October 13, 2026
Here’s a phrase you never hear at D2C scaleups: “oh no, we started planning for Black Friday too early.”
Most founders feel constantly behind when peak season rears its head, not least because its timeline creeps forward each year. In 2026, deals started appearing in September and fewer than one in five plan to wait until Black Friday to start shopping.
The ideal preparation would involve an army of data analysts, marketing strategists, and influencers working for months to build the ultimate Black Friday/Cyber Monday (BFCM) funnel. Failing that though, smart founders can reach for their little robot pals to help them out.
This guide shares a series of AI prompts you can use over the next six weeks* to feel like you have an entire BFCM team supporting you over the coming weeks.
It is not another “Win Black Friday in 14 Seconds” post. At Zendbox, we view AI as a powerful tool that has clear limitations and risks. So we designed our prompts to help you get more value out of LLMs, rather than outsourcing all of your work, creativity, and basic mental faculties to your AI minion.
Epsilon estimates there’s nearly £18 billion up for grabs between BFCM and January sales, with the average UK consumer planning to spend £334 across the peak window. These are the handful of prompts our experts believe will help you win the most of that windfall during BFCM and beyond.
* If you’re reading this in mid November, don’t worry: these prompts will still be effective. You might just have to work a tiny bit harder over the coming fortnight.
Your BFCM strategy is too important to give AI complete control. So before you go ham with these prompts, let’s walk through a few basic best practices to apply across the board.
First, continue prompting your chosen chatbot until the output is short and clear enough to make reviewing it simple. We all know AI outputs need human oversight, but in practice it can be almost impossibly tempting to think “Ah, f—it” after the first page or two of accurate but very boring text.
The solution is to remove that temptation. Each prompt is designed to avoid workslop: the output should not be a ten thousands word document you’d need four coffees to make sense of. But if your LLM does produce an unwieldy output, follow up with this simple response:
Review your output and condense it without losing meaning or value. Add a clear summary with bullet points.
Second, set aside time for every task to actively engage with the AI output. Yes, these prompts can save you a lot of energy and accelerate the process. But they shouldn’t simply take the task off your plate.
For example, once you have AI-generated email copy, commit thirty minutes to editing it. Even if you do this using your chatbot to revise the content, it will most likely dramatically improve the output.
Finally, these prompts should ideally be used in order. It’s fine to skip some; you might not need help calibrating your discounts. But each is designed to make the next prompt more effective, giving you a system you can use over the next six weeks to maximise performance on the big weekend.
Your BFCM strategy does not exist in a vacuum: it should be informed by a nuanced view of your supply/demand dynamics, historical performance, and specific market. LLMs tend towards generic outputs; they need all that extra context to produce strategies and content that will help your specific brand make the most of BFCM.
The goal of this prompt is to create a single cohesive document that captures that context. Rather than running multiple analyses and reviews as discreet tasks, you will save a lot of time and reduce the potential for errors, oversights, and hallucinations. Because once you have this context document, you can attach it to other prompts.
Note: This prompt requires you to attach whatever contextual data you have. The exact inputs will vary: not every founder has access to all this information. But try to include as much data and information as possible, including:
Inventory data
Product pricing over the last nine months
2025 BFCM sales data
Customer reviews or testimonials
Ad performance for each platform you use
Insights about your competitors
However, you should only use data that you’re confident is accurate. You’re better off with less context that actually reflects reality.
The Prompt:
Act as an expert analyst for a UK D2C brand. Create a short, clear context document to inform my Black Friday/Cyber Monday (BFCM) strategy, covering marketing, pricing, conversion and fulfilment. If I haven't attached any files yet, ask me for them and wait before starting.
Follow these steps in order:
Review every file I've attached. Summarise what it tells you about my products, customers, margins, stock and past BFCM performance.
Using my competitor notes, plus web search if you have it, profile my 5 closest competitors: positioning, typical pricing and past BFCM promotions. Link a source for every competitor claim. If you can't find one, say so rather than guessing.
