Is AI Recommending Your Brand This Black Friday?

Most BFCM plans focus on what happens when a shopper reaches your website: the landing page, the product discovery journey and the checkout experience. But an increasingly important decision can happen before any of that, when a shopper asks ChatGPT, Gemini or Google’s AI Mode what to buy.

A shopper looking for a premium winter coat, a gift for a design-conscious homeowner or everyday trainers may receive a shortlist of recommendations before visiting a single retailer. If your brand isn't included, or the assistant describes it inaccurately, you could lose a potential customer before your website has a chance to convert them.

For eCommerce brands preparing for Black Friday Cyber Monday (BFCM), this raises an important question: when shoppers ask AI for recommendations in your category, does your brand make the shortlist?

You can have the right products, competitive pricing and a well-funded campaign, yet still miss out if AI assistants don't understand what makes your brand relevant.

The shortlist now forms before the click

AI-assisted shopping is no longer just an emerging trend to monitor. It is becoming part of how consumers research products, compare brands and decide what to buy.

Salesforce reported that AI and agents influenced 20% of global orders during Cyber Week 2025 through personalised recommendations and conversational customer service. Before the season, an Adobe survey of 5,000 US consumers found that 53% planned to use AI services for research before purchasing, according to TechCrunch.

UK shoppers are showing similar interest. Salesforce research cited by CX Today found that 22% of UK adults planned to use AI for holiday shopping in 2025.

The trend has continued into 2026. According to reporting by PYMNTS, AI-referred traffic to Shopify stores tripled year on year in the second quarter, with orders from those channels also tripling. In the first quarter, orders from new buyers arrived through AI searches at nearly twice the rate seen in traditional organic search.

These figures come from different studies and reporting periods, so they shouldn't be treated as a single measure of AI shopping adoption. However, they point to a meaningful opportunity: AI discovery can introduce brands to shoppers who haven't purchased from them before.

For growth teams, that's particularly important during BFCM. The customer journey may begin with a conversational question rather than a Google search, a social advert or a visit to your homepage.

In WIRO's BFCM Playbook, Operations Director Amy Highland describes AI as a new layer of discovery that sits in front of the website, rather than simply another marketing channel to optimise.

That distinction matters. Traditional search optimisation often focuses on earning visibility for relevant queries. AI discovery adds another consideration: whether an assistant understands your products well enough to include them in a useful recommendation.

Why brands disappear from AI shortlists

It's tempting to assume that AI recommendations are primarily a price comparison, with a cheaper competitor winning the shopper's attention. But a more fundamental problem can arise before price becomes relevant: your brand may never be considered.

Christian Kilin, Co-Founder and CEO of Glara, which measures how AI assistants represent luxury and fashion brands, describes this problem in the Playbook:

Glara's tracking illustrates how AI assistants can establish unexpected competitive comparisons. For one British leather goods label it monitors, a more accessible American brand appears in a quarter of AI answers about the label, and the rival's website is cited more frequently than the label's own.

The implication is that AI-generated comparisons don't necessarily reflect the competitive landscape a brand has defined for itself. Assistants draw on the information available to them and may connect brands in ways their marketing teams wouldn't expect.

Three recurring information gaps can contribute to this problem.

1. Product information doesn't explain what makes the product relevant

Fashion, footwear and home purchases rarely come down to a single keyword. Shoppers might specify material, fit, occasion, budget, dimensions or delivery requirements in one question.

A product page that provides little more than a title, price and hero image offers limited detail to match against those requirements. A more complete description gives shoppers and AI systems a clearer understanding of the product's characteristics and intended use.

Amy Highland captures the shift in the Playbook:

For Shopify merchants, this means looking beyond whether a product page is technically published or indexed. Are its materials, construction, fit, dimensions, care instructions and key benefits clearly described? Are product variants labelled consistently? Can a shopper distinguish your product from alternatives using the information available?

The more accurately your catalogue communicates what you sell, the easier it becomes to assess whether a product matches a specific request.

2. Independent evidence about your brand is limited

Your website explains how you want your brand to be understood. Independent sources provide another perspective.

Customer reviews, editorial coverage, product comparisons and relevant community discussions can offer additional evidence about a product's quality, suitability and reputation. AI assistants may draw on these sources when generating answers, depending on the platform and query.

A strong product with limited independent coverage may therefore have less supporting information available than a competitor with more established reviews and external mentions.

This doesn't mean every brand needs to pursue the same publications or generate large volumes of content. The priority is to identify the evidence that matters in your category and understand which sources AI assistants actually cite when answering commercially relevant questions.

