Black Friday GPT Prompts 2026: 75 Prompts for a Better Campaign

How to use this library without producing generic sale copy

A prompt cannot rescue an undefined offer. Before opening an AI tool, collect the product list, normal prices, approved sale prices, inventory or capacity, eligible regions, start and end times with time zones, shipping or delivery conditions, exclusions, returns, brand voice, audience evidence, and legal or compliance requirements. When a fact is missing, the model should mark it missing rather than improvise.

Replace every bracketed field with your information. Give the model examples of approved writing and a list of phrases the brand avoids. Ask for a rationale or evidence map before final copy when the task contains claims. This makes review faster because a person can see which input supports each sentence.

Use the prompts as stages, not a single giant instruction. Start with campaign diagnosis, then offer design, then channel execution, then quality checks. Keep approved facts in a source-of-truth document and paste the relevant section into each task. Do not let a later creative prompt quietly change the price or eligibility decided earlier.

Every generated output remains a draft. Check price, dates, product availability, comparative claims, testimonials, guarantees, accessibility, and links. Send regulated, contractual, or legally sensitive language through the normal expert review. The model can organize evidence and surface questions; it cannot approve the campaign.

1. Create one campaign fact sheet with prices, dates, products, regions, exclusions, inventory constraints, and approved claims.
2. Choose a prompt for one decision, provide the fact sheet, and require the model to label assumptions.
3. Review strategy before copy, and copy before design or scheduling.
4. Test links, prices, timing, personalization, accessibility, and mobile layout with a person.
5. Keep the final approved version outside the chat so later generations cannot overwrite it.

Prompts 1-15: strategy, audience, and campaign architecture

These prompts turn scattered plans into explicit decisions. They are most useful in September and October, before discounts and channel deadlines create pressure. Keep the output analytical until the campaign owner approves the direction.

Act as a retail campaign strategist. Review this campaign brief: [PASTE]. Separate confirmed facts, assumptions, unresolved decisions, risky claims, missing operational details, and questions requiring an owner. Do not write promotional copy. Return a prioritized evidence checklist with owner and deadline columns.

Using only this customer evidence [PASTE], identify the three audience segments most likely to benefit from the offer. For each, describe the job they need done, purchase barrier, proof required, useful channel, and message to avoid. Flag conclusions not supported by evidence.

Turn this product, audience, and commercial goal into five possible campaign positions. Each position must name the customer, concrete problem, offer role, and reason to believe. Score clarity, differentiation, evidence, and brand fit. Recommend one and explain the trade-off.

Design a three-level offer ladder from these approved products and margins [PASTE]. Include entry, core, and premium choices; who each serves; value without the discount; final price; operational risk; and likely cannibalization. Do not invent bundles, bonuses, or savings.

Build a Black Friday 2026 campaign calendar from [START DATE] through [END DATE]. Include preparation, preview, launch, reminder, final-hours, Cyber Monday, support, fulfillment, and post-sale review. Assign owner, input, output, dependency, approval, and fallback for each milestone.

Define a distinct role for email, paid search, organic social, affiliates, website, in-product messaging, SMS, and customer support in this campaign. Prevent every channel from repeating the same copy. Use this audience, budget, and consent context: [PASTE].

Develop a fair treatment plan for existing customers when new customers receive this promotion: [PASTE]. Consider upgrades, renewals, credits, loyalty recognition, support scripts, and customers who purchased recently. Identify cost and trust trade-offs without promising an unapproved remedy.

Create a Black Friday campaign for a product that will not reduce price. Use service, education, implementation help, useful bundles, or limited capacity only when truthful and approved. Inputs: [PRODUCT VALUE, MARGIN, CAPACITY, AUDIENCE]. Avoid fake scarcity and anti-sale posturing.

Analyze these competitor campaign pages [PASTE TEXT OR NOTES]. Create a matrix of audience, promise, proof, offer structure, exclusions, urgency, and weaknesses. Do not copy phrases. Recommend white-space positions our verified evidence can support.

Adapt this campaign strategy for [REGIONS]. Compare currency, timing, shipping or access, holidays, language, payment behavior, regulations, and support coverage. Produce shared global elements and region-specific decisions. Mark everything requiring local verification.

Create conservative, expected, and high-demand scenarios using this inventory or service capacity [PASTE]. For each, estimate exposure by channel, pause triggers, waitlist behavior, substitution rules, support load, and customer communication. Do not fabricate demand forecasts.

Build a risk register for this Black Friday campaign. Cover pricing errors, overselling, broken codes, site performance, misleading savings, accessibility, consent, fraud, refunds, support overload, fulfillment, affiliate copy, and AI-generated factual errors. Add likelihood, impact, owner, prevention, detection, and response.