Note my operational limits for peak: stock cover for key products, reorder lead times, and anything in my data that suggests a fulfilment bottleneck.
List the gaps: important questions my data can't answer yet.
Format the output with clear headings so I can attach it to later prompts. Keep it under 1,500 words. Tag every claim as [My data], [Source: link] or [Assumption], and never present an assumption as fact.
Your BFCM discounts require a delicate balance between competitive offers and reasonable margins. You can’t afford to lose sales to cheaper competitors; you also can’t afford to sell at a loss or set unreasonable pricing expectations for the future.
This prompt works out the deepest discount each product can sustain. It uses your real costs, stock levels and expected cost-per-sale, and checks it against what comparable brands have offered. It then rolls that analysis up into the simplest structure your margins allow.
As we explained recently, shoppers overwhelmingly prefer a clear "X% off everything" deal to bundles and conditional offers. The item-level maths tells you what X can be, and which products (if any) need to sit outside it.
It also checks your reference prices. Inflated "was" prices damage trust with the returning customers who make up most BFCM sales, and under the DMCC Act they can also lead to legal action.
Note: Attach the context document from the previous prompt. If it doesn't already include them, you'll also need unit costs, your fulfilment and delivery cost per order, payment fees and your average ad cost per sale.
LLMs are also unreliable at arithmetic across large tables. The prompt asks the AI to show its working, but check the margins on your bestsellers in a spreadsheet before you commit to anything.
The Prompt:
Act as a D2C pricing analyst. Using the BFCM context document I've attached, recommend a Black Friday/Cyber Monday discount structure for my brand. If I haven't attached it yet, ask me for it and wait before starting.
Follow these steps in order:
For each product, calculate the deepest discount I can offer while keeping a healthy margin. Account for product cost, fulfilment and delivery costs, payment fees and expected advertising cost per sale. If a figure is missing, ask me for it rather than estimating.
Flag products where stock is too low to support extra demand, and products where I'm overstocked and a deeper discount would free up cash.
Compare your proposed discounts with competitors' BFCM pricing on similar products, using only sourced information.
Recommend the simplest structure my margins can support. Shoppers prefer one clear discount across everything over bundles or conditional deals, so only suggest exclusions or tiers where the numbers demand it.
Check every proposed "was" price against my actual selling prices in the attached data, and flag any that wouldn't be a genuine previous price.
Show your working for every margin calculation. Present the result as a table (product, current price, BFCM price, margin after discount, stock risk), followed by a summary of no more than 200 words explaining the structure. Tag every figure as [My data], [Source: link] or [Assumption].
With your context and pricing locked in, you can get to the fun bit. Most D2C founders enjoy the creative part, so this prompt is designed to leave that with you. It will offer you some ideas, but mostly it deals with the boring stuff around the advertising: email sequences, captions, and planning your advertising budget.
As we covered recently, ad prices spike in the final run-up, and most shoppers have planned their purchases by then, so the money works harder winning over fence-sitters than chasing cold audiences.
Note: Attach the context document, the output from the discount prompt, and three to five of your best-performing past emails and social posts.
The Prompt:
Act as a D2C marketing strategist. Using the context document and discount plan I've attached, create a focused Black Friday/Cyber Monday (BFCM) campaign for my brand. I've also attached examples of my past emails and social posts: match their tone of voice. If I haven't attached these yet, ask me for them and wait before starting.
Follow these steps in order:
Identify my 3 strongest angles for this year's BFCM, based on my reviews, product strengths and how my sale prices compare with the rest of the year. Shoppers are sceptical about Black Friday deals, so prioritise honesty and transparency over hype.
Draft a 4-email sequence covering the run-up, launch day, Cyber Monday and a final reminder. For each email, give 3 subject line options, preview text and body copy under 150 words.
If early access suits my brand, draft one extra email offering it only to past customers.
Suggest 5 social post concepts, each with a one-line creative brief and a caption under 50 words.
Recommend who to target with paid ads during BFCM week, prioritising people who already know my brand (site visitors, cart abandoners and email subscribers) over cold audiences.
