Black Friday and Cyber Monday (BFCM) are changing, and this year, ecommerce merchants have another channel to compete on. Alongside traditional search, social media, and paid advertising, retailers now need to consider whether AI shopping assistants can discover, understand, and recommend their products.

The AI agent push is happening, and it isn’t subtle. Major technology companies, including OpenAI, Google, Microsoft, Amazon, and Meta, are expanding their AI shopping capabilities. Depending on the platform, these assistants can help consumers research products, compare prices, monitor deals, and, in some cases, complete purchases with the shopper's authorization.

…And it’s working! Consumers are increasingly turning to tools like ChatGPT, Google Gemini, and Microsoft Copilot to research products, compare prices, and find the best deals. Instead of scrolling through dozens of product pages, shoppers can ask an AI assistant to narrow their options based on budget, preferences, and specific needs.

According to Adobe's 2026 holiday shopping forecast, AI-driven referral traffic to U.S. retail websites is expected to increase by 130% year over year during the November and December holiday season.

For merchants, this means ensuring your store is ready to be discovered, understood, and recommended by AI shopping agents, especially as we head toward the two biggest shopping periods of the year: BFCM and the holidays. 

In this blog, we’ll explain how agentic ecommerce is changing the shopping journey, which AI tools consumers use, and what ecommerce merchants can do to review and improve their visibility before the BFCM rush. 

What is Agentic Commerce?

Agentic commerce uses AI-powered systems to help consumers discover, evaluate, select, and potentially purchase products on their behalf.

Traditional ecommerce relies heavily on customers navigating websites themselves. They search for products, open multiple tabs, compare specifications, read reviews, and eventually decide to buy.

Agentic commerce brings AI into the process and often takes your website out of the human shopping journey. For example, instead of searching for "best winter boots Canada," a shopper might open their AI tool of choice and ask:

"Find me a pair of waterproof winter boots under $200 CAD that are suitable for temperatures below -20°C, have good traction on ice, and can be delivered to Montreal before December 15." 

An AI shopping assistant can interpret those requirements, research suitable products, compare available information, and suggest options that meet the shopper's needs. Some systems can go further by monitoring prices, preparing shopping carts, or completing eligible transactions with the shopper's authorization. 

Depending on the platform, shoppers might complete their purchases within the AI experience itself or be directed to the merchant's website. In either case, the AI assistant relies on external commerce systems, merchant integrations, or checkout infrastructure to support the transaction.

Many consumers using AI product discovery like this will still eventually go to your website to check out, but some platforms are also adding in-chat checkout capabilities, letting AI systems complete purchases on your behalf right in the chat. 

This creates an immediate opportunity for online retailers to make products easier for AI systems to discover, evaluate, and recommend to users shopping on these AI platforms. 

For an even more in-depth breakdown of all the ways to use agentic AI in ecommerce, whether it’s in customer service, marketing or sales, check out our full Agentic AI in Ecommerce series. 

Why Black Friday 2026 is different

A Black Friday ecommerce strategy used to mean building the best sales, deals, and bundles, and then fighting for search rankings, ad placements, email engagement, and customer attention with flashy marketing campaigns and content during the year's most competitive time. 

AI introduces another layer of competition, one that can influence purchasing decisions before customers even visit a retailer's website. Here’s what’s changing: 

Shoppers are moving from keywords to conversations

Traditional product searches tend to be short and to the point:

1. "Best running shoes"

2. "Black Friday laptop deals"

3. "Winter jackets Canada"

Conversational AI lets shoppers be more specific: They can describe how they plan to use a product, identify key features, set a maximum budget, and ask the assistant to explain trade-offs. For example:

"Compare three lightweight laptops under $1,500 CAD for a university student. Prioritize battery life, portability, and reliability over gaming performance."

For merchants, this makes detailed and accurate product information increasingly valuable. Clear specifications, compatibility details, use cases, and product attributes help AI shopping systems evaluate whether a product meets a shopper's requirements. Visibility isn't guaranteed, though, and recommendations depend on each platform's discovery and ranking systems.

AI can influence which products make the shortlist

When an AI assistant presents a handful of recommendations, shoppers may use those suggestions as a starting point, creating an additional visibility challenge for ecommerce brands.

Even a beautifully designed product page can't persuade a customer who never discovers the product or page at all. 

