ChatGPT Prompts for Google Ads

<context> Product/service: [PRODUCT] Target customer: [TARGET CUSTOMER] Primary goal: [GOAL] Monthly budget: [BUDGET] </context> <task> 1. Generate a keyword list for the product above, grouped into four intent buckets: transactional, commercial-investigation, navigational, and informational. 2. For each bucket provide 12-15 keywords using natural searcher phrasing, not internal jargon. 3. Flag which buckets deserve budget given the goal of [GOAL] (e.g. prioritize transactional + commercial for lead/sale goals). 4. Note 5 modifier patterns to scale the list (e.g. "best", "near me", "for [use case]", "[competitor] alternative", pricing terms). 5. Output as a table with columns: keyword, intent bucket, why it matters, suggested match type. </task>

<context> My product: [PRODUCT] My site: [YOUR URL] Known competitors: [COMPETITOR 1], [COMPETITOR 2], [COMPETITOR 3] Goal: [GOAL] </context> <task> 1. Infer the core value propositions each competitor likely bids on based on their positioning. 2. Build a keyword gap table: keywords competitors probably own vs. keywords my product can win on differentiation, price, or niche use case. 3. Identify 10 "wedge" keywords where a smaller advertiser can compete profitably (lower competition, high intent). 4. Suggest 5 competitor-conquesting keywords and the messaging angle each ad would need to justify the click. 5. Warn about any keywords likely to have brand-bidding restrictions or poor Quality Score for my landing page. </task>

<context> Product: [PRODUCT] Core head term: [HEAD KEYWORD] Ideal customer pain points: [PAIN POINTS] Goal: [GOAL] </context> <task> 1. Generate 40 long-tail keywords (3+ words) that expand the head term, organized by the job-to-be-done they imply. 2. For each, note the likely funnel stage (awareness, consideration, decision). 3. Highlight the 10 lowest-CPC, highest-conversion-probability terms for a limited [BUDGET]. 4. Group semantically similar long-tails into 4-6 themes ready to become ad groups. 5. Add 5 question-format keywords suited to a future informational/PMax asset. </task>

<context> Keyword list: [PASTE KEYWORDS] Budget: [BUDGET] Goal: [GOAL] Account maturity: [NEW ACCOUNT or HAS CONVERSION DATA] </context> <task> 1. Assign each keyword a recommended match type (exact, phrase, broad) based on intent confidence and budget. 2. Explain the trade-off: tighter control vs. broader reach, given my account maturity. 3. Recommend whether to lean on broad match + Smart Bidding or stay exact/phrase given conversion data availability. 4. Propose a match-type rollout sequence for the first 30 days. 5. List the negative keywords I must add before enabling any broad match to protect [BUDGET]. </task>

<context> Keyword list: [PASTE KEYWORDS] Product: [PRODUCT] Goal: [GOAL] </context> <task> 1. Cluster the keyword list into tightly themed ad groups (single keyword theme each) for strong relevance and Quality Score. 2. For each ad group, name it, list its keywords, and state the one searcher intent it serves. 3. Recommend a target of 5-15 keywords per ad group and split any oversized clusters. 4. For each ad group, draft the core promise its ads and landing page must deliver. 5. Output a structure ready to paste into Google Ads Editor. </task>

<context> Product: [PRODUCT] Product lines / services: [LIST] Geographies: [LOCATIONS] Monthly budget: [BUDGET] Goal: [GOAL] </context> <task> 1. Design a full account structure: campaigns by intent/product line, ad groups by keyword theme. 2. Recommend campaign types (Search, Performance Max, Shopping, Brand) and how to split budget across them given [BUDGET]. 3. Decide whether to segment campaigns by geography, device, or match type and justify each split. 4. Define a clear naming convention for campaigns and ad groups. 5. Output a tree diagram (text) of the recommended account hierarchy. </task>

<context> Brand name: [BRAND] Product: [PRODUCT] Competitors bidding on my brand: [YES/NO] Goal: [GOAL] Budget: [BUDGET] </context> <task> 1. Explain why brand and non-brand belong in separate campaigns and the metrics each should be judged on. 2. Recommend a budget allocation between brand and non-brand for my goal. 3. Decide whether to defend the brand campaign given competitor bidding behavior. 4. Propose bidding strategies for each (brand often Target Impression Share; non-brand often Target CPA/ROAS). 5. List the negatives to cross-apply so brand and non-brand do not cannibalize each other. </task>

