Why AI Won’t Recommend Your BFCM Hero Products

Most Black Friday plans revolve around a handful of priority products. There’s the new-season collection that needs traction, the carryover stock that needs to move before January, and the hero products carrying the biggest share of paid media spend.

Brands spend weeks refining their offers, campaign creative and email calendars. Yet one important question often gets overlooked: can AI shopping assistants find enough reliable information about the products you’re planning to promote?

As shoppers increasingly use AI to research purchases, that gap matters. A compelling campaign and a generous discount might bring shoppers to your website, but neither guarantees that your products will appear in an AI-generated recommendation. Product descriptions, attributes, availability and customer reviews all help shape the information available to AI tools.

For brands preparing for Black Friday Cyber Monday (BFCM), the risk is particularly relevant. The products receiving the most promotional attention may be the ones with the least customer evidence behind them.

How AI shopping assistants decide what to recommend

Imagine a shopper asks an AI assistant to find a wool-blend overshirt suitable for the office, priced under £150.

The shopper isn't necessarily browsing your homepage, scrolling through a category page or seeing your latest campaign. They're looking for a product that matches specific requirements.

To produce a useful recommendation, an AI assistant needs information about the products available to it. That might include price, materials, sizing, product descriptions, availability and customer feedback.

As Okendo explains in WIRO's BFCM Playbook, AI assistants assess products “one SKU at a time”. This makes the quality and accessibility of individual product information particularly important, rather than relying solely on the strength of a brand's overall marketing.

The commercial opportunity is growing. According to figures cited in WIRO's BFCM Playbook, Shopify reported that AI-driven traffic to its stores grew eightfold year on year in the first quarter of 2026, while orders from AI-powered searches increased nearly 13-fold (PYMNTS, May 2026).

Other reported figures point in the same direction. Adobe recorded an 805% year-on-year increase in AI-driven traffic to retail websites on Black Friday 2025, according to Retail Insight Network. Digital Commerce 360 also reported that AI traffic converted 54% better than non-AI traffic on Thanksgiving.

In the UK, research cited by CX Today found that 22% of UK adults planned to use AI for holiday shopping in 2025.

These figures come from different studies and markets, so they shouldn't be treated as a single measure of UK AI shopping behaviour. However, they point to an emerging discovery channel that eCommerce brands should be preparing for.

Shopify-related reporting cited by PYMNTS in August 2026 also suggests that half of AI-referred sessions land directly on product pages, at a rate 2.5 times higher than visits from traditional search. For merchants, that reinforces the importance of ensuring product pages provide the information shoppers need to make a decision.

The implication for BFCM is straightforward: your promotional strategy needs to account for how individual products are discovered, not just how shoppers are driven to your store.

A product page that clearly communicates its features, answers common questions and provides useful customer feedback can support both discovery and conversion. A page with incomplete information gives shoppers and the systems helping them research  less to work with.

The BFCM review gap: are your hero products ready?

Customer reviews tend to accumulate around products that already sell well. An established bestseller may have months or years of feedback, while a newly launched collection has little or none.

Yet BFCM campaigns frequently prioritise products beyond the usual bestsellers. Brands may promote new-season launches, seasonal gift sets, higher-margin lines or clearance stock that needs to move before the end of the year.

That can create a mismatch between promotional investment and available customer evidence.

Sarah Skolnik, Agency Partnerships Manager at Okendo, describes the problem in WIRO's BFCM Playbook:

The issue extends beyond AI discovery. During the most competitive advertising period of the year, brands can end up sending expensive traffic to product pages that lack the reassurance shoppers need to buy.

Research from Northwestern University's Spiegel Research Center found that a product with five reviews was 270% more likely to be purchased than a product with no reviews. The research also found that the impact varied by product price, with review presence particularly influential for more expensive purchases.

A separate example published by MarketingProfs in 2017 reported that displaying reviews increased conversion by 190% for a lower-priced product and 380% for a higher-priced product at one gift retailer. These are specific research findings, not guaranteed results for every store, but they illustrate the potential value of customer feedback.

This is especially relevant for premium fashion, footwear and home brands. When shoppers are considering a more expensive coat, a pair of trainers or a piece of furniture, they may want reassurance about fit, materials, comfort, quality or dimensions before committing.

The goal isn't necessarily to collect hundreds of reviews for every product before Black Friday. It's to identify the products you're actively promoting and make sure they have useful, accessible evidence wherever possible.

Review quality matters as much as quantity

A high review count is not automatically useful if the feedback doesn't answer the shopper's questions.

