As we rapidly approach the holiday season, thousands of eager deal hunters will be hitting the stores, both online and in person, hunting after coveted Black Friday sales. But before they do, the all-important research phase begins.
When people are turning to AI assistants to ask where to shop, find out whether a discount is genuine, or how to get early access, the answer may mention a retailer—but it may also draw its conclusions from a deal site, a finance blog, a price-history tool, or a consumer review.
That changes the job for marketers trying to get in front of those shoppers as they plan their Black Friday activity. Visibility is no longer just about being named. It is about being associated with the right category, and supported by useful information.
Meltwater analyzed two weeks of Black Friday answers from nine AI assistants to understand which brands appeared, what information shaped the recommendations, and where marketers can still influence the answer.
Contents
How Black Friday AI recommendations were measured
The Black Friday shortlist forms before the shopping conversation begins
Black Friday recommendations are split by shopper intent
AI recommends retailers but relies on other sources
AI is questioning Black Friday discounts
Specific offers are easier for AI to repeat
Online shopping is the default, but no retailer owns the advice
What marketers should publish before Black Friday peaks
Frequently asked questions about Black Friday AI recommendations
How Black Friday AI recommendations were measured
Meltwater GenAI Lens captured answers from nine AI assistants: ChatGPT, Claude, Copilot, DeepSeek, Google AI Mode, Google AI Overviews, Llama, Perplexity, and Grok.
The assistants responded to four prompts:
- Where can I find the best deals this Black Friday?
- How can I get early access to Black Friday sales online?
- Is it better to shop Black Friday online or visit stores?
- Are there any hidden ways to save extra money this Black Friday?
| Capability | Meltwater GenAI Lens |
| Analysis window | October 13–26, 2026 |
| Data sources | Answers from nine AI assistants to four Black Friday questions, including the web pages cited in those answers |
| Brands / entities tracked | Retailers, deal sites, cashback services, price tools, publishers, regulators, and other entities named organically in the answers |
| Key term definitions | Mention rate: the percentage of answers to a prompt that named an entity at least once. Prominence: how early and centrally an entity appeared in an answer. Visibility: a combined 0–100 measure using mention rate and prominence. Sentiment: a 0–100 score, with 50 representing neutral. Because every prompt requested recommendations, sentiment is best used comparatively. Citation: a web page attached to an AI answer as supporting evidence. |
The brands in this analysis were not preselected. These figures show how often entities appeared in the answers; they do not represent market share, consumer preference, sales, or conversion rate.
Download a one-page PDF summarizing the findings of this analysis.
The Black Friday shortlist forms before the shopping conversation begins
The online social conversation from shoppers starts late. The AI shortlist does not.
Black Friday shopper posts peak in November: our social analysis of 5.67 million Black Friday posts found that 61.9% were published between November 1 and Cyber Monday. Only 11.4% appeared between August and October.
The AI analysis took place earlier, between October 13-26. And the same retailers were already appearing consistently across the four questions: Walmart in 46% of answers, Amazon and Target in 45% each, and Best Buy in 43%.
By the time most shoppers begin posting, AI assistants already have a familiar group of recommendations established. Marketers waiting for the November conversation to peak may well be arriving after the shortlist has formed, reducing their chances of showing up in a meaningful way.
Publish offer details early, while there is still plenty of time for AI systems and the sources they rely on to pick them up.
Black Friday recommendations are split by shopper intent
AI does not produce one monolithic leaderboard for Black Friday. Rather, it builds its shortlists for different shopping intent, and the recommendations change depending on the job the shopper is trying to accomplish.
- When shoppers ask where to find the best deals, retailers dominate the answer.
- When they ask how to save more, cashback services and price-history tools move to the front.
- When they ask whether to shop online or in stores, the answer shifts toward convenience and friction—and almost no retailer owns the category.
That means retailers are competing for several kinds of visibility at once: category authority, savings credibility, membership value, and positive shopping experience. A brand can lead in one of those conversations and barely appear in another.
The best-deals prompt produced a crowded retailer shortlist. Amazon appeared in 97% of answers, Best Buy in 94%, Walmart in 93%, and Target in 87%. AI assistants often named several retailers together, linking each to a product category: electronics, toys, home goods, appliances, bulk purchases, or televisions.
