20 AI Prompts for Paid Social

CopyI'm launching paid ads for [URL]. Here's what I know: - Product: [what you sell] - Price: [price point] - Target CPA: [what you can afford to pay per customer] - Monthly budget: [amount] - Platform: [Meta / TikTok / Pinterest / LinkedIn] Build me a complete campaign structure. Include: 1. Campaign objective and optimisation event 2. Number of ad sets and why 3. Targeting for each ad set (be specific — not "interest targeting") 4. Bid strategy with reasoning 5. Budget allocation across ad sets 6. 3 distinct creative angles with hook, body, CTA for each 7. What metrics to check on day 3, day 7, and day 14 8. What would make you kill this campaign vs. scale it Before you start: calculate whether my budget is sufficient to exit the learning phase at my target CPA. If it is not, say so and tell me the minimum budget that works.

CopyI sell [product/service] at [price] to [audience]. My monthly ad budget is [amount]. I'm considering [Meta / TikTok / Pinterest / LinkedIn / Google]. For each platform, tell me: 1. Whether my product category performs well there (with reasoning, not just "it depends") 2. Expected CPM range and what that means for my budget 3. Whether my budget is enough to exit the learning phase 4. The strongest and weakest part of each platform for my specific use case 5. Your recommended priority order — which platform first, which second, which to skip entirely Be direct. If a platform is wrong for my product, say so and say why. I'd rather hear it now than after spending $2,000.

CopyI'm building a Meta ads audience strategy for [product/service] at [price point]. My ideal customer is [brief description]. Go deeper than demographics. I need: 1. 5 psychographic profiles — what these people believe, what frustrates them, what they've already tried 2. For each profile: the Meta interest categories and behaviors that would reach them 3. Which of these 5 profiles I should test first and why (rank by likely conversion rate, not audience size) 4. Lookalike seed audiences I should build — what source data would produce the best lookalike and at what percentage 5. A broad targeting argument — make the case for running zero interest targeting with just age/geo and letting the pixel find the audience I'm running [campaign objective]. My pixel has [number] of conversion events in the last 28 days.

CopyI compete with [competitor 1], [competitor 2], and [competitor 3] in [category]. I've looked at their ads in [Meta Ad Library / TikTok Creative Center / LinkedIn Ad Library] and here's what I see: [Paste or describe 3-5 competitor ads — the hook, the format, the offer, the CTA] Analyze these ads as a media buyer: 1. What positioning angle is each competitor using? (price, quality, speed, identity, fear, aspiration) 2. What's the implied audience for each ad? 3. Where are the gaps — what angle is nobody using that could work? 4. Which of these ads is likely performing best and why? (based on creative principles, not guessing) 5. Write me 3 ad concepts that exploit the gaps you identified. Each should have a different hook, a different format (static, video, carousel), and a different emotional angle. Make them specific to my product: [brief description].

CopyThis ad copy is working for us on Meta: "[paste your winning ad copy]" It targets [audience] selling [product] at [price]. The primary text drives a [CTR of X%] and [conversion rate of Y%]. I need 5 variations that keep the same core angle but change the execution. For each variation: 1. A different opening hook (the first line people see before "See more") 2. The same core promise, reframed 3. A different proof point or specificity detail 4. A different CTA approach Rules: don't make them longer than the original. Don't add emojis if the original doesn't have them. Don't change the tone. I want variations, not rewrites. The goal is to test hooks while keeping the proven body structure.

CopyWrite a [15 / 30 / 60] second video ad script for [product] targeting [audience] on [TikTok / Instagram Reels]. Product: [what it does, key benefit, price] Goal: [purchases / signups / app installs] Tone: [e.g., direct and confident, not salesy / UGC casual / authority] Structure the script as: - HOOK (0-3 sec): 5 different opening hooks I can test. Each should work as a standalone scroll-stopper. No "Hey guys" or "Did you know" — those are dead. - BODY (3-20 sec): The core message. One version. Problem → product → proof → outcome. - CTA (last 3-5 sec): Clear, single action. No "link in bio" — give me a CTA that works in an ad format. For each hook, tell me what psychological trigger it uses (curiosity gap, pattern interrupt, social proof, identity, controversy, transformation). Mark which hook you'd test first and why.