Translate this campaign goal [PASTE] into a measurement plan. Include leading indicators, commercial outcomes, margin, new versus returning customers, refund or cancellation rate, support cost, cohort quality, and post-sale retention. Define each metric and the decision it informs.

Assume this campaign failed six weeks after Black Friday. Using the plan [PASTE], write ten plausible causes across offer, message, operations, channel, technology, customer trust, and measurement. For each, name an early signal and a prevention action we can take now.

Turn this campaign research [PASTE] into a one-page approval brief: customer problem, proposed offer, why now, financial guardrails, evidence, channels, timeline, operational readiness, risks, unresolved decisions, and explicit approvals requested. Keep facts separate from recommendations.

Prompts 16-30: pricing, bundles, and merchandising

This group helps shape and explain an offer without inventing prices or using a percentage that cannot be reproduced. Supply approved commercial data and have finance or the responsible owner verify the result.

From these normal and promotional prices [PASTE], calculate absolute saving, percentage saving, first-year cost, monthly equivalent, and renewal difference. State the comparison basis beside every result. Flag mismatched plans, billing periods, currencies, capacities, or taxes. Show formulas.

Audit each was/now claim in this offer table [PASTE]. Ask whether the comparison price is the normal price for the identical plan and period. Identify inflated anchors, ordinary annual discounts presented as seasonal savings, and claims that need evidence.

Evaluate this proposed bundle [PASTE] from the buyer's perspective. Identify which items work together, which inflate perceived value, setup dependencies, overlapping features, and customer types who should not buy it. Recommend keep, remove, or optional for every item.

Generate ten clear names for these three offer tiers [PASTE BENEFITS]. Names must communicate increasing scope without shaming the entry tier or using vague superlatives. Explain what expectation each name creates and flag any that could mislead.

Create a buyer-facing comparison table from this approved plan data [PASTE]. Rows should reflect decisions customers actually make. Include price, billing, capacity, core features, exclusions, renewal, and best-fit user. Write unknown when a fact is absent.

Order these sale products [PASTE] for a collection page. Balance popularity, margin, availability, audience intent, and decision ease. Explain the first eight placements and propose filters that reduce overwhelm. Do not label an item best without criteria.

Review this good-better-best structure [PASTE]. Test whether each step adds meaningful value, whether the middle option is genuinely suitable, and whether any feature is artificially withheld. Suggest a fairer structure while preserving the commercial target.

Design a clear journey when a free trial and annual Black Friday offer coexist. Specify eligibility, trial end, charge timing, remaining credits, cancellation, and messages at each step. Identify points where a customer might misunderstand or be charged unexpectedly.

Create an upgrade decision framework for current customers on [PLAN]. Compare staying, upgrading now, and upgrading later. Use these approved prices and entitlements [PASTE]. Account for unused prepaid time, proration, renewal, migration, and features the customer actually uses.

Draft an information architecture for explaining a discounted first year and full-price renewal. Put the sale amount, term, renewal basis, cancellation, and eligibility where a buyer will see them before the CTA. Provide concise mobile and desktop versions.

Turn these coupon rules [PASTE] into an unambiguous specification for customers, support, affiliates, and engineering. Cover capitalization, stacking, eligible products, regions, customers, uses, dates with time zones, error messages, and fallback. Surface contradictions.

Plan how this offer should work for gifts or team seats. Address recipient activation, ownership, start date, duplicate accounts, seat transfer, refunds, renewal responsibility, privacy, and support. Use only these approved capabilities: [PASTE].

Create a customer-first substitution policy for products or capacity likely to sell out. Define equivalent criteria, consent, price handling, communication, refund choice, and when to stop promotion. Inputs: [INVENTORY, ALTERNATIVES, CONSTRAINTS].

Using this offer and product evidence [PASTE], write responses to ten likely price objections. Acknowledge when the product is not a fit, compare total value without attacking competitors, and avoid invented ROI or pressure. Include a short and detailed response.

Score this offer page [PASTE] from 1 to 5 on identity, eligibility, price basis, savings proof, included capacity, exclusions, timing, renewal, cancellation, support, and accessibility. Quote the evidence for each score and provide a prioritized repair list.

Prompts 31-45: landing pages, email, ads, and social

Use these after the offer fact sheet is approved. The instructions deliberately reduce exaggerated language and require channel-specific work instead of one generic paragraph pasted everywhere.

Create a landing-page outline from this approved offer brief [PASTE]. Lead with customer outcome, then offer facts, proof, plan comparison, fit and non-fit, steps, terms, FAQs, and CTA. Map every factual claim to the input. Mark proof gaps.

Write five above-the-fold options for [AUDIENCE] using only [APPROVED FACTS]. Each needs a concrete H1, one explanatory sentence, price or offer summary, primary CTA, and compact terms line. Avoid biggest, ultimate, revolutionary, and false urgency.

