Artificial intelligence (AI) is rapidly transforming the landscape of digital advertising, offering PPC (Pay-Per-Click) professionals powerful tools to streamline workflows from campaign planning to reporting. This curated collection of AI prompt ideas and templates is designed to help you leverage generative AI, making tasks like crafting negative keyword lists, generating ad copy variations, and summarizing client reports faster and more efficient. By offloading routine tasks to AI, marketers can dedicate more time to strategic thinking and creative execution.

With the right prompt, essential PPC tasks become significantly easier. This list of example prompts, curated by the team at Search Engine Journal, is built for you to use and adapt to your specific needs. We will be updating this resource regularly.

Crafting Effective AI Prompts

These prompt templates serve as excellent starting points to help you scale your PPC workflows. To create an effective prompt, ensure you incorporate the following elements:

  • Clear Input: Assign the AI a specific role, be precise about the task, and clearly outline the data you are providing.
  • Context: Offer background information so the AI understands your overall goal, not just the immediate question.
  • Constraints: Set guardrails or structure (e.g., outlines, rulebooks, style guides) to ensure the result aligns with your expectations and avoids off-target answers.

For all prompts listed below, remember to insert your unique information where indicated, such as [INSERT ...].

Keyword Research & Planning

1. Long-Tail Keyword Expander

This prompt helps generate themed keyword groups from a seed keyword to build a robust campaign structure. The AI will expand your seed keyword into 20–30 related long-tail variations, categorized by search intent (informational, commercial, transactional). It will incorporate modifiers like "best," "cheap," "near me," and "how to," prioritizing keywords with strong buyer intent for paid search. The output will group similar keywords into 3–5 themed ad groups.

Input needed: Seed keyword (e.g., "running shoes"), target location, and campaign objective (e.g., "sales").

Expected output: A table detailing Ad Group Theme, Keyword List, and Estimated Intent.

2. Match Type Strategy Recommender

Assign the most appropriate match type to each keyword based on your control and volume goals. The AI will recommend whether each keyword should use exact, phrase, or broad match, considering competitiveness, intent clarity, and budget. For high-intent terms, it will favor exact or phrase match. For discovery, it will suggest broad match with tight negatives. The output will also explain the trade-off for each choice.

Input needed: A list of 10–15 keywords, your campaign goal (e.g., "conversions"), and your monthly budget range.

Expected output: A table with columns for Keyword, Match Type, and Reasoning.

3. Negative Keyword Starter List

Prevent wasted ad spend by identifying irrelevant search terms upfront. This prompt generates 15–25 negative keywords that would attract non-buyers or irrelevant clicks. It includes common wasteful terms like "free," "jobs," "DIY," "tutorial," competitor names, and terms indicating wrong intent. The AI will explain why each negative keyword matters for your campaign and recommend whether it should be phrase match or exact match. Note that terms like "free" or "cheap" may be part of valid high-intent searches (e.g., "free shipping"), so negative keywords should be added selectively.

Input needed: Your core product/service, industry, and the keywords you are currently bidding on.

Expected output: A three-column list: Negative Keyword, Match Type, and Reason to Exclude.

Ad Copywriting & Testing

4. RSA Asset Generator (Google Ads)

Create diverse responsive search ad (RSA) assets optimized for testing. The AI will write 10 unique headlines (max 30 characters) and four descriptions (max 90 characters) that blend emotional hooks, feature callouts, urgency, and social proof. It will include at least one headline with a number or statistic and ensure assets can combine in any order without repetition or contradiction. Google Ads recommends providing at least five unique headlines to achieve "Good" Ad Strength.

Input needed: Product/service name, top 3 benefits or features, and your primary call-to-action (CTA).

Expected output: Two sections: Headlines (numbered 1–10) and Descriptions (A–D).

5. RSA Asset Mixer (Google Ads)

Transform features, benefits, and CTAs into testable responsive search ad components. This prompt generates 12 headlines and four descriptions by mixing and matching your provided benefits, features, and CTAs. It varies the messaging style across emotional appeal, logical reasoning, urgency, and social proof, keeping all copy within Google Ads character limits and ensuring seamless combinations. Google Ads recommends at least five unique headlines for "Good" Ad Strength.

Input needed: A list of 3–5 product benefits, 3–5 product features, and 2–3 preferred CTAs.

Expected output: Two sections: Headlines (numbered 1–12) and Descriptions (A–D).

6. Ad Angle Brainstorming Tool

Discover fresh messaging angles to test against your current ads. The AI will generate six alternative ad angles, such as scarcity, authority, pain/solution, comparison, guarantee, or transformation. For each angle, it will write one sample headline and explain when to use it, avoiding repetition of your current ad's approach.

Input needed: Your top-performing ad copy, product or service details, and target audience pain points.

Expected output: A table with columns for Angle Type, Sample Headline, and Best Use Case.

Audiences & Targeting

7. Audience Segment Hypothesis Builder

Draft testable audience segments with a clear conversion rationale. This prompt proposes 4–6 audience segments (e.g., in-market, affinity, custom intent, remarketing) with clear definitions. For each, it explains why they are likely to convert and suggests initial bid adjustments (raise/lower/neutral). It prioritizes audiences with historical relevance if mentioned.