Consider a customer choosing between two coats. A review that says “lovely product, quick delivery” offers some reassurance, but it doesn't explain whether the coat runs small, how warm it is or whether the fabric feels premium.

A detailed review that describes fit, comfort and material quality gives the next shopper more relevant information.

The same principle applies to footwear sizing, the durability of accessories, the feel of fabrics and the dimensions of home products.

For BFCM, review collection should therefore focus on more than volume. Recent, relevant feedback that addresses real purchase concerns can help shoppers make better-informed decisions. It may also provide useful product-level context for AI systems that can access that content.

Why your product reviews might be invisible to AI

Collecting reviews is only part of the job. Brands also need to consider whether those reviews are accessible to the systems they want to reach.

Many Shopify stores use third-party review widgets that load content through JavaScript after the main page has been delivered. This can work perfectly well for customers browsing the site in a regular browser. However, not every crawler processes a page in the same way.

In a December 2024 analysis, Vercel reported that none of the major AI crawlers it examined rendered JavaScript, while Googlebot supported full-page rendering.

That finding is specific to the crawlers and behaviour examined at the time. AI systems and crawling capabilities can change, so it shouldn't be interpreted as proof that every AI tool is unable to access JavaScript-rendered content. It does, however, highlight a technical issue worth checking.

If your reviews only appear after a script executes, some systems may not see the same content that a customer sees on the page.

Alex Wright, Partner Manager at Yotpo, explains the wider significance :

The practical question for your development team or review provider is simple: is the review content present in the page's initial HTML, or does it only become available after JavaScript runs?

If reviews are loaded dynamically, ask your provider what options are available to make that content accessible to relevant crawlers. The appropriate solution will depend on your theme, app and implementation; it may be possible to resolve the issue through configuration rather than a full rebuild.

Don't stop at reviews, either. Size guides, fit notes, product specifications and frequently asked questions can also be difficult to access if they're embedded in images or delivered through components that certain crawlers cannot process.

For Shopify merchants, the wider lesson is to treat product information as part of the technical foundations of discovery. Content needs to be accurate, useful and accessible not simply visible to a human shopper after the page has finished loading.

Which BFCM products should you prioritise?

With limited time before Black Friday, auditing every product on your store in equal detail is unlikely to be the best use of resources.

Start with the products where better information could have the greatest commercial impact. Four factors can help you prioritise.

1. Promotional and advertising investment

Start with the products receiving the most paid media spend, prominent homepage placement or dedicated campaign exposure. If a product is central to your BFCM strategy, it deserves closer attention.

Compare your promotional plan with its existing review coverage and product information. A high-investment product with few useful reviews is a clear candidate for action.

2. Price point and purchase complexity

Higher-priced products often require more consideration before purchase. Shoppers may want more reassurance about quality, fit, performance or suitability before spending.

Prioritise products where uncertainty is likely to create friction. Detailed customer feedback and clear product specifications can help address that uncertainty.

3. Common customer questions

Look at the questions your customer service team receives before and after purchase. Review support tickets, product enquiries, return reasons and existing customer feedback to identify recurring concerns.

For fashion and footwear, these might include sizing, fit and material. For home and lifestyle products, they could involve dimensions, assembly, durability or compatibility.

Use those insights to improve product descriptions, add clear answers to frequently asked questions and encourage customers to share relevant experiences in their reviews.

4. Newness and review coverage

New launches often start without an established review history. If a new product is central to your BFCM campaign, plan ahead to collect feedback from genuine purchasers as orders begin to come through.

Where reviews aren't yet available, don't manufacture social proof or imply that a product has an established track record. Instead, strengthen the information you can provide: accurate specifications, clear imagery, sizing guidance and answers to common questions.

Your priorities will depend on your BFCM strategy. A campaign led by established bestsellers with extensive review coverage may benefit more from improving technical accessibility and product-page clarity. A campaign built around new-season launches may need to focus first on information gaps and a realistic plan for collecting customer feedback.

The objective isn't to optimise every SKU at once. It's to focus on the products that matter most to your peak trading performance.

A four-week plan to improve AI product visibility before Black Friday

Black Friday falls on 27 November 2026. With the campaign approaching, merchants need a practical plan that fits around existing trading, development and promotional deadlines.

Here's how to structure the work across four weeks.

Week 1: Audit your BFCM product line-up

Map your promotional calendar against product-level information.

