Create Ads That Convert with AI-Powered Copy

Create a comprehensive ad account audit checklist for [platform — Google Ads / Facebook / LinkedIn / etc.]. My account currently runs [number] campaigns with a monthly spend of [amount]. I suspect there is wasted spend. Build an audit covering: (1) Account structure — campaign organization, ad group/set structure, naming conventions, (2) Targeting — audience overlap, negative keywords/exclusions, geographic settings, (3) Bidding — strategy appropriateness, bid caps, budget pacing, (4) Creative — ad fatigue indicators, variant diversity, format mix, (5) Tracking — conversion setup, attribution model, pixel health, (6) Quick wins — the 5 things I should check first that most commonly waste money. For each item, explain what to look for and what a red flag looks like.

Build a comprehensive negative keyword strategy for my Google Ads account. My business: [describe product/service]. My target keywords: [list main keywords]. Common irrelevant searches we probably get: [any you know about]. Create: (1) a campaign-level negative keyword list (broad terms that never apply to my business), (2) ad group-level negatives to prevent keyword cannibalization, (3) industry-specific negatives I might not have thought of, (4) a process for weekly search term review and negative keyword maintenance, and (5) negative keyword match type recommendations (broad vs phrase vs exact) for each term. Organize by category: competitors, job-seekers, students/free-seekers, wrong intent, wrong geography.

My ads are showing signs of fatigue. Platform: [platform]. The ads have been running for [duration]. Current metrics: CTR [X%] (was [Y%]), CPA [X] (was [Y]), frequency [X]. Help me: (1) confirm whether this is actually ad fatigue vs other issues (audience saturation, seasonal changes, competition), (2) calculate the optimal frequency cap I should have set, (3) create 3 refreshed versions of my best-performing ad that feel new but keep the winning elements, (4) suggest 2 completely new angles to test, (5) recommend a creative refresh schedule going forward (how often to rotate), and (6) design a creative testing pipeline so I always have fresh ads ready before fatigue hits.

My current ROAS is [X] and I need it to be [Y]. Platform: [platform]. Product price: [price]. Current CPA: [amount]. Current conversion rate: [percentage]. Funnel: [describe — click to landing page to purchase]. Help me model what needs to change: (1) calculate the maximum CPA I can afford at my target ROAS, (2) identify which lever has the most impact — lowering CPC, improving CTR, improving landing page conversion rate, or increasing AOV, (3) for each lever, suggest 3 specific tactics to improve it, (4) create a 30-60-90 day improvement plan with specific targets for each metric, and (5) identify the point at which scaling becomes unprofitable and what signals to watch for.

Help me choose the right attribution model for my business. My sales cycle: [length from first touch to purchase]. My channels: [list all marketing channels]. My customer journey typically looks like: [describe common paths]. My current attribution model: [last-click/first-click/linear/etc.]. Explain: (1) how my current model is likely misrepresenting performance, (2) which channels are probably getting too much credit and too little credit, (3) recommend the best attribution model for my business with rationale, (4) explain how changing the model will shift my budget allocation decisions, (5) suggest a practical implementation plan for the new model, and (6) recommend a testing approach to validate the new model (e.g., incrementality testing).

Create a TikTok advertising strategy for [product/service]. Target audience: [describe — age, interests, behaviors on TikTok]. Budget: [amount]. Design: (1) 3 native-feeling ad concepts that use TikTok trends without looking like ads (describe the visual concept, hook, and CTA for each), (2) recommended ad placements (In-Feed, TopView, Branded Hashtag Challenge, Spark Ads), (3) a creator partnership brief for 2 types of creators who would resonate with our audience, (4) sound/music strategy — trending sounds to consider, (5) ideal video lengths and pacing for each concept, and (6) a testing plan for the first month. The ads must not look like ads — TikTok users scroll past anything polished.

Help me set up a Google Performance Max campaign for [product/service]. Business type: [ecommerce/lead gen/local]. Website: [URL or describe]. Current Google Ads setup: [describe existing campaigns]. Create: (1) asset group strategy — how many groups, how to segment them, (2) complete text assets — 5 headlines (30 chars), 5 long headlines (90 chars), 5 descriptions (90 chars), (3) image and video asset recommendations (sizes and styles), (4) audience signal recommendations (custom segments, interests, demographics), (5) bid strategy recommendation with rationale, and (6) a monitoring plan for the first 4 weeks — what metrics to watch and when to intervene. Include common PMax pitfalls to avoid.

Create an Amazon Sponsored Products campaign strategy for [product]. Product category: [category]. Current BSR: [if known]. Price: [price]. Key competitors: [list]. Design: (1) keyword research — 20 high-intent keywords in exact, phrase, and broad match, (2) campaign structure — auto campaigns vs manual campaigns, how to organize them, (3) negative keyword strategy specific to Amazon, (4) bidding strategy — starting bids and adjustment rules, (5) a plan for harvesting converting search terms from auto campaigns, and (6) a 30-day optimization schedule. Include ACoS targets for launch phase vs mature phase.

Design a retargeting campaign using my email list. List size: [number]. List composition: [customers, leads, newsletter subscribers, etc.]. Platform: [Facebook/Google/LinkedIn]. I want to [goal — re-engage past customers, upsell, win back churned users, etc.]. Create: (1) audience segmentation strategy — how to split the list for different messaging, (2) ad creative for each segment (2 variants per segment), (3) exclusion strategy — who should NOT see these ads, (4) lookalike audience strategy built from the best segments, (5) frequency and duration recommendations, and (6) a measurement plan — what counts as success for each segment. Include privacy/compliance considerations for email list targeting.

Create a local advertising strategy for [type of local business] in [city/region]. Monthly budget: [amount]. Service area: [radius or neighborhoods]. Current marketing: [what you do now]. Design: (1) Google Local Services Ads setup and optimization tips, (2) Google Ads local campaign with geo-targeting settings and ad copy, (3) Facebook/Instagram ads targeting local audiences (radius targeting, local interests, community groups), (4) a review generation strategy that feeds into ad social proof, (5) local landing page recommendations — what to include for local SEO and ad relevance, and (6) tracking setup to measure calls, directions, and foot traffic from ads. Include budget split recommendations across platforms.

Create a weekly advertising performance report template for [platform(s)]. My key metrics: [list — spend, impressions, clicks, CTR, CPA, ROAS, conversions, etc.]. My stakeholders: [who reads this — CEO, marketing manager, client, etc.]. Design a report that includes: (1) executive summary — 3 sentences maximum covering performance, key wins, and concerns, (2) metric dashboard with week-over-week and month-over-month comparisons, (3) top and bottom performing campaigns/ad sets with analysis of why, (4) creative performance — which ads are winning and losing, (5) budget pacing — are we on track to hit monthly targets, (6) action items for next week, and (7) one insight or learning that applies beyond this week. Format it so a non-marketer can understand the story.

Help me write a campaign post-mortem. Campaign: [name/description]. Duration: [dates]. Budget: [total spend]. Goal: [what we wanted to achieve]. Results: [actual results vs targets]. Create a structured post-mortem: (1) Executive summary — did we hit the goal? By how much over or under? (2) What worked — top 3 wins with data to support each, (3) What did not work — top 3 underperformers with root cause analysis, (4) Surprises — anything unexpected that we should learn from, (5) Creative learnings — which messages, formats, and hooks resonated, (6) Audience learnings — which segments performed best, (7) Specific recommendations for the next campaign, and (8) A/B test results and their implications. Be honest about failures, not just celebratory about wins.

Help me build an ad spend forecast for the next [3/6/12] months. Current monthly spend: [amount]. Current CPA: [amount]. Current ROAS: [ratio]. Revenue goal: [target]. Growth rate desired: [percentage]. Create a forecasting model that includes: (1) projected monthly spend needed to hit revenue targets, (2) expected CPA changes as we scale (diminishing returns model), (3) platform-by-platform budget recommendations, (4) seasonal adjustment factors for [industry], (5) a conservative, moderate, and aggressive scenario, and (6) the breakeven ROAS at each spend level. Show the math so I can adjust assumptions. Flag the point where scaling becomes inefficient.

I am running ads on multiple platforms and need to compare performance fairly. My platforms and metrics: [List each platform with: spend, impressions, clicks, conversions, revenue] Analyze: (1) normalize metrics across platforms (different platforms report differently — help me compare apples to apples), (2) calculate true CPA, ROAS, and cost per impression for each, (3) identify which platform is most efficient for each funnel stage, (4) flag any attribution overlap (same conversion counted by multiple platforms), (5) recommend budget reallocation based on the data, and (6) suggest which metrics to prioritize for each platform based on its role in the funnel. Include caveats about comparing self-reported platform data.

Help me design an incrementality test for my advertising on [platform]. I want to measure whether my ads are actually driving incremental sales or just capturing demand that would have happened anyway. My current setup: [describe campaigns, targeting, spend]. Design: (1) explain what incrementality testing is and why it matters for my situation, (2) recommend a test methodology (geo-lift, ghost ads, holdout groups, etc.) appropriate for my budget and scale, (3) define the test and control groups, (4) calculate the minimum test duration and sample size needed, (5) list the metrics I should track during the test, and (6) explain how to interpret the results and what to do with the findings. Include what a good vs bad incrementality result looks like.