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ChatGPT for SEO
ChatGPT version that is specifically tailored to SEO content creation.
Prompt Chains
Run complex prompt chains in ChatGPT to get perfectly SEO optimized content.
Google Scraper
Scrape content, PAA or HTML like H2 or titles from Google into your prompts.
Prompt Library
Large prompt library that covers all kind of SEO use cases.
Pricing
Learn more about our future plans and why SEOTraffic is free.
Use Cases
SEO Content
Create SEO content effortlessly by using prompt chains that scrape Google.
Auto Publish
Use our WP plugin to automatically publish content directly from ChatGPT into Wordpress.
Analyse Content
Use our