For each priority SKU, review:

• The number and recency of customer reviews.
• Whether reviews contain useful details about fit, quality, materials or performance.
• The completeness of product descriptions, specifications and sizing information.
• The accessibility of review content in the initial HTML.
• The questions customers ask most frequently about the product.

Rank the products according to promotional investment, purchase complexity and the size of their information gaps. This gives your team a manageable list of priorities instead of an open-ended site-wide audit.

Week 2: Collect more useful customer feedback

Identify products that need additional reviews and contact eligible customers who have already purchased them.

Make review requests straightforward and timely. Where your review platform allows it, use neutral prompts that encourage customers to describe their experience in useful detail, such as how a product fits, feels or performs.

Follow the rules that apply to your review collection process. Feedback should reflect genuine customer experiences, and incentives or other material connections should be disclosed where required.

Prioritise the products that feature most prominently in your campaign, but remember that review collection takes time. Don't assume every request will produce a review before Black Friday.

Week 3: Improve product information and accessibility

Work with your eCommerce, development and customer experience teams to close the most important gaps.

Update product descriptions with accurate information about materials, dimensions, sizing and use cases. Add answers to recurring customer questions in readable text, rather than relying exclusively on imagery or inaccessible interactive elements.

Check how your review provider delivers content to the page. If important information is only available after JavaScript executes, investigate the available options for improving crawler access.

You should also review the consistency of your product data, including pricing, availability and product attributes. AI recommendations cannot reliably match shoppers with products if the underlying information is incomplete or out of date.

Week 4: Validate the changes and protect the release

Once changes are live, revisit the priority product pages.

Check that the new content is visible, that reviews load correctly for customers and that your technical changes haven't introduced problems with the shopping experience.

You can also test representative queries in AI shopping assistants to see whether your priority products appear and how they're described. Treat these checks as directional observations, not a guarantee of future visibility: results can vary between tools, queries and users.

Finally, coordinate with your development team around the BFCM release freeze. Any changes that affect product templates, review integrations or structured data should be tested properly before peak trading begins.

Okendo's contribution to WIRO's BFCM Playbook includes further practical guidance on collecting reviews ahead of peak. It's a useful companion to this checklist for brands looking to turn preparation into action.

Make review optimisation part of your CRO strategy

Improving review coverage before Black Friday is a useful starting point, but the bigger opportunity is to make product information part of ongoing conversion rate optimisation (CRO).

Reviews can help shoppers evaluate a product, but they also reveal the questions that prevent people from buying. If customers repeatedly mention sizing uncertainty, unclear dimensions or unexpected material quality, those patterns can inform improvements to the product page and the wider customer experience.

For example, a fashion brand might test a clearer fit summary near the size selector. A footwear retailer might make sizing guidance easier to find before a customer adds a product to their basket. A homeware brand might bring dimensions and practical-use information higher up the page.

These changes should be prioritised and tested against meaningful outcomes, such as conversion rate, returns and customer confidence, rather than assumed to work simply because they add more content.

This is where technical implementation, UX and CRO need to work together. Better information needs to be accessible to the systems interpreting it and useful to the people making the purchase.

At WIRO, this joined-up approach underpins our CRO and growth work with eCommerce brands. Product information, customer experience and technical implementation are considered together because improvements in one area can affect the performance of another.

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

Conclusion: prepare your products for AI-assisted shopping

Your BFCM hero products may have the right offer, the right creative and the right media budget. But if their product information is incomplete, their reviews are limited or important content is difficult for relevant crawlers to access, you may be leaving an important part of product discovery to chance.

AI recommendations aren't determined by reviews alone. Product attributes, relevance, availability, pricing and other information all matter, and different AI tools may use different methods to generate recommendations.

Nevertheless, customer feedback and accessible product information are areas merchants can improve before peak trading.

Start with the products that matter most to your BFCM strategy. Audit their review coverage, address the questions shoppers actually ask and check that important content is accessible beyond the standard browser experience.

You don't need to overhaul your entire Shopify store to make a start. You need a clear view of where the biggest gaps are and a practical plan to close them before Black Friday.

Get the full expert perspective in WIRO's BFCM Playbook

Reviews are only one part of the changing relationship between AI and eCommerce. Our BFCM Playbook brings together Okendo, Yotpo and more than a dozen technology partners to explore how AI is influencing product discovery, conversion, customer service and retention.

Each partner shares practical recommendations to help brands prepare for peak trading, from improving product information to strengthening the wider customer experience.

If you're preparing your Shopify store for Black Friday and want to turn these insights into a practical action plan, download the BFCM Playbook or speak to the WIRO growth team about your priorities.