The hidden-savings prompt produced a different kind of recommendation. Rakuten appeared in 46% of answers, ahead of Target at 29% and Amazon at 28%. Honey appeared in 26%, TopCashback in 24%, Capital One Shopping in 22%, and Ibotta in 21%. These entities were recommended because of the saving mechanism itself while the retailer merely became the place where shoppers used the discount, cashback, gift card, or browser extension.
The online-versus-in-store prompt barely produced a retailer ranking at all. Across that question, the assistants generated just 37 brand mentions, compared with 1,715 for the best-deals prompt. Every assistant recommended shopping online by default. Advice was focused on avoiding crowds, comparing prices, tracking limited stock, and using pickup when available.
These different answer patterns give marketers a practical way to plan. Match the content to the job the shopper wants AI to solve: use category-specific product information for deal searches, a measurable benefit for savings searches, precise membership and timing details for early access, and clear information about pickup, stock, delivery, or returns for shopping-experience questions. A promotion may attract attention, but question-specific information gives AI something useful to repeat.
AI recommends retailers, but relies on other sources
Being recommended gets a brand into the answer. The cited sources help explain why it is there.
A citation is a source link that the AI assistant attaches to an answer. Across our analysis, seven of the nine assistants supplied citations, totaling 2,878 cited pages.
The pages behind Black Friday AI recommendations were rarely retailer product pages. Instead, deal and affiliate sites supplied much of the information that the AI models drew from:
- Blackfriday.com received 94 citations and RetailMeNot received 38.
- Personal-finance and educational publishers shaped saving advice: Joingerald.com received 121 citations, Dayzora.com 85, and Well Kept Wallet 57.
- Technology and consumer media helped establish category authority, with CNET receiving 67 citations, PCMag 65, and ConsumerAffairs 47.
The Amazon case shows the gap most clearly: It appeared in 97% of answers to the best-deals question, yet the site amazon.com did not rank among the 100 most-cited domains.
Target had a similar absence in citations. Walmart.com received 38 citations and BestBuy.com 37, but third-party publishers supplied much more of the surrounding explanation.
Thus, a retailer can own the recommendation while another source owns the reason.
Marketers looking to shore up their AI answer presence this Black Friday need to consider that AI assistants need material they can use to explain why a brand belongs in the answer. A page that announces a sale is a promotion. A page that explains the access rules, categories, price conditions, return policy, and timing is impartial evidence.
AI is questioning Black Friday discounts
While recommending where to shop, five of the nine assistants also warned shoppers to check whether the discount was genuine.
- Grok told shoppers that only about one in three Black Friday deals reaches a true season low.
- Perplexity recommended checking a product’s 90-day or one-year price history.
- Even when shoppers asked where to find the best deals, assistants directed them toward tools such as CamelCamelCamel and Keepa to verify the price first.
The warnings were not usually attached to one named retailer’s policy or another. Instead, the assistants questioned the category’s pricing practices.
That concern mirrors the analysis of 5.67 million Black Friday social posts, where pricing trust was the leading shopper complaint at 30.1%, compared with 15.3% for affordability and debt.
It boils down to people, and the AIs, questioning “Is this really a deal?”
That fundamental concern among consumers changes what promotional content needs to accomplish. A large percentage-off claim may attract attention, but it doesn't do much to resolve the doubt. Price history, eligibility conditions, price-match rules, post-purchase adjustment windows, and return terms give the shopper something they can easily check.
Specific offers are easier for AI to repeat
Vague promotions give AI little to work with. Offers that specify who qualifies, when they start, and what they include are easier to describe accurately. The answers around "early-access" show how this works.
Walmart led early-access recommendations, appearing in 65% of answers. Assistants repeatedly mentioned its members-only head start. Google AI Overviews described a five-hour head start, while Copilot and Perplexity referred to member-only early shopping hours.
Walmart.com received 28 citations for the early-access question, its strongest showing across the four prompts. The answer had something specific to work with: a named membership program, a defined audience, and a time-based benefit.
The same pattern appears in the language used across early-access answers. “Early access” appeared in 73% of responses, “members” in 32%, “loyalty programs” in 18%, “accounts” in 17%, and “notifications” in 15%.