Input needed: Your product or service offering, known customer demographics or behaviors, and your campaign goal (e.g., "purchase").

Expected output: A table with columns for Audience Name, Definition, Why It Converts, and Bid Adjustment.

8. Keyword-To-Funnel Stage Mapper

Align keywords with buyer journey stages for smarter targeting. The AI will categorize each keyword as cold (informational), warm (comparison/research), or hot (ready to buy). The output will recommend which keywords deserve higher bids, tighter targeting, or special landing pages, and flag any keywords that may need remarketing support.

Input needed: A list of 10–20 performing keywords, your typical customer journey (e.g., awareness → decision), and your conversion goal (e.g., "sale").

Expected output: A table with columns for Keyword, Funnel Stage, Bidding Priority, and Notes.

Bidding & Budget

9. Bidding Strategy Selector

Recommend the right automated or manual bidding strategy. This prompt suggests whether to use manual CPC, maximize clicks, target CPA, target ROAS, or maximize conversions. It explains which strategy fits based on data maturity and control needs, and includes one caution or condition for each option. Note that Target CPA and Target ROAS perform best with approximately 30–50 recent conversions.

Input needed: Your campaign goal (e.g., "conversions"), daily or weekly conversion numbers, and your budget size and flexibility.

Expected output: A table with columns for Strategy, Best For, and Caution.

10. Campaign Budget Allocator

Split a fixed budget across campaigns based on priority and performance. The AI will allocate budget percentages to each campaign based on historical ROI, strategic priority, and growth potential. It recommends higher spend for proven converters and testing budgets for new initiatives, justifying each split with a concise sentence. Remember that Google may exceed daily budgets by up to ~15% due to daily pacing rules, and consider shared budgets or portfolio bidding strategies.

Input needed: Total monthly budget, a list of 3–6 campaigns with their goals, and past ROAS or CPA per campaign (if available).

Expected output: A table with columns for Campaign, Budget %, Amount, and Reasoning.

Search Query Mining

11. Search Term Negative Identifier

Clean up search query reports by flagging wasteful terms. This prompt reviews search terms and identifies 5–10 that should be added as negatives. It looks for irrelevant intent, low commercial value, or terms triggering ads incorrectly, explaining why each term wastes spend and suggesting the correct match type (phrase or exact negative).

Input needed: A list of 20–30 recent search terms, performance data (cost and conversion, if available), and your campaign objective.

Expected output: A table with columns for Search Term, Add as Negative?, Reason, and Match Type.

12. High-Opportunity Query Promoter

Find search queries worth promoting to dedicated keywords or ad groups. The AI will identify 3–5 search queries with strong click-through rates or conversion rates that are not yet standalone keywords. The output will recommend promoting them to exact or phrase match with custom ad copy and estimate the potential impact if given more budget and ad relevance.

Input needed: A search term report with impressions and conversions, your current keyword list, and budget availability.

Expected output: A table with columns for Query, Current Performance, Promotion Recommendation, and Expected Lift.

Landing Pages & CRO

13. Ad-To-Page Relevance Checker

Spot mismatches between ad promises and landing page content. This prompt compares the ad's main claim with the landing page headline, imagery, and CTA, flagging any gaps where the page does not deliver on the ad's promise. The output suggests 2–3 quick fixes to improve message match and reduce bounce rate. Note: AI cannot visit URLs directly, so you must paste the landing page text or a summary.

Input needed: Ad headline and description, landing page URL or summary, and your primary conversion goal.

Expected output: A report with a summary paragraph and a bulleted list of gaps and fixes.

14. Landing Page CTA Optimizer

Create clear, compelling CTAs aligned with each ad angle. The AI will propose three CTA options that match the ad's tone and promise. One option will emphasize urgency, one will reduce friction, and one will reinforce value. CTAs will be kept short (2–5 words) and action-oriented.

Input needed: Ad messaging or angle, offer type (product/service), desired action (e.g., "sign up"), and landing page details (text, summary, or screenshot).

Expected output: A numbered list with CTA text and a brief explanation for each.

Reporting & Insights

15. Client-Friendly Performance Snapshot

Turn raw metrics into a one-slide summary clients can easily understand. This prompt writes a 3–4 sentence narrative explaining overall performance, highlighting wins and flags. The summary includes one insight about what is working and one recommendation for next steps, keeping the language simple and avoiding jargon.

Input needed: Current metrics (CTR, CPC, conversion rate, CPA), spend data (budget spent and conversions delivered), and a comparison period (e.g., "last month").

Expected output: A report with a short paragraph summary and 2–3 key takeaway bullets.

16. Metric Change Explainer

Translate performance shifts into clear, actionable insights. The AI writes 3–5 sentences explaining why a specific metric changed, considering factors like competition, bid adjustments, ad fatigue, seasonality, targeting shifts, or platform changes (e.g., Google algorithm updates, iOS 14.5 on Meta). The explanation concludes with one recommended action to sustain gains or fix declines.

