By Ruslan Galba | Tegra
These three prompts are pulled directly from our AI workflow system. We use variations of these across 20+ brands. Each one replaces a specific manual task that used to eat hours of our team's time every week.
Copy each prompt. Paste it into Claude or ChatGPT. Swap in your own data where indicated. Run it.
You'll get a feel for what structured AI prompting looks like vs. the generic "write me some headlines" approach that produces garbage.
Most people paste "write me 15 Google Ads headlines for [product]" and get 15 vague, interchangeable headlines back. That's not an AI workflow. That's asking a question.
These prompts work because they include context. Each one primes the AI with specific data about your account, your competitors, and your customers before asking it to produce anything.
The quality of AI output is 100% determined by the quality of context you provide. These three prompts demonstrate that principle.
What it replaces: 2-3 hours of manual search term report analysis What it produces: Negative keyword candidates with estimated waste, grouped by theme
Copy this prompt and paste your CSV data where indicated:
You are a Google Ads specialist analyzing search term data. I'm going to give you a search term report. Your job is to identify wasted spend and recommend negative keywords.
MY ACCOUNT CONTEXT:
- Business type: [YOUR BUSINESS TYPE - e.g., "e-commerce selling organic skincare"]
- Target CPA: $[YOUR TARGET CPA]
- Products/services: [LIST YOUR MAIN PRODUCTS]
- Branded terms to protect: [YOUR BRAND NAME AND VARIATIONS]
INSTRUCTIONS:
1. Identify every search term that has:
a. Zero conversions AND spent more than $[YOUR TARGET CPA x 2]
b. CTR below 1.5% with 100+ impressions (poor relevance signal)
c. Informational intent ("how to," "what is," "why") in commercial campaigns
2. Group the waste terms by theme (e.g., "competitor brand terms," "informational queries," "irrelevant category," "geographic mismatch")
3. For each group, recommend:
- Specific negative keywords to add (phrase match or exact match)
- Whether to add at campaign level or account level
- Estimated monthly waste if these terms continue
4. Flag any search terms that are converting well but might be undervalued (low CPA, low spend - these are expansion opportunities)
5. Calculate total estimated monthly waste across all flagged terms
FORMAT: Output as a table with columns: Search Term | Cost | Conversions | Issue | Recommended Negative | Match Type | Level (Campaign/Account)
SEARCH TERM DATA:
[PASTE YOUR CSV DATA HERE]
AI will return a categorized list of waste terms with specific negative keyword recommendations. On an average account, this finds $500-5,000/month in wasted spend.
Critical step after running: Don't blindly add every recommendation. Review each negative keyword to make sure it won't block legitimate queries. AI occasionally flags terms that look irrelevant but actually convert at low volume.
AI compresses this into a structured output in under a minute. You spend 10-15 minutes reviewing and implementing.
What it replaces: 1-2 hours of manual competitor ad research What it produces: Messaging angle breakdown, positioning gaps, counter-headline ideas
You are a competitive intelligence analyst for Google Ads. I'm going to give you ad copy from my top competitors. Analyze their messaging strategy and identify positioning gaps.
MY BRAND CONTEXT:
- My brand: [YOUR BRAND NAME]
- My primary value proposition: [WHAT MAKES YOU DIFFERENT]
- My category: [YOUR PRODUCT CATEGORY]
- My strongest proof point: [YOUR BEST METRIC - e.g., "4.8 stars from 2,300 reviews" or "12 years in business"]
COMPETITOR ADS:
[For each competitor, paste their ads in this format:]
COMPETITOR: [Name]
Ad 1: [Headline] | [Description] | Running approximately [X months]
Ad 2: [Headline] | [Description] | Running approximately [X months]
[Continue for 5-10 ads per competitor]
ANALYSIS INSTRUCTIONS:
1. For each competitor, classify their ads across these 10 messaging angles:
- Price/Value
- Quality/Premium
- Urgency/Scarcity
- Social Proof
- Authority/Expertise
- Convenience/Ease
- Guarantee/Trust
- Free Offer
- Comparison
- Newness/Innovation
Show the percentage of their ads using each angle.
2. Build a messaging matrix showing all competitors side by side.
3. Identify:
- RED OCEAN angles (above 40% average usage - oversaturated)
- CONTESTED angles (15-40% usage)
- BLUE OCEAN angles (below 15% usage - positioning opportunities)
4. For the top Blue Ocean opportunity, generate 5 counter-positioning headlines that:
- Are under 30 characters each
- Would NOT sound like something any of these competitors would say
- Include at least one specific, verifiable claim
- Avoid these banned words: Premium, Innovative, Experience, Discover, Unlock, Elevate, Transform
5. For each counter-headline, explain the "shadow weakness" of the competitor angle it counters.
FORMAT: Start with the messaging matrix, then gaps analysis, then counter-headlines with reasoning.