3. Practical store information is unclear or inconsistent

A shopper considering a purchase may need to know whether an item runs true to size, whether a sofa fits a particular space, when an order will arrive or whether a product can be returned.

If delivery cut-offs, returns policies and sizing guidance are vague, buried or inconsistent across your website, assistants may struggle to provide accurate answers.

These details can appear less important than product discovery, but they often determine whether a shopper feels confident enough to buy.

For BFCM, when delivery deadlines and returns conditions can directly influence purchasing decisions, clear and consistent information is particularly valuable.

What Shopify merchants can control and what they can't

Improving AI visibility doesn't mean trying to control every recommendation an assistant generates. Different platforms use different sources and methods to select and present products. You can't guarantee that a particular product will appear for every relevant query.

You can, however, improve the information available to those systems.

Shopify Catalog structures product information from eligible merchants so AI channels, including ChatGPT and Copilot, can discover and understand products. According to Shopify's guidance, the platform can also fill in certain missing attributes when the available product information is sufficiently clear.

That creates an important responsibility for merchants: the information AI uses may not be limited to the exact wording your team has written. The structure and quality of your product data also matter.

Shopify provides a foundation, but individual AI channels determine how products are ranked, described and presented. Being included in a catalogue isn't a guarantee of a recommendation.

Chris Nawrocki, CCO and Founder of Heur, frames the broader issue as one of brand governance:

The analogy is useful. You wouldn't expect a sales associate to explain your collection accurately without providing information about the materials, fit, craftsmanship and customer policies. The same principle applies to the information available to AI assistants.

For Shopify merchants, the work falls into two related but distinct areas.

Improve discoverability through better product data

Start with the foundations of your product catalogue.

Shopify recommends selecting accurate product categories because these determine which attributes are relevant and which attributes the platform can apply or infer. Clear variant options also matter: size, colour and material should be represented consistently rather than buried in ambiguous product names.

Review your priority products for missing or inconsistent information. Where relevant, make sure descriptions clearly explain:

• Materials, construction and product specifications.
• Fit, sizing, dimensions and care requirements.
• Intended use, occasion and key benefits.
• Available variants, pricing and stock status.

For premium brands, this is also an opportunity to communicate value. If craftsmanship, material quality or specialist design justifies a higher price, the product information should explain those differences clearly rather than relying on brand positioning alone.

Improve answer accuracy through clear store information

Shopify's free Knowledge Base app offers another way to improve how AI assistants answer questions about your store.

The app lets merchants review questions customers ask about their business, customise answers and identify questions AI cannot currently answer from the available information.

This is particularly useful for practical details such as delivery, returns and store policies. If an assistant repeatedly provides outdated or incorrect information, investigate the underlying source and correct it.

However, Knowledge Base is not a complete AI visibility solution. It helps improve the accuracy of store-related answers; it doesn't guarantee that your brand or products will appear in recommendations.

Treat product data, store answers and independent evidence as complementary parts of the same effort.

How to run an AI visibility audit before Black Friday

Before making changes, establish what AI assistants currently say about your brand. Both Glara and Heur recommend starting with this kind of assessment in WIRO's BFCM Playbook.

The objective isn't to collect a few screenshots showing that your brand appears in ChatGPT. It's to understand whether you're visible for commercially relevant questions, how accurately you're represented and which sources support the answers.

A structured audit can help your team identify patterns and prioritise fixes.

Step 1: Choose the products that matter commercially

Start with the products that feature prominently in your BFCM plan.

These might include hero products, high-margin lines, popular gifts, new launches or products receiving significant paid media support. There's little value in auditing your entire catalogue with equal intensity if your immediate objective is to improve discovery for a smaller group of priority products.

For each product, identify the key reasons a shopper might choose it, the questions they are likely to ask and the competitors they might consider.

Step 2: Test different types of shopper questions

People use AI at different stages of their buying journey. Some are exploring options; others are comparing specific brands or resolving concerns before purchasing.

Your prompts should reflect those different needs.

Step 3: Test multiple AI assistants

Run your prompts across several relevant assistants, such as ChatGPT, Gemini and Google AI Mode.

The same question can produce different answers across platforms, and results may vary with phrasing, location and timing. A brand that appears in one answer may be absent from another.

Keep the prompts consistent during each audit round so you can compare results more meaningfully. Avoid treating a single response as proof of overall visibility.

Step 4: Record three things for every answer

For each prompt, document:

• Brand presence: Does your brand appear, and is it recommended or merely mentioned?
• Brand accuracy: Are your products, positioning, price point and practical details described correctly?
• Sources cited: Which product pages, reviews, publications or other websites support the answer?

