{"id":35311,"date":"2025-11-19T08:00:51","date_gmt":"2025-11-19T13:00:51","guid":{"rendered":"https:\/\/www.kaspersky.co.za\/blog\/?p=35311"},"modified":"2025-11-21T15:11:19","modified_gmt":"2025-11-21T13:11:19","slug":"black-friday-ai-assistance","status":"publish","type":"post","link":"https:\/\/www.kaspersky.co.za\/blog\/black-friday-ai-assistance\/35311\/","title":{"rendered":"Hacking Black Friday: using LLMs to save on the “sale of the year”"},"content":{"rendered":"

Black Friday is an annual bargain hunt that often spirals into chaotic impulse buying. Stores promise incredible discounts of 50\u201370%, but are those savings really as significant as they seem? In 2025, we\u2019ve got a new ally on our side in the fight for smart spending: artificial intelligence. Here\u2019s how you can use powerful LLMs like ChatGPT and Claude to save money and never fall for a shady seller\u2019s tricks again.<\/p>\n

Before we enlist AI to help you save, it\u2019s crucial we understand the battlefield. Studies paint a grim picture: a significant portion of those Black Friday \u201csuper discounts\u201d are nothing more than a marketing illusion<\/a>.<\/p>\n

The tactic is simple and effective: in early October, stores hike up their prices<\/a>, sometimes by fifty to a hundred percent. Then, when Black Friday finally hits, they \u201cslash\u201d the price by that same 50% and proudly tout the impressive discount on the tag. In reality, you\u2019re just buying the item at its regular price \u2014 or sometimes even paying a premium.<\/p>\n

While the European Union\u2019s Omnibus Directive mandates that retailers display the lowest price from the last 30 days, even this rule is easily skirted. Retailers just hike the price up 30 days before the event, which allows them to technically adhere to the directive while still duping consumers<\/a>.<\/p>\n

How LLMs can help you save<\/h2>\n

Artificial intelligence is changing the game. Analysts estimate that in 2024, AI tools helped consumers make a staggering $60 billion<\/a> in transactions during Cyber Week, and that number is only projected to climb in 2025. Already, one in three U.S. shoppers plans<\/a> to lean on AI for their shopping needs.<\/p>\n

As you know, an LLM is immune to emotion; it won\u2019t react to marketing triggers like \u201c2 hours left!\u201d or \u201conly one left in stock!\u201d Instead, the model analyzes huge volumes of data, compares prices, tracks price history, and helps you make rational decisions.<\/p>\n

In seconds, AI can crawl hundreds of online stores, zeroing in not only on the product you want at the lowest price but also on cheaper alternatives with comparable specs. Modern LLMs can help you figure out if a discount is truly beneficial \u2014 or if you\u2019re falling for a scam. Amazon, for example, has already integrated a price-tracking feature into its AI assistant, Rufus<\/a>, though users have noted that the tool still has some kinks to work out<\/a>. Using just a few prompts, the AI can factor in your preferences, budget, and past purchases to suggest exactly what you need, cutting through all the marketing noise. Instead of wasting hours poring over spec sheets, just ask the assistant, \u201cWhat\u2019s the difference between vacuum cleaner A and vacuum cleaner B?\u201d And you get your answer \u2014 regardless of whether the seller\u2019s website features a comparison tool. You can use the prompts below for ChatGPT, Claude, or Gemini.<\/p>\n

Preparing for Black Friday with AI<\/h2>\n

Step 1. Create a wish list<\/h3>\n

Don\u2019t wait for the sales to start; your goal is to gather all the baseline data upfront.<\/p>\n

Help me create a shopping list for Black Friday. My budget is: [amount].
\nI'm interested in the following categories: [electronics\/clothing\/home goods].
\nPriorities: [performance\/quality\/brand\/price].
\nCreate a structured list with explanations of why each item is worth considering.<\/code><\/p>\n

Step 2. Start tracking prices<\/h3>\n

This is a critical stage. You need to know the real price of an item before the Black Friday marketing hype machine starts rolling. On Amazon, tools like CamelCamelCamel<\/strong><\/a> and Keepa<\/strong><\/a> can help, and for AliExpress, look at AliPrice<\/strong><\/a> and AliTools<\/strong><\/a>.<\/p>\n

Step 3. Analyze price dynamics<\/h3>\n

Collected the price data? Excellent. If you see a sharp price spike in October followed by a corresponding drop in November, you\u2019re looking at the classic scam tactic. But if the data on the charts seems unclear, use the prompt below. The months we used are just examples, so feel free to use your own date ranges. The larger the intervals between the price checks, the higher your chances of catching an unjustified price hike.<\/p>\n

I'm tracking [product name] on [platform]. Here's the price data:
\n- September: [price]
\n- Early October: [price]
\n- Late October: [price]
\n- Current price: [price]
\n- Advertised discount: [percentage]
\n- Analyze this data. Is this a genuine discount or is the store manipulating prices?
\nWhen is the best time to buy? Should I wait for Black Friday or buy now?<\/code><\/p>\n

Step 4. Search for alternatives<\/h3>\n

Don\u2019t get fixated on a single product. There may be more advantageous alternatives available.<\/p>\n

I want to buy [product, model]. My goal is to [what it's needed for]. Budget: [amount].
\nFind 3\u20135 alternative products that solve the same problem but might be more cost-effective.
\nCompare them based on features, price, and reviews. Display the results in a table.<\/code><\/p>\n

Experience shows that LLM models are particularly good at comparative analysis, highlighting key differences between similar products.<\/p>\n

Step 5. Vet the seller and the website<\/h3>\n

Black Friday is an absolute field day for scammers. In the third quarter of 2025 we saw the number of fake online stores skyrocket by 20% compared to the monthly average. Let\u2019s run through the immediate red flags that should raise your suspicions:<\/p>\n