Compare that with a broad claim such as “our biggest Black Friday sale.” It may sound exciting, but it leaves an assistant with very little to explain. Who gets access? When does it begin? Which products qualify? What does the shopper need to do?
Specificity gives the recommendation shape and detail. So, marketers have practical checklist: publish the membership tier, access window, eligibility rules, product exclusions, notification process, and any relevant fees in plain language.
Online shopping is the default, but no retailer owns the advice
The online-versus-in-store question reveals a different kind of opportunity for marketers approaching Black Friday promotions: look at what customers are trying to avoid by shopping online, and use it to either differentiate your in-person experience.
All nine assistants recommended shopping online by default, with only two offering a retailer by name. The rest answered with practical advice: avoid crowds, compare prices more easily, watch for shipping delays, and use pickup when possible.
Crowds appeared in 71% of answers. Convenience and long lines each appeared in 36%, while shipping delays appeared in 21%.
This is a rare open lane in the dataset. The assistants have a strong point of view about how to shop, but no retailer owns the advice.
A brand can enter that answer by providing proof of a better experience: accurate stock visibility, dependable collection, flexible returns, clear delivery expectations, or a way to avoid the busiest in-store moments. The opportunity is less about shouting a lower price and more about answering the friction shoppers already anticipate.
What marketers should publish before Black Friday peaks
The findings point to a useful seasonal planning timeline:
- Choose the question. Decide whether the campaign is built to win best-deal, early-access, savings, category, or shopping-experience questions.
- Give the offer something concrete to say. Publish numbers, dates, membership conditions, eligible products, and exclusions.
- Make the discount verifiable. Include price history, comparison rules, return conditions, and adjustment windows where relevant.
- Map the evidence. Identify the deal sites, finance publishers, category reviewers, and community platforms shaping the answer.
- Publish before the peak. By the time shopper conversations surge in November, the AI shortlist may already be established.
- Measure the answer itself. Track whether assistants mention the brand, describe the offer accurately, cite useful sources, and leave important questions unanswered.
Meltwater helps marketing teams bring those signals together. GenAI Lens shows how AI assistants describe a brand and which sources support the answer.
Social listening reveals the concerns emerging in the shopper conversation and media intelligence shows how publishers frame the category and the offer. Campaign measurement, post-level analysis, and visual analysis help teams understand which content addresses those concerns.
For campaigns that include creators, creator research and partnership management can extend the same view into who is discussing the offer and how that content performs.
The practical advantage is a clearer path from signal to decision: identify the question, find the information gap, publish the evidence, and monitor whether the answer changes.
Frequently asked questions about Black Friday AI recommendations
Which retailer appeared most often across the Black Friday answers?
Walmart appeared in 46% of answers across all four questions, followed by Amazon and Target at 45% each and Best Buy at 43%. Rankings changed significantly depending on the question.
Why can a retailer appear in an AI answer without its own website being cited?
AI assistants may recommend a retailer after reading deal pages, comparison articles, finance blogs, or consumer media. Those sources can describe the retailer’s offer even when the retailer’s own domain is not cited.
How can retailers make Black Friday offers easier for AI to repeat?
Publish specific details about membership access, timing, eligible products, discount conditions, returns, pickup, price matching, and post-purchase adjustments. Clear, reference-friendly information gives assistants more accurate material to summarize.
When should retailers publish Black Friday content?
Before the November conversation peaks. In this analysis, the AI shortlist was already established between October 13 and 26, while 61.9% of shopper posts occurred between November 1 and Cyber Monday.
Why does price history matter in Black Friday AI answers?
Price history helps shoppers judge whether a discount reflects a genuine seasonal low. Five of nine assistants warned that advertised Black Friday discounts might not represent real savings.
Do all AI assistants provide sources for their recommendations?
No. Perplexity attached 815 sources during the analysis window and Copilot attached 545, while DeepSeek and Llama attached none. GenAI Lens tracking across other topics from July through October shows the same behavior for those two models.
Can AI visibility measure Black Friday campaign performance?
AI visibility can show whether a brand appears in relevant answers, how the offer is described, and which sources support the recommendation. It should be evaluated alongside social conversation, media coverage, campaign engagement, and business outcomes.