Merchants therefore need to think beyond attracting visitors to their websites. They also need to consider how their products are represented across search engines, shopping platforms, product feeds, and AI-powered discovery experiences.

Product accuracy becomes even more important during BFCM

Black Friday sales often change quickly. Merchants will switch up Black Friday deals, create new bundles or BOGO offers, or further reduce prices based on stock availability, which products they would like to move more of, and how far into the sale period they are. 

Rapidly changing promotions and inventory can create challenges for AI shopping assistants, which may retrieve product information through web searches, merchant feeds, or direct commerce integrations. If that information is outdated, shoppers could receive recommendations for unavailable products or expired discounts.

Although AI platforms are responsible for their own outputs, merchants can reduce the risk of inaccurate product information by keeping their catalogues, feeds, and websites consistent.

Which AI tools are consumers using to shop?

1. ChatGPT

Probably the most popular LLM for the average Joe, ChatGPT can help shoppers find products, compare alternatives, and identify the options that best meet their needs. Its shopping research experience supports more involved purchasing decisions, including side-by-side comparisons and personalized buying guides.

For example, a shopper might ask:

"I'm looking for a coffee machine under $500 CAD. Compare three options that make good espresso, don't require much maintenance, and are suitable for a small kitchen."

ChatGPT can ask follow-up questions, evaluate product information, and explain each option's strengths and limitations.

ChatGPT also displays shopping results with product images, details, and merchant links. Instant Checkout is available for some eligible products and merchants, but it isn't available everywhere.

For Shopify merchants using Agentic Storefronts, ChatGPT currently operates as a product discovery and referral channel. Shoppers complete their purchases through the merchant's Shopify checkout, either in an in-app browser or a separate browser tab. Other AI channels, including Microsoft Copilot, Google AI Mode and Gemini, and Meta, can support Shopify-powered checkout directly within their experiences when the feature is available and activated.

What merchants should know: ChatGPT uses product metadata, merchant information, and other retail sources to support shopping recommendations. OpenAI also supports direct merchant product feeds, while Shopify merchants benefit from existing Shopify Catalog integrations.

2. Google AI Mode and Gemini

Google combines its established search and shopping infrastructure with generative AI. Shoppers can use Google AI Mode and Gemini to research products, explore alternatives, and ask more detailed questions than a traditional keyword search might capture.

Google's AI shopping capabilities are supported by its Shopping Graph and merchant product information. Google has also introduced the Universal Commerce Protocol (UCP), an open standard designed to support interactions between AI shopping agents and merchants.

In May 2026, the platform announced additional agentic shopping developments, including its Universal Cart. However, availability and checkout integrations continue to vary by user and location. 

What merchants should know: Google Merchant Center, accurate product feeds, strong technical SEO, and appropriate structured data remain important foundations for product visibility.

Google confirms that established SEO best practices continue to apply to its generative AI search experiences.

3. Microsoft Copilot

Microsoft Copilot helps consumers research products, compare retailers, explore deals, and find gifts.  Copilot can display product information including prices, available retailers, review summaries, and other details, depending on the merchant data available.

Microsoft also introduced Copilot Checkout in the United States in January 2026, allowing eligible shoppers to complete purchases within the experience.

What merchants should know: Clear product information, competitive offers, and accurate merchant data can support visibility. Checkout capabilities and shopping features differ by market and integration.

4. Perplexity

Perplexity is another AI-powered research platform that consumers can use to explore purchasing options and find products. Its shopping functionality helps users research products, evaluate reviews, and identify relevant merchants.

Perplexity also offers Instant Buy, which lets eligible U.S.-based users purchase from participating merchants.

What merchants should know: Detailed specifications, credible reviews, and useful buying guides can help make product information more accessible to research-focused shoppers.

5. Amazon Alexa for Shopping

Amazon's AI shopping assistant, previously called Rufus and renamed Alexa for Shopping in May 2026, helps customers research and compare products within Amazon's shopping environment.

It offers personalized recommendations, product comparisons, price history, and price alerts. The platform has also introduced Auto-Buy for eligible customers and purchases, letting users authorize a purchase when a product reaches a set price.

What merchants should know: For brands selling through Amazon, accurate marketplace listings, detailed product information, and customer reviews remain important. Amazon's shopping ecosystem is distinct from the feeds and integrations used by independent ecommerce websites.

