
Shopping online often assumes that customers can explain what they want before they begin. They choose a category, enter a search term and narrow the results using filters. Yet someone furnishing a room may know the feeling they want long before they can name the products that would create it.
OpenAI’s new shopping-agent demonstration, set inside fictional homeware retailer Vesper & Alder, explores that uncertainty. A shopper uses conversation and a room photo to find furniture, refine the selection and arrange delivery. The shopping brief develops during the exchange, suggesting four changes in how customers could search and buy.
1. The search begins with a situation
The shopper wants a warmer corner of the room and a place to read. A photograph supplies context that would be difficult to express through a few keywords, and the agent suggests a chair, table and lamp. The customer can begin with an incomplete idea and see a possible interpretation.
We expect more searches to begin with descriptions of everyday situations. People may use voice, photographs and loosely expressed preferences, allowing the conversation to reveal which product categories belong in the search.
2. The brief develops after the first suggestion
After seeing the suggested arrangement, the shopper asks to keep it under $250. The agent changes the chair, brings the original set within that amount before tax and updates the preview. The budget enters the conversation after the first recommendation has made the possibilities clearer.
That could make searching feel more like working something out with a helpful shop assistant. Customers can respond to a suggestion, change one requirement and expect the next answer to retain the rest of the context.
3. Customers judge the combination
The visual preview shows how the proposed furniture could look together in the room. The shopper can judge the effect of the combination while the conversation continues. It gives them something to react to before committing: a customer might recognise that the arrangement feels crowded, or that a different colour would suit the room. A complementary throw appears later as an optional addition.
We think this could shift more attention towards the outcome of a purchase: how a corner will feel, how an outfit will look, or what a meal will become. Comparing individual products would remain part of shopping, alongside a growing expectation of seeing how the choices fit together.
4. The conversation continues after checkout
After checkout, the shopper realises they selected collection and asks to switch to home delivery. The agent checks the address and obtains confirmation before updating the order. A change that might normally involve finding an order page or contacting support becomes another turn in the conversation.
As this experience becomes familiar, we expect customers to want continuity across browsing, buying and aftercare. The same interaction could carry their intentions forward, with clear confirmation when a conversation leads to an actual change.
For small retailers, the sensible response for now is to continue good AI Visibility practice and keep a close eye on these developments. Clear, accurate business and product information remains useful as discovery changes. As suitable capabilities become available through the platforms you use, you can judge when they offer something worthwhile for your customers.
💻 Try This Yourself
Imagine an agent became available on your ecommerce platform. Picture a customer describing a complete need your shop could help with, such as preparing a dinner party or furnishing a home office. As the conversation develops, they add a budget, change a preference and ask how several products would work together.
Could the agent use your existing listings to suggest a suitable combination, explain its choices and adjust the selection while keeping the overall need in mind? Think through the experience to checkout and delivery. Where would your catalogue and policies provide clear answers, and where would the conversation run short of information?
📕 Worth Reading
If you’re curious to look deeper into how AI search is changing the internet, these articles are worth a look.
Discount context needs to reach shopping assistants. Shopify’s 9 October changelog explains that its catalogue now shares compare-at prices with AI shopping agents, alongside current prices. If you use Shopify, review the sharing control it describes so your intended discount information can accompany products beyond your storefront. Read Shopify’s update.
A meal idea can become a shopping basket. OpenAI’s 1 October Safeway case study describes shoppers starting with a recipe, photo or request, finding relevant groceries through ChatGPT and continuing to Safeway for checkout. It offers a concrete example of the changing discovery experience discussed above. Read OpenAI’s case study.
✅ AIVisCity Answers
Q: What can I learn from the websites an AI assistant cites when it recommends my competitors?
A: You can learn which service details and supporting evidence appear alongside a competitor’s recommendation. Read the cited pages against the customer’s question, then compare them with your own information. This can reveal genuine gaps worth fixing, such as unclear availability, service areas or proof of experience.
Want a more detailed explanation? Check out here.
👋 Until Next Week
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See you in the next issue of AIVisCity Weekly