Input needed: The metric that changed (e.g., "conversions"), before and after values, and context (seasonality, changes made, external factors).

Expected output: A short paragraph formatted for reporting or client email.

Competitive Analysis

17. Competitor Ad Messaging Scanner

Summarize competitor ad strategies to find differentiation opportunities. This prompt analyzes competitor ads for recurring themes, offers, CTAs, and emotional triggers. The output identifies 2–3 messaging gaps or angles competitors are not using and suggests how to position your ads differently while staying relevant to searcher intent.

Input needed: 3–5 competitor ad examples (headlines and descriptions), your product or service, and your unique selling points (USPs).

Expected output: A report with a summary paragraph and a bulleted list of differentiation ideas.

18. Gaps & Differentiators Finder

Identify unique value propositions that competitors are not claiming. The AI lists 4–6 ad angles, offers, or value propositions that your brand can own but competitors are not emphasizing. The focus is on authentic differentiators like guarantees, speed, customization, support quality, or niche expertise, with an explanation of why each gap matters to buyers.

Input needed: Your product/service features and benefits, themes from competitor ads or websites, and target audience needs or pain points.

Expected output: A table with columns for Differentiator, Why Competitors Miss It, and Buyer Appeal.

Advanced PPC Prompts

19. Enhanced PPC Keyword Research Suggestion Prompt

This advanced prompt template is designed to help a PPC keyword research specialist build a comprehensive and high-performing keyword strategy. It guides the AI through keyword discovery and expansion (brand, generic, related, competitor terms), match type strategy with reasoning, negative keyword generation across common categories, and campaign organization into tight, focused ad groups. It emphasizes customer-centric thinking, long-tail keywords, and ongoing optimization.

Input needed: Detailed campaign context including product/service, landing page URL, target audience, campaign goal, monthly budget, and geographic target.

Expected output: Structured lists for keyword categories, a table for match type strategy, categorized negative keywords, and a proposed campaign/ad group structure, all with detailed reasoning.

20. Enhanced Funnel-Based Ad Copy Generator

This advanced prompt template instructs a PPC copywriting expert to create high-performing ad copy for responsive search ads (Google Ads), Meta ads (Facebook/Instagram), and LinkedIn ads, specifically optimized for different customer journey stages (top, middle, bottom of funnel). It provides detailed requirements for each platform and funnel stage, along with core copywriting principles like user benefits, keyword integration, social proof, and friction removal.

Input needed: Product/service description, target audience, desired funnel stage(s), platform(s), unique differentiators, keywords (for Google Ads), and any relevant context (goals, seasonality, promotions).

Expected output: Ad copy tailored for the specified platform(s) and funnel stage(s), including headlines, descriptions, primary text, and CTA buttons, adhering to character limits and best practices, along with an expected Ad Strength for Google Ads.

Keep Refining Your Prompts As Models Evolve

Good prompts are not static; they require continuous refinement. As AI models evolve, so too will their interpretation of your instructions. Brent Csutoras, an in-house LLM expert at Search Engine Journal, emphasizes that effective prompting today is less about phrasing and more about understanding how the machine interprets your instructions.

"As much as this might feel like a human… you’re talking to a machine. The problem you have is that you are asking a prediction engine to give you the answer it thinks you want based on some rules that you’ve given it."

Csutoras also warns that prompt structure significantly impacts model behavior:

"The way your prompt is structured and the way you type it actually has a massive effect on how your output’s going to come. It will skip certain things and ignore certain things, if it’s not written well."

Therefore, treat prompts as living documents. After revising an output, ask your model where your prompt caused confusion and how it would rewrite the instructions to prevent future issues. This feedback loop allows the model to help refine the instructions you provide, with Csutoras himself updating his prompts monthly.

To ensure your prompts remain sharp and reliable, here is his advice for auditing and improving them:

How To Audit And Improve Your Prompts

  • Cross-model Testing: Run prompts across various models like ChatGPT, Claude, and others. Ask each model what it would change about your prompt.
  • Self-Critique Loops: Ask the AI how it interpreted your instructions, which steps it skipped, and where it found conflicts.
  • Priority Mapping: Have the AI list the steps in your prompt in the order it believes they matter most. This reveals how it "reads" your request.
  • Project-Based Prompting with Artifacts: Build structured projects where instructions, templates, tone guides, product documentation, and datasets are predefined. Models maintain consistency by drawing from the same controlled materials every time.
  • Data Filtering: Remove emotional language or subjective tone from research inputs before adding them to a project. Cleaner data produces cleaner output.
  • Continuous Improvement: Regularly ask the AI to adjust your instructions based on your edits. Update your prompt monthly to keep it evolving with your workflow.

We will be updating this list on a regular basis with more prompt ideas and examples to make your PPC more efficient.

Disclaimer: These PPC-focused prompts are not designed to be "one-size-fits-all" because results generated may contain inaccuracies or incomplete data. Always fact-check your outputs against primary sources, and review for compliance and accuracy.

More Resources:

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