6. Meta Muse

The newest AI tool on the list, Meta’s Muse agent can be used to discover, buy, track and return products, all while generating a one-time credit card number to keep your real card information hidden from itself and the merchant you’re buying from. 

In addition to searching the web for what the user wants, Muse, as a Meta product, can also buy and sell items on Facebook Marketplace, including making offers and negotiating prices with the seller on your behalf.

How are consumers prompting AI shopping assistants?

We’ve given some examples above, but it’s worth breaking down exactly how shoppers talk to their LLMs and AI assistants as they move through this new iteration of the customer journey. Remember, understanding how shoppers communicate with AI helps you see what information merchants should provide.

Here are examples of realistic shopping prompts and the corresponding opportunities for ecommerce stores.

When talking to AI, shoppers aren’t necessarily looking for a specific product by name; instead, they’re describing a problem, use case or desired outcome. 

While merchants should still optimize for product and category keywords, they should also answer questions about suitability, compatibility, performance, value, and purchasing conditions so AI has information to draw on when recommending your store or product.  

10 ways to prepare your ecommerce store for agentic commerce before BFCM

You don’t have to rebuild your entire ecommerce store or completely rethink your content and marketing strategy to get ready for AI-powered shopping. In fact, many of the most valuable improvements are established ecommerce and SEO best practices.

The difference is that these improvements now serve two audiences: human shoppers and the AI systems helping them make decisions.

1. Make sure AI systems can access your website

Start with technical discoverability, and review your site for issues such as blocked product pages, incorrect canonical tags, unintended noindex directives, broken internal links, and important content that's hard to access. 

Next, look at your AI crawler settings. OpenAI distinguishes between OAI-SearchBot, which supports ChatGPT search discovery, and GPTBot, which is associated with model training. Merchants can manage these crawlers independently.

Shopify merchants should also understand that web crawling and Shopify Catalog are separate discovery methods. Blocking an AI crawler through robots.txt can affect open-web discoverability, but it doesn't prevent Shopify Catalog from sharing eligible product information with AI channels you've activated. Review both your crawler settings and your Agentic Storefronts configuration to understand how your products are being made available.

Review your robots.txt configuration, CDN settings, and bot-protection rules with your development team or agency. 

2. Improve the quality of your product data

Your product data is one of the most important foundations of AI ecommerce. Provide as much practical information about your products as possible so that AI bots are capable of pulling links to your stock in response to specific user queries. 

For your priority BFCM products, review:

1. Product titles and descriptions

2. Brand names and product identifiers

3. Dimensions, materials, and technical specifications

4. Colours, sizes, and other variants

5. Compatibility and intended uses

6. Current prices and inventory

7. Warranty and return information

Avoid vague marketing language where more specific details are available.  

For Shopify merchants: Review how your product information is represented in Shopify Catalog, particularly if important attributes are stored in metafields, metaobjects, or custom data structures. 

Shopify Catalog Mapping can help ensure that product titles, descriptions, categories, and other attributes are sourced correctly for participating AI shopping channels.

This is especially important for stores with complex catalogues or custom integrations, where the information available to AI shopping systems may not match everything displayed on the storefront.

3. Keep your product feeds accurate and up-to-date

A product feed is a structured collection of information that shopping platforms use to understand and display products, typically including product identifiers, titles, descriptions, images, prices, and availability.

For Google, Merchant Center provides a central way to manage product information used across shopping experiences.

OpenAI also provides product feed specifications for eligible merchants that want to share structured catalogue information directly.

Shopify's Agentic Storefronts use Shopify Catalog to make eligible product information available to supported AI shopping channels. In Shopify admin, navigate to Sales channels > Agentic to review your participation settings, product eligibility, and available channel controls. Agentic Storefronts are active by default for eligible stores, subject to Shopify's applicable terms and configuration requirements.

Check which products are included in Shopify Catalog, whether the information is accurate, and which channels have access to it. Product availability through Google and Meta may also depend on their respective Shopify sales channel integrations.

4. Implement and validate structured data

Structured data, i.e. schema markup, provides machine-readable information about your website's content.