Write a compact Black Friday module that can sit on an existing product page without replacing the evergreen explanation. Include exact price, comparison basis, eligibility, end time and zone, renewal, CTA, and a link label for full terms.

Draft a launch email to [SEGMENT]. Use this fact sheet and voice guide [PASTE]. Structure: useful subject, preview text, why the product matters, exact offer, three evidence-based benefits, who it fits, terms, CTA. Provide plain-text and HTML-copy versions.

Draft an email to existing customers about [OFFER]. Acknowledge their relationship, explain whether they qualify, show any approved loyalty or upgrade option, and provide a support path. Do not make a new-customer offer sound like a reward for loyalty.

Create one abandoned-cart email that helps rather than pressures. Restate the selected product, exact cost and renewal, answer the top three likely uncertainties, link to support and terms, and mention the verified end time once. Do not imply inventory scarcity unless supplied.

Write a final-day email using the confirmed end time [TIME AND ZONE]. Focus on who should act and who should skip. Repeat the exact offer and renewal. Avoid countdown language beyond the factual deadline. Include a fallback sentence if availability changes.

Generate twelve paid-search ad variations grouped by intent: brand, category, problem, comparison. Stay within [PLATFORM LIMITS]. Use only approved prices and claims. Add a matching landing-page promise and negative-keyword ideas for each group.

Plan seven social posts with different jobs: education, customer problem, product demonstration, proof, offer explanation, FAQ, and deadline. For each give format, hook, evidence, caption outline, visual brief, CTA, and comment-response risk. Inputs: [PASTE].

Write a 30-second vertical video script demonstrating [REAL WORKFLOW]. Show the before state, product action, observable result, exact offer, and terms. Include shot list, on-screen text, voiceover, captions, and a claim-check column.

Create a mandatory affiliate campaign brief. Include approved claims, prohibited claims, exact prices, comparison basis, eligibility, dates and zones, disclosure language, required destinations, brand assets, update process, and how to correct stale posts.

Turn this offer into flexible creator talking points rather than a scripted endorsement. Separate personal-experience statements from vendor facts, require clear commission or sponsorship disclosure, and list claims the creator must not make without their own evidence.

Write ten concise homepage promotion strips for [OFFER]. Each must fit [CHARACTER LIMIT], communicate product plus benefit, state the offer without hiding conditions, and use a specific CTA. Provide a mobile version and accessible aria-label.

Create customer-facing FAQs from these support tickets, offer terms, and product facts [PASTE]. Prioritize eligibility, price, renewal, cancellation, current customers, credits, regions, refunds, access, and support. Do not create an answer when evidence is missing.

Compare these email, ad, social, affiliate, and landing-page drafts [PASTE]. Build a discrepancy table for price, dates, eligibility, product names, benefits, exclusions, urgency, renewal, and CTA destination. Recommend one canonical wording for each fact.

Prompts 46-60: service, QA, and operational readiness

Campaign quality is often determined after someone clicks. These prompts prepare the people, systems, and fallback language required when codes fail, inventory changes, or buyers have legitimate questions.

Create a support knowledge-base outline from the final offer terms [PASTE]. Include diagnostic questions, exact answers, escalation conditions, refund boundary, screenshots needed, and change log. Separate customer-visible articles from internal procedures.

Draft concise support macros for code failure, ineligible plan, existing customer, duplicate purchase, charge timing, renewal, cancellation, refund request, sold-out product, and regional restriction. Use empathy, verified facts, next action, and escalation when evidence is unclear.

Write a checkout QA plan for [OFFER]. Cover devices, browsers, currencies, taxes, guest and signed-in users, new and current customers, valid and invalid codes, stacking, seat counts, confirmation, analytics, accessibility, cancellation, and failure recovery.

Given this campaign URL inventory [PASTE], create a test matrix for source URL, final destination, redirect count, status, mobile behavior, tracking parameters, page offer, region, and owner. Flag links that could expose a stale or conflicting promotion.

Define an analytics event plan from impression through renewal intent. Include event name, trigger, required properties, privacy boundary, deduplication, QA method, and business question. Avoid collecting personal data that is not needed for the decision.

Create a response playbook for a code that fails after launch. Include detection, pause criteria, owner, technical checks, customer message, affiliate update, support macro, make-good approval, evidence preservation, resolution notice, and retrospective.

Create a decision tree for a displayed price that differs from checkout. Distinguish tax, currency, stale cache, wrong plan, eligibility, configuration error, and genuine price change. Include when to pause advertising and who can approve public wording.

Plan a degraded campaign experience if the main landing page or checkout becomes slow. Define essential text, lightweight assets, queue behavior, status message, alternate support route, analytics, and criteria to reduce paid traffic. Do not promise availability you cannot confirm.

Audit this campaign page specification [PASTE] for keyboard access, focus, headings, link purpose, contrast, text resizing, motion, image alternatives, captions, error messages, form labels, tables, and mobile zoom. Return issues by severity with test steps.