CopyI need 5 static ad concepts for [product] on [platform]. Each ad will be [1080x1080 / 1080x1350 / 1000x1500]. Product: [what it is, key benefit, price] Audience: [who] Goal: [conversion event] Brand style: [minimal / bold / editorial / UGC-style — or paste your website URL] For each concept give me: 1. Visual description — what's in the image, layout, color palette, typography style 2. Headline text overlay (max 6 words) 3. Supporting text if needed (max 12 words) 4. Primary text (the copy that appears above the image in the feed) 5. Why this concept works — what makes someone stop scrolling Make each concept a genuinely different approach: different visual strategy, different emotional angle, different information hierarchy. I don't want 5 versions of the same ad with different headlines.

CopyI'm sending paid traffic from [platform] to this page: [URL] The ad promises: [paste your ad copy or describe the hook/offer] The audience is: [who] The conversion event is: [purchase / signup / lead form / add to cart] Current metrics: [CTR X%, conversion rate Y%, bounce rate Z%] Audit this landing page as a paid media specialist, not a web designer. I need: 1. Message match — does the page deliver what the ad promised in the first viewport? What's the gap? 2. Friction points — what's between the click and the conversion? Count the steps and identify where people drop 3. Trust signals — what's present and what's missing (reviews, logos, guarantees, specificity) 4. Mobile experience — is the CTA above the fold on mobile? Is the page fast? 5. The single highest-impact change I could make to improve conversion rate from paid traffic 6. A rewritten hero section (headline + subheadline + CTA) that maintains continuity with my ad copy

CopyMy Meta ads CPA has increased from [old CPA] to [new CPA] over the last [timeframe]. Here's my data: - Daily budget: [amount] - Campaign objective: [purchases / leads / etc.] - Number of ad sets: [number] - Current frequency: [number] - CTR (link): [%] - CPM: [amount] - Conversion rate (from click to purchase/lead): [%] - Pixel setup: [browser only / browser + CAPI / unsure] - Last significant edit: [what you changed and when] - Conversions per ad set per week: [number] Diagnose this in order: 1. Is my tracking clean? (based on what I described) 2. Is my budget mathematically sufficient for my CPA target? 3. Am I stuck in learning phase? 4. Is this creative fatigue? (check frequency + CTR trend) 5. Is this an offer/landing page problem? (check CTR vs. conversion rate) For the most likely root cause: tell me exactly what to do in Ads Manager. Column path, what to look for, what to change. Not theory — steps.

CopyMy Meta campaign launched [X days ago] and it's barely spending. Here's the situation: - Daily budget: [amount] - Bid strategy: [lowest cost / cost cap at $X / bid cap at $X] - Targeting: [broad / interests / lookalike / retargeting] - Audience size estimate: [from Ads Manager] - Campaign objective: [purchases / leads / etc.] - Number of ads in the ad set: [number] - Ad status: [active / in review / rejected] - Account history: [new account / established with spend history] - Any recent policy warnings or restrictions: [yes/no, details] Walk through every possible cause in order of likelihood: 1. Bid/budget too low for the auction 2. Audience too narrow 3. Ad review or policy issue 4. Account-level delivery restrictions 5. Campaign structure problem (competing ad sets, overlapping audiences) 6. Tracking or event configuration issue For each: how do I check it in Ads Manager, and what's the fix? Tell me which cause you think is most likely given what I described.

CopyI'm getting clicks but almost no conversions on [platform]. Here's my data: - CTR (link click): [%] - Landing page views as % of link clicks: [%] - Conversion rate (landing page view to conversion): [%] - Bounce rate from analytics: [%] - Average time on page: [seconds] - Platform reporting vs. analytics reporting: [do the numbers match?] - Pixel/CAPI status: [describe your setup] - Landing page URL: [URL] - What the ad promises: [the hook/offer in the ad] Diagnose in this order: 1. Is there a tracking gap? (compare link clicks → landing page views → analytics sessions → conversions) 2. Is the ad attracting the wrong audience? (high clicks but instant bounces = curiosity clicks, not intent) 3. Is the landing page failing? (good time on page but no conversion = friction or offer problem) 4. Is there a message mismatch between ad and page? Give me the single most likely cause and the specific fix. Then give me the second most likely cause in case the first fix doesn't work.