For ecommerce stores, relevant types include:

• Product for product identity and attributes

• Offer for pricing and availability

• MerchantReturnPolicy for applicable return information

• ShippingService or OfferShippingDetails for shipping information, where appropriate

Google's merchant listing documentation explains how structured data can make products eligible for enhanced search experiences. That said, structured data helps traditional search and product understanding, but no special schema markup guarantees a recommendation or citation in generative AI results. This just ensures that your store can be properly parsed by humans, search engines and AI agents alike. 

5. Make your Black Friday promotions easy to understand

What helps human shoppers also helps AI bots. Keep promotional information consistent across your website and product feeds.

For each offer, clearly communicate the regular price, promotional price, eligible products, start and end dates, coupon requirements, exclusions, and shipping conditions.

6. Create content that answers real buying questions

As mentioned above, AI agents are particularly useful for answering specific questions, comparing options, or helping users understand purchases. This means your content should also address those same questions so they have information to pull from. 

Instead of publishing only a generic "Black Friday Deals" page, consider content such as:

• Best gifts for home cooks under $100

• How to choose the right winter jacket for Canadian weather

• Which mattress type is best for side sleepers?

• Product A vs. Product B: Key differences explained

• What to consider before buying a refurbished laptop

Include clear recommendations, meaningful comparisons, relevant specifications, and genuine limitations where appropriate.

7. Strengthen your brand's credibility

AI excels at parsing the internet and pulling information from different sources into a single response. For merchants looking to improve AI product discovery for their store, maintaining a consistent, credible brand presence is extremely helpful. 

Keep your company information, policies, product claims, and merchant details accurate across the channels where customers encounter your business. Customer reviews can also provide valuable context about product quality, fit, performance, and satisfaction.

8. Make shipping, returns, and availability clear

Delivery expectations can vary considerably depending on whether an order ships to Toronto, Vancouver, Halifax, or a remote community. Make sure shoppers can easily find accurate information about:

• Shipping costs and eligible regions

• Processing times and delivery estimates

• Holiday order cut-off dates

• Return windows and associated fees

• Product availability by variant

• Currency, taxes, and any applicable cross-border charges

If a human customer will ask it of your support team, it's extremely likely that they’re also asking their AI chatbots when sending them out into the internet to find what they’re looking for. 

9. Optimize the shopping experience for humans, too

Agentic commerce doesn't eliminate the importance of ecommerce design and user experience.

As we hit on earlier, people are asking more of their AI agents these days, but many AI-assisted shoppers will still visit your website to confirm details and complete their purchases. 

Focus on mobile performance, intuitive navigation, accessible interfaces, reliable site search, clear calls to action, and a straightforward checkout. Make sure inventory, pricing, and promotions stay consistent between your storefront and connected systems.

For Shopify merchants, review theme performance, third-party app dependencies, checkout customizations, and integrations before the BFCM rush. 

10. Measure your visibility in AI-powered shopping

Tracking and measuring AI analytics is still tricky. Traditional ecommerce analytics focuses heavily on sessions, traffic sources, conversion rates, and revenue, but AI introduces more questions:

• Are your products appearing in AI-generated recommendations? 

• Are shopping assistants describing them accurately? 

• Which competitors appear alongside your brand? 

• Are AI-referred visitors converting?

Review referral traffic from AI platforms in your analytics tools. Google also introduced dedicated generative AI performance reporting in Search Console, and Shopify’s Agentic Storefronts capabilities also provide channel-related discovery/sales insights. 

You can also build your own AI visibility audit process: Create a set of realistic prompts related to your priority products, run them across relevant shopping assistants, and record the results. Track whether your brand appears, which products are recommended, whether the information is correct, and which sources are referenced. Repeat this process a few times each audit to track differences in AI answers across prompts. 

Conclusion

AI shopping assistants are changing how consumers discover and compare products, but you don't need to reinvent your entire ecommerce strategy to prepare. Accurate product data, accessible content, reliable integrations, and a strong customer experience are still the foundations of success.

As Black Friday and Cyber Monday approach, review how your products appear across AI shopping channels and identify any gaps that could cost you visibility.

As a Shopify Platinum Partner agency, Blue Badger helps ecommerce merchants optimize their Shopify stores, product data, and integrations for today's shopping experiences and whatever comes next. Contact our team to prepare your store for BFCM and the growing world of agentic commerce.