Build a pre-send email checklist covering audience and exclusions, subject and preview, sender, offer facts, links, tracking, personalization fallbacks, accessibility, dark mode, plain text, mobile, unsubscribe, consent, schedule, time zone, and seed-list proof.

Convert this promotion into a fulfillment handoff. State products, variants, forecast ranges, cutoffs, packing or digital delivery, substitutions, staffing, carrier or infrastructure dependencies, customer updates, failure thresholds, and daily reporting.

Brainstorm misuse scenarios for this offer without giving instructions for exploitation. Cover account farming, code sharing, chargebacks, reseller abuse, automated purchases, identity mismatch, and support manipulation. Suggest proportionate detection and customer-safe controls.

Create a campaign change-log template. Fields: timestamp, requested change, reason, affected facts and channels, evidence, approver, implementer, URLs or assets updated, QA result, affiliate notice, support notice, and rollback. Add severity levels.

Design a 15-minute daily campaign brief: sales and margin, conversion, errors, support themes, refunds, availability, channel anomalies, affiliate compliance, customer sentiment, decisions needed, owner, deadline, and changes since yesterday. Keep vanity metrics secondary.

Run a go/no-go assessment from these artifacts [PASTE]. Score offer approval, price configuration, inventory, landing page, checkout, analytics, accessibility, support, fulfillment, legal review, affiliate readiness, incident response, and ownership. No-go any critical unknown.

Prompts 61-75: analysis, learning, and next-year preparation

The campaign is not finished when the timer ends. These prompts help distinguish durable customers from discounted volume, document mistakes, and preserve evidence for the next seasonal decision.

Turn this campaign dataset [PASTE] into a decision narrative. Separate volume, revenue, margin, new and returning customers, channel contribution, refunds, support cost, and retention signals. Explain uncertainty and avoid attributing causation from correlation alone.

Compare Black Friday buyers with a comparable non-sale cohort using [DATA]. Examine product mix, order value, activation, usage, support, refunds, cancellation, repeat purchase, and margin. State selection limitations and what cannot yet be concluded.

Evaluate each offer or bundle using units sold, contribution margin, attachment, cannibalization, refund rate, support load, activation, and follow-on behavior. Classify grow, repair, retire, or insufficient evidence, and explain the decision threshold.

Review this channel report [PASTE]. Identify where last-click reporting may over-credit branded search, email, affiliates, or retargeting. Propose practical tests and additional evidence needed before reallocating budget. Do not invent incremental lift.

Map each major message to its placements and results. Control for audience and channel where possible. Identify messages that attracted qualified buyers, messages that created support confusion, and claims needing stronger evidence. Recommend three future tests.

Cluster these campaign questions and tickets [PASTE] by underlying uncertainty, not wording. Quantify frequency if data is complete, identify the page or message that should have answered each cluster, and draft a repair backlog.

Analyze these refund and cancellation reasons [PASTE]. Separate product mismatch, misunderstood offer, technical failure, accidental renewal, capacity limits, quality, support, and fraud. Do not blame customers. Recommend product, copy, checkout, and service changes.

Compare affiliates on approved-claim compliance, disclosure, audience fit, conversion, refund rate, support burden, new-customer quality, and stale-content correction. Avoid ranking solely by gross revenue. Identify partners requiring coaching, pause, or expansion.

Facilitate a blameless retrospective from this timeline [PASTE]. Organize what helped, what failed, contributing system conditions, customer impact, detection, response, and corrective actions. Assign an owner and verification method to every action.

Review campaign incidents and performance data across page speed, checkout, codes, analytics, email, integrations, cache, mobile, and accessibility. Distinguish observed evidence from hypotheses. Recommend fixes ranked by customer impact and recurrence.

Audit every campaign URL and asset after the sale. Classify update to evergreen, mark expired, redirect, retain as historical evidence, or remove from navigation. Preserve useful comparisons and avoid leaving active-looking expired claims.

Create a 2027 baseline record from final 2026 evidence. Save normal price, sale price, exact plan, capacity, dates, eligibility, renewal, checkout notes, source URLs, screenshots, and discrepancies. Separate facts from lessons and predictions.

Plan a post-purchase sequence that helps customers receive value rather than pushing another sale. Include activation, first useful outcome, capacity guidance, support, renewal transparency, feedback timing, and an easy exit. Segment by product and experience.

Create a ten-slide readout from this verified campaign evidence [PASTE]. Cover objective, strategy, offer, operations, commercial result, customer quality, incidents, learning, actions, and next decision. Put definitions and caveats beside each headline metric.

Convert the approved plans, results, and retrospective [PASTE] into a reusable playbook. Include roles, inputs, decision gates, calendars, templates, QA, incident response, evidence standards, metrics, archive locations, and sections that must be revalidated next year.

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