CopyHere's my paid social performance for this week vs. last week: [Paste your metrics — spend, impressions, CPM, clicks, CTR, conversions, CPA, ROAS, frequency, and any other metrics you track. Include both weeks for comparison.] Platform: [Meta / TikTok / Pinterest / LinkedIn] Goal: [target CPA / target ROAS] Monthly budget: [amount] Analyze this like a senior media buyer: 1. What changed and why? (don't just say "CPM went up" — tell me what likely caused it) 2. What's working that I should protect? (don't touch what's winning) 3. What's the biggest problem and what's the specific action? 4. Should I change budget this week? Up, down, or hold — with reasoning. 5. What creative action do I need to take? (new creative, kill underperformers, test new angles) 6. Any leading indicators of a problem coming next week? Be direct. I don't need encouragement, I need decisions.

CopyI want to scale my Meta campaign. Here's where I am: - Current daily spend: [amount] - Target daily spend: [amount] - Current CPA: [amount] - Maximum acceptable CPA: [amount] - Weeks at current performance: [number] - Conversions per ad set per week: [number] - Number of active ad sets: [number] - Number of active ads: [number] - Best performing ad: [describe it — format, hook, age] - Frequency on best audience: [number] Build me a week-by-week scaling plan. Include: 1. Budget increase schedule (how much, how often, which lever — CBO budget vs. ad set budget) 2. When to add new ad sets vs. scale existing ones 3. Creative pipeline — how many new ads do I need and when 4. The specific metrics that tell me to pause scaling 5. What to do if CPA spikes 30% after a budget increase 6. Whether I should use ASC (Advantage+ Shopping Campaigns) at this scale Don't tell me to "increase budget by 20% every 3 days" without explaining why that number and what to watch for.

CopyI need a creative testing framework for [platform]. Here's my situation: - Monthly ad spend: [amount] - Current number of active ads: [number] - How often I add new creative: [frequency] - Best performing ad format: [static / video / carousel / UGC] - Best performing angle: [describe what's working] - Product: [what you sell] - Audience: [who] Build me a testing framework: 1. Testing hierarchy — what do I test first, second, third? (format → hook → body → CTA → audience, or a different order — and why) 2. How many variations per test and what minimum spend before I call a winner 3. A 4-week testing calendar — what goes live each week 4. How to isolate variables so I actually learn something from each test 5. What "winning" means — which metric determines the winner (CTR, CPA, ROAS, or something else) and at what confidence level 6. What to do with losers — kill immediately, or is there useful signal in a losing ad? I want a system I can repeat every month, not a one-time plan.

CopyI'm running ads on multiple platforms. Here's my monthly performance: [For each platform, list: spend, conversions, CPA, ROAS, CPM, CTR, trend direction (improving / stable / declining)] Total monthly budget: [amount] Business goal: [maximize conversions at target CPA / maximize revenue / maximize ROAS] Target CPA: [amount] or Target ROAS: [number] Recommend a budget reallocation: 1. Where am I overspending relative to performance? 2. Where is there headroom to spend more before hitting diminishing returns? 3. What's the optimal split and how much improvement do you estimate? 4. Are any platforms not worth running at all at my total budget level? 5. What would change this recommendation? (e.g., "if TikTok CPA drops below $X, shift $Y there") Show your reasoning with the numbers. I need to be able to explain this to [my team / my client / my cofounder].

CopyHelp me calculate whether paid acquisition works for my business: - Average order value: [amount] - Cost of goods / fulfilment: [amount or % of AOV] - Gross margin: [% or amount] - Average customer purchases per year: [number] - Customer retention rate: [% or "I don't know"] - Subscription model: [yes/no — if yes: monthly price and average lifetime in months] - Current CPA on [platform]: [amount, or "I haven't started yet"] - Monthly ad budget: [amount] Calculate: 1. Maximum allowable CPA on first purchase (break-even) 2. Maximum allowable CPA including repeat purchases / LTV 3. Target CPA at [20% / 30%] profit margin after ad spend 4. Whether my current budget is sufficient to generate statistically meaningful results at this CPA 5. How many conversions per month I need to exit the learning phase on Meta 6. The minimum viable monthly budget for paid social to work for this business If the math doesn't work — if my margins can't support the typical CPAs on [platform] — tell me directly. I'd rather know before I spend.