The third point is particularly valuable. If assistants repeatedly cite a competitor's product pages or independent coverage, those sources can help explain why the competitor is being included.

The aim is to find recurring patterns rather than chase individual answers. Treat the audit as a directional baseline, then repeat it after making changes to assess whether the results are improving.

Turning AI audit findings into practical fixes

Once you have your results, group the problems by their underlying cause. This makes it easier to assign ownership and prioritise work that can be completed before BFCM.

If your products rarely appear in discovery prompts, improve product data

Review product categories, attributes and variant information in Shopify. Then check whether product pages clearly communicate the features shoppers are likely to specify in their questions.

For a premium fashion brand, that could mean improving descriptions of fabric composition, construction, fit and care. For a home brand, it might mean clarifying dimensions, materials, finishes and intended use.

Don't add keywords simply to make a page longer. The goal is to provide specific, accurate information that helps distinguish the product and match it to relevant shopping needs.

If AI gets store information wrong, fix the source

Incorrect delivery estimates, outdated returns policies and inconsistent sizing guidance can undermine trust.

Update the relevant policy pages and product information first. Then review the questions and answers available through Shopify's Knowledge Base app, where appropriate.

Prioritise questions that could directly affect a purchase decision, especially during peak trading when delivery cut-offs and returns conditions become more important.

If competitors dominate the cited sources, investigate the evidence gap

When AI answers repeatedly cite other brands, publications or review sources, the issue may extend beyond your own website.

Start by identifying the sources that appear most frequently and assessing whether they are relevant to your category and target customers. Look for gaps in customer feedback, credible editorial coverage or useful product comparisons.

Review collection for priority products may be achievable within weeks, although results depend on customer response. Building editorial coverage, partnerships and a stronger independent reputation usually takes longer.

Not every competitor mention requires a response. Focus on comparisons that affect commercially important products and reveal a genuine gap in how your brand is understood.

Prioritise what can be changed before peak

With Black Friday on 27 November 2026, the most practical approach is to separate immediate fixes from longer-term work.

Product attributes, product descriptions, policy pages and store answers are often within your team's control. Independent evidence and broader reputation building may take longer, but starting now can support future trading periods as well.

Coordinate the work across marketing, merchandising, development and customer experience. Agree on the priority products, assign ownership and ensure any changes to product templates or integrations are tested before your peak code freeze.

Make AI visibility an ongoing part of eCommerce growth

AI visibility shouldn't become an annual checklist completed a few weeks before Black Friday.

Product data changes, collections evolve, stock availability shifts and store policies are updated. AI assistants also change how they retrieve and present information. A one-off audit cannot account for all of that.

The stronger approach is to make AI visibility part of the wider eCommerce optimisation process.

Merchandising teams should maintain accurate product information. Marketing should ensure the brand narrative is clear and supported by credible evidence. Development teams should make important content accessible and structured appropriately. Customer experience teams should identify the questions that prevent shoppers from buying.

These responsibilities overlap with conversion rate optimisation (CRO). The product information that helps an AI assistant understand a product can also help a human shopper decide whether to purchase it.

At WIRO, we bring strategy, UX, Shopify development and continuous testing together through our CRO and growth retainers. The aim is to improve the wider shopping experience, rather than treat AI visibility as an isolated technical task.

You can explore our case studies to see how we approach eCommerce growth across fashion, lifestyle and home brands.

Conclusion: make sure your brand makes the shortlist

Black Friday discovery increasingly begins before a shopper reaches your website. AI assistants can shape which products people consider, which brands they compare and what they believe about a product before they click through.

You cannot dictate what every assistant recommends, but you can improve the information it has to work with. Accurate product data, clear store answers and credible independent evidence all help build a more complete picture of your brand.

Start by auditing the products that matter most to your BFCM strategy. Identify where your brand is missing, where its description is inaccurate and which sources influence the answers. Then prioritise the fixes that can make a difference before peak trading.

The objective isn't to control every AI answer. It's to make your brand easier to understand, more accurately represented and better prepared to compete for consideration.

Explore the WIRO BFCM Playbook

Glara and Heur are among more than a dozen technology partners contributing to WIRO's BFCM Playbook. Their perspectives explore AI discovery alongside wider changes in product information, customer service and the agentic shopping journey.

The Playbook brings together practical recommendations to help eCommerce brands prepare for 27 November and beyond.

If you'd like support turning your AI visibility audit into improvements across your Shopify store, explore our CRO and growth services and speak to the WIRO team.