You'll get a clear picture of what messaging territory is crowded, what's open, and specific headline ideas that occupy the open territory.
The most valuable output is usually the Blue Ocean identification. Most brands compete on the same 2-3 angles as everyone else without realizing there are entire positioning territories nobody has claimed.
What it replaces: 1-2 hours of writing + editing ad copy What it produces: 25 scored headline candidates for one RSA, pre-filtered for AI tells
You are a Google Ads copywriter who has been trained to avoid AI-sounding copy. Generate headline candidates for a Responsive Search Ad, then self-score each one.
KEYWORD CLUSTER:
[LIST YOUR 3-5 TARGET KEYWORDS]
BRAND CONTEXT:
- Brand: [YOUR BRAND NAME]
- Product: [SPECIFIC PRODUCT OR SERVICE]
- Primary differentiator: [WHAT MAKES YOU DIFFERENT]
- Offer: [CURRENT OFFER - e.g., "Free shipping over $49" or "30-day trial"]
- Strongest proof: [YOUR BEST SPECIFIC METRIC]
CUSTOMER LANGUAGE (from real reviews/forums):
- "[PASTE A CUSTOMER QUOTE ABOUT THEIR PROBLEM]"
- "[PASTE ANOTHER CUSTOMER QUOTE]"
- "[PASTE A THIRD CUSTOMER QUOTE]"
TOP-PERFORMING EXISTING HEADLINES (if available):
- "[YOUR BEST HEADLINE]" - CTR: X%
- "[YOUR SECOND BEST]" - CTR: X%
GENERATION RULES:
1. Generate 25 headline candidates. Each must be under 30 characters.
2. Mix three emotional approaches:
- First-Person Pain (articulate the reader's problem): 8 headlines
- Specific Moment (capture a situation they recognize): 8 headlines
- Emotional Contradiction (tension between two truths): 9 headlines
3. HARD RULES - auto-fail any headline that:
- Uses em dashes
- Contains these words: Experience, Discover, Unlock, Elevate, Transform, Unleash, Premium (without evidence), Innovative, World-class
- Uses "Your journey to..." or "Take X to the next level" or "Everything you need"
- Could be said by any competitor with zero modification
4. For each headline, self-score on a 100-point rubric:
- Visualizable (can you picture it?): 0 or 10
- Falsifiable (could it be proven wrong?): 0 or 10
- Unique (would a competitor NOT say this?): 0 or 10
- Relevance to keyword cluster: 0-20
- Clarity in under 30 chars: 0-15
- Proofability (claims backed by evidence): 0-15
- Emotional punch: 0-10
- Customer language used: 0-10
5. Sort by score descending. Mark the top 15 as SELECTED and the bottom 10 as CUT.
FORMAT: Table with columns: # | Headline | Chars | Approach | Score | Status (SELECTED/CUT) | Reasoning
You'll get 25 headlines with scores. The top 15 become your RSA candidates. The scoring makes it easy to see why some work and others don't.
After running this prompt:
Each prompt follows the same structure that makes AI useful for ads:
Context first. Every prompt starts with brand-specific information. This is the single biggest factor in output quality.
Structured instructions. Not "write headlines" but "generate 25 candidates following these specific rules, then score each one against this rubric." Structure prevents generic output.
Built-in quality gates. The banned word list, the scoring rubric, the character limits. These constraints force AI to work harder and produce better results.
Human validation required. Every prompt includes a "what to do after" section. AI generates. You validate. The combination is what works.
| Task | Manual Time | With These Prompts |
|---|---|---|
| Search term waste analysis | 2-3 hours | 15 minutes (including review) |
| Competitor ad analysis | 1-2 hours | 20 minutes (including setup) |
| RSA headline generation | 1-2 hours | 15 minutes (including validation) |
| Total | 4-7 hours | 50 minutes |
That's 3-6 hours back every week. Multiply by 4 weeks and you've recovered 12-24 hours per month - on just three tasks.
These three prompts are the starting point. The complete AI workflow system includes:
The Full Prompt Library:
The Context Stack:
The Anti-AI Copy Filter:
The 8-Minute Weekly Audit:
These 3 prompts demonstrate the principle. The Google Ads AI Agentic System ($4,997+) gives you the full toolkit:
The quick start gets you moving. The full system builds the competitive advantage.
Get the Google Ads AI Agentic System at tegra.co/store/google-ads-ai-agentic-system