CopyI need help understanding my true ad performance. Here's what I see: - Meta Ads Manager reports: [conversions and ROAS] - Google Analytics reports (from UTMs): [conversions and ROAS] - My backend / Shopify / CRM reports: [actual orders/leads and revenue] - Attribution window I'm using: [7-day click, 1-day view / other] - Am I running other channels? [Google Ads, email, organic, etc.] The numbers don't match. Help me: 1. Explain why each platform reports differently (view-through, click windows, last-touch vs. modeled) 2. Estimate the real contribution of my Meta ads based on the data discrepancy 3. Tell me which number I should use for decision-making and why 4. Whether I should change my attribution window setting and what the trade-off is 5. A simple framework I can use weekly to reconcile platform reporting with actual revenue I don't need a perfect attribution model. I need a practical one that helps me make better budget decisions.

CopyI'm launching a new product with zero ad data. No pixel history, no customer list, no conversion data. Product: [what it is, price, who it's for] Website: [URL] Total launch budget: [amount over what period] Platform: [Meta / TikTok / Pinterest / all] Do I have email subscribers or existing customers from another product? [yes — how many / no] Build me a cold-start launch plan: 1. Phase 1 (Week 1-2): What campaign structure generates learning data fastest? Which objective to start with if I don't have enough conversion volume for purchase optimisation? 2. Phase 2 (Week 3-4): How and when to shift from learning to optimising 3. Audience strategy with no lookalike seed — what do I target? 4. Creative for a product nobody has heard of — what angles work for cold launches? 5. The specific metrics and thresholds that tell me "this is working, invest more" vs. "this isn't working, pivot" 6. Common cold-start mistakes to avoid (I know "don't edit during learning" — give me the non-obvious ones)

CopyI need a [Black Friday / holiday / seasonal event] campaign plan for [product/store]. Regular period metrics: [CPA, ROAS, daily spend, CPM] Event dates: [when the sale/event starts and ends] Offer: [discount %, bundle, free shipping, etc.] Budget for the event period: [amount] Do I have a customer list for retargeting? [yes — size / no] Build a phased plan: 1. Pre-event (2 weeks before): What campaigns to run to build warm audiences and seed the pixel. Budget allocation. 2. Event launch (day 1-2): Campaign structure, bid strategy, budget. Should I use cost cap or highest volume during peak CPM periods? 3. Mid-event: How to read the data and adjust in a compressed timeline where waiting 7 days isn't an option 4. Post-event: How to transition back to evergreen without crashing performance 5. Creative strategy: How many assets do I need ready before the event? What formats and angles for urgency-driven buying? 6. CPM reality check: How much higher will CPMs be during this period and how does that change my target CPA math? I know CPMs spike during [event]. Factor that into every recommendation.

CopyWrite a monthly paid social report for [my client / my CMO / my cofounder]. They are [technical level: understands CPAs / only cares about revenue and profit / somewhere in between]. Here's this month's data: [Paste all metrics: spend, impressions, CPM, clicks, CTR, conversions, CPA, revenue, ROAS — for this month and last month. Break down by platform if running multiple.] Business context: [anything relevant — new product launch, seasonal period, budget change, creative refresh, etc.] Goal: [target CPA / ROAS / revenue target] Write the report in this structure: 1. Executive summary (3 sentences max — did we hit the goal, what was the biggest win, what's the biggest risk) 2. Performance overview (month-over-month comparison with context for every significant change) 3. What worked (specific campaigns, creatives, or audiences — name them) 4. What didn't work and what we did about it 5. Recommendations for next month (prioritized, with expected impact) 6. Budget recommendation for next month (increase / hold / decrease — with reasoning) Write it in plain language. No jargon without explanation. No vanity metrics. If impressions went up but conversions went down, lead with conversions.