AI Ad Copy Generation
Effortless, high-performing Google Ads Ad Copies for your entire product feed.
THE CHALLENGE OF SCALING ECOMMERCE PPC
Handling ad campaigns for thousands of SKUs is a continuous challenge. Keeping ad copy relevant, engaging, and optimized at scale is nearly impossible without the right approach.
Struggling to personalize ad messaging?
In a traditional way, crafting personalized and engaging text for each variation takes hours or even a day. And the results often lead to generic, underperforming ads that fail to connect with the right audience.
Maintaining a strong Google Quality Score
Google rewards well-structured, relevant ads with better Quality Scores. These scores directly affect CPC and ad placement. But successful ads require ongoing tuning based on keyword relevance, engagement, and landing page experience. Doing this manually isn’t a scalable choice.
Reducing CPC via effective ad copies
Poorly optimized ads lead to low engagement and higher CPCs. Without a system to generate and test high-performing variations, advertisers lose their competitive edge. This drives up acquisition costs and cuts into campaign profitability.
WHAT WE DO
Our solution automates ad creation at broad levels, generating high-performing Google Ads copy for thousands of products effortlessly.
Our AI-powered solution generates:
- Headlines + descriptions per search term
- Ad copy tailored to each product’s key selling points
- Keyword-optimized, Google-compliant messaging
HOW WE DO IT
1) Extracting Search Terms from Google Ads
We pull real-time search term data directly from the Google Ads API with key metrics like clicks, impressions, and search volume. This ensures ad copy is based on actual user behavior, making it highly relevant and performance-driven.
2) Filter and Enrich Keywords Using Product Feed
The extracted search terms are filtered and enriched with product data, including:
- Product titles & descriptions: Match keywords with real product content.
- Product brand & ratings: Identify high-performing brands for better targeting.
Custom Search Engine (CSE) matching: Cross-checks landing and category pages for text relevance, ensuring strong keyword-to-page alignment.
3) Generate Keyword-Campaign-Adgroup-Ad Copy Sheet
- Ad Group and Campaign Structuring: We generate ad groups and campaigns based on the Equal Links Sheet, product categories, and keyword clustering.
- Ad Copy: Content is extracted from Equal Links Sheet URLs or, if unavailable, from the product database. OpenAI generates headlines and descriptions per term.
- Then, a structured dataset ready for ad creation.
Generated sheets organize ad groups, campaigns, and corresponding ad copies for seamless ad creation.
4) AI-Powered Ad Copy Generation
Using OpenAI’s Retrieval-Augmented Generation (RAG), we generate the desired number of headlines and descriptions per search term by pulling content from:
- The most relevant landing page (if available)
- Product titles & descriptions from the database
- Google Autosuggest Data (if applicable)
This entire process ensures that every ad is optimized for higher Quality Scores, lower CPC, and better conversions.
Cost Calculator for AI-Generated Google Ad Copies
Curious about the cost of generating customized, high-quality ad copy at scale? Our AI Ad Copy Cost Calculator provides a clear, instant estimate to help you budget effectively for your ad campaigns. Perfect for enterprises requiring thousands of ad variations!
Cost Estimations for Generating 1000 Responsive Search Ads
| Model | Tokens
A token is a piece of text, like a word or punctuation. As a rule of thumb, one token is about 4 characters, or roughly ¾ of a word, so 100 tokens equals about 75 words.
|
Cost | ||||
|---|---|---|---|---|---|---|
| Input | Output | Total | Input | Output | Total | |
| gpt-3.5-turbo-0125 | 24.030 | 2.280 | 26.310 | $ 0,01 | $ 0,00 | $ 0,02 |
| gpt-4 | 24.030 | 2.280 | 26.310 | $ 0,72 | $ 0,14 | $ 0,86 |
| gpt-4-turbo | 24.030 | 2.280 | 26.310 | $ 0,24 | $ 0,07 | $ 0,31 |
| gpt-4o | 23.760 | 2.150 | 25.910 | $ 0,06 | $ 0,02 | $ 0,08 |
| gpt-4o-mini | 23.760 | 2.150 | 25.910 | $ 0,0036 | $ 0,0013 | $ 0,0048 |
- Would you like to get started with AI for PPC Use Cases? Here is our DOUGLAS Case Study.
- Need support to build your own AI PPC solution? Contact us!
KEY FEATURES
- Retrieval-Augmented Generation (RAG): Creates intent-driven ad copy by pulling data from top-ranking content sources.
- Domain-Specific Insights: Analyzes product titles, descriptions, and website content to craft engaging, conversion-focused messaging.
- Comprehensive Output for PPC Optimization: Generates multiple headlines and descriptions per search term, allowing teams to test and refine ad performance.
- Enhanced Ad Relevance: Aligns ad copy with user intent, leading to higher engagement and better conversion rates.
- Improved Quality Scores: Well-structured, relevant ads help boost Quality Scores, lowering CPC and increasing ad visibility.
- Operational Efficiency & Scalability: Automates repetitive tasks, freeing PPC teams to focus on strategy and analysis.
BENEFITS OF AI AD COPY GENERATION
- Reduction in cost-per-click through higher Quality Scores
- Faster campaign launches for seasonal promotions and new products
- Higher click-through rates with intent-matched messaging
- Scale to an unlimited number of SKUs without increasing your team size
- Continuous optimization based on performance data
- Consistent brand voice across thousands of variations
FAQ
What is an Open AI Token?
Whenever you interact with an Open AI LLM you are consuming tokens for sending and receiving words. As a rule of thumb 100 Tokens are needed for around 75 words.
What does RAG stand for?
RAG stands for Retrieval-Augmented-Generation. Before the LLM is answering a question or solving a task you can use various knowledge resources to look up information for that context and hand it over to the LLM to make use of it.
Which Problem is solved by using RAG?
The generated results are way more accurate. Especially when you deal with recent topics that are not part of the model training so far. The problem of “Hallucinations” is minimized. The LLM can be considered as a writing assistant that puts all facts together you are handing over which gives you a lot of control.
Which knowledge could be used for Ad Copy Generation in PPC?
A good starting point is the available website content. Let’s say you already have a running Google Ads Account structure with keywords pointing to a relevant final url. A straightforward approach would be to save the text content of the website and send it to the LLM before creating a specific ad copy for a given keyword. If you have a product feed available with detailed product descriptions this is another great resource for creating highly relevant ad copies.