Keep the whole plan under 1,200 words. Don't invent product claims, reviews or statistics: only use what's in my files, and flag anything I should check before publishing.
There's no point spending weeks building demand if shoppers bail at the checkout. Peak traffic magnifies every bit of friction on your product pages and checkout, and most of the fixes are small enough to finish before the big weekend.
This prompt runs the checks from our CRO guide with Zendbox CEO James Khoury. But it also checks for BFCM-specific friction and offers recommendations to improve conversions during the peak-week.
Note: An LLM can't walk through your checkout the way a customer does. On your phone, take screenshots of your bestselling product page and every step of the checkout, and attach them with your context document. The prompt tells the AI to stick to what it can see; if it starts speculating about pages you didn't share, ignore it.
Aim to have changes live by mid-November. You can then re-use the prompt to review the changes and make any final tweaks.
The Prompt:
Act as a conversion rate optimisation (CRO) specialist for D2C brands. Audit my product pages and checkout for friction before Black Friday/Cyber Monday (BFCM). I've attached my context document plus mobile screenshots of my bestselling product page and every checkout step. If I haven't attached these yet, ask me for them and wait before starting.
Check for these issues in order:
True cost: can shoppers see the full price, including delivery, before they reach the checkout?
Returns: is my returns policy visible on the product page and written in plain language?
Payment: am I missing methods my customers are likely to expect, such as Apple Pay, Google Pay, PayPal or buy now, pay later?
Delivery: are delivery speeds, next-day cut-off times and last Christmas delivery dates easy to find?
Price transparency: do my pages show how the BFCM price compares with my usual price, in plain text that shoppers and AI assistants can easily read?
Anything else that adds friction, such as unnecessary form fields, forced account creation or cluttered layouts.
For each issue, rate its severity (high, medium or low), explain in one sentence why it matters, and suggest a fix. Prioritise fixes I can make without a developer. Keep the output under 800 words and only comment on what you can actually see in my screenshots.
D2Cs shouldn’t see BFCM as a single sales push, but an opportunity to win long-term customers. The challenge is that new customers have set low pricing expectations; keeping them on the subscription or driving repeat purchases requires extensive follow-up.
This prompt builds the system that turns BFCM buyers into repeat customers. It covers the segments to set up in advance, a follow-up email sequence for each one, targeted offers that don't undercut your sale, and a checklist of the automations you'll need. If you sell subscriptions, it also plans how to keep BFCM subscribers beyond their discounted first order.
Note: Attach your context document and, ideally, a breakdown of your customer list showing first-time and returning buyers. Then build the segments and automations before BFCM starts. Setting them up retroactively for thousands of new customers in December is nobody's idea of festive fun.
UK marketing email rules also apply to your shiny new customers. You can usually email existing customers about similar products under the "soft opt-in", but only if you gave them a clear chance to opt out when they bought. The prompt flags segments where consent looks unclear, but check your email platform's records rather than relying on the AI's judgement.
The Prompt:
Act as a D2C retention specialist. Using the context document I've attached, build a post-purchase plan that turns my Black Friday/Cyber Monday (BFCM) buyers into repeat customers. If I haven't attached it yet, ask me for it and wait before starting.
Follow these steps in order:
Define 3 or 4 customer segments I should set up before BFCM, such as first-time buyers, returning customers and shoppers who only buy discounted items.
For each segment, outline a follow-up email sequence of up to 5 emails: delivery and how-to-use content first, then a review request, then a targeted offer. Time each email from the delivery date, not the order date.
Draft the full sequence for first-time buyers. Keep each email under 150 words, with 2 subject line options.
Recommend a follow-up offer for each segment that protects my margins, such as a replenishment reminder, a complementary product or a January offer. Never go deeper than my BFCM discount. If I sell subscriptions, include a plan to keep BFCM subscribers beyond their discounted first order.
List the automations and triggers I need to set up in my email platform as a simple checklist.
Keep the whole plan under 1,200 words. Only plan marketing emails for people who have opted in or qualify under the soft opt-in rule, and flag any segment where consent might be unclear.
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