<context> Goal: [GOAL] Conversion volume last 30 days: [NUMBER] Target CPA or ROAS: [TARGET] Budget: [BUDGET] </context> <task> 1. Recommend the best bidding strategy (Manual CPC, Maximize Clicks, Maximize Conversions, Target CPA, Target ROAS, Maximize Conversion Value) for my goal and data volume. 2. Explain the conversion-data threshold each strategy needs to perform. 3. Propose a migration path: which strategy to start with and when to graduate to a smarter one. 4. Warn about the learning-period volatility and how long to wait before judging results. 5. Set a realistic starting target given my historical data. </task>

<context> Product: [PRODUCT] Serviceable locations: [LOCATIONS] Customer behavior notes: [WHEN/WHERE THEY BUY] Budget: [BUDGET] Goal: [GOAL] </context> <task> 1. Recommend location-targeting settings (presence vs. presence-or-interest) and why. 2. Propose location bid adjustments based on likely value differences between regions. 3. Build a starting ad-schedule (dayparting) hypothesis aligned to when my customers convert. 4. Flag locations to exclude to protect [BUDGET] (low intent, out of service area). 5. Note which targeting decisions to revisit once conversion data accumulates rather than guessing now. </task>

<context> Product: [PRODUCT] Have product feed / Merchant Center: [YES/NO] Creative assets available: [IMAGES/VIDEO/TEXT] Budget: [BUDGET] Goal: [GOAL] </context> <task> 1. Recommend whether to run Performance Max, Search-only, or both in parallel for my situation. 2. Explain how PMax and Search interact and how to prevent PMax from eating my Search traffic. 3. List the asset groups and signals PMax needs to perform, and whether I can supply them. 4. Propose a budget split and a 30-60 day test design to compare the two. 5. Define guardrails (brand exclusions, account-level negatives) to keep PMax on-strategy. </task>

<context> Product: [PRODUCT] Key benefits: [BENEFITS] Differentiators: [WHAT MAKES IT UNIQUE] Offer/CTA: [OFFER] Target keyword theme: [THEME] Goal: [GOAL] </context> <task> 1. Write 15 distinct RSA headlines (max 30 characters each, count them) covering: benefit, feature, social proof, offer, urgency, and keyword-insertion variants. 2. Ensure at least 3 headlines include the target keyword theme for relevance/Quality Score. 3. Make headlines pinnable into position 1 (brand/offer) and position 2 (benefit) where appropriate, and label which to pin. 4. Avoid duplicate phrasing so Google can test true variety. 5. Output as a numbered list with character counts shown. </task>

<context> Product: [PRODUCT] Key benefits: [BENEFITS] Proof points: [STATS/AWARDS/REVIEWS] Offer/CTA: [OFFER] Goal: [GOAL] </context> <task> 1. Write 4 RSA descriptions (max 90 characters each, count them) that each lead with a benefit and end with a clear CTA. 2. Vary the angle across the four: outcome-focused, risk-reversal, proof-driven, and urgency. 3. Include the offer in at least one description and a proof point in another. 4. Keep language active and specific; no vague superlatives without proof. 5. Output as a numbered list with character counts shown. </task>

<context> Ad group keyword theme: [THEME] Keywords: [PASTE KEYWORDS] Product: [PRODUCT] Landing page promise: [PROMISE] Goal: [GOAL] </context> <task> 1. Write a complete RSA (15 headlines, 4 descriptions) tightly matched to this single keyword theme. 2. Mirror the searcher's exact language from the keywords in the headlines for relevance. 3. Ensure the ad promise matches the landing page promise so the scent stays consistent. 4. Flag any headline/description that would create a mismatch with the landing page. 5. Output the full ad plus a one-line note on expected Quality Score impact. </task>

<context> Product: [PRODUCT] Target customer: [TARGET CUSTOMER] Key benefits: [BENEFITS] Goal: [GOAL] </context> <task> 1. Write two complete RSAs: one leaning emotional (fear of missing out, status, relief) and one leaning rational (price, specs, time saved, ROI). 2. Keep both within RSA character limits and label each headline's angle. 3. Explain which audience segment each version likely resonates with. 4. Define how to A/B these (ad variation experiment) and what metric decides the winner. 5. Predict which is likely to win for my goal and why. </task>

<context> Industry: [INDUSTRY] Draft ad copy: [PASTE HEADLINES + DESCRIPTIONS] Claims made: [LIST CLAIMS] Goal: [GOAL] </context> <task> 1. Review the draft ad against common Google Ads policies (prohibited claims, superlatives needing proof, restricted-industry rules, trademark use). 2. Flag any phrase likely to trigger disapproval and explain why. 3. Rewrite each flagged line into a compliant version that keeps the persuasive intent. 4. Note any claims that require visible proof or disclaimers on the landing page. 5. Output a before/after table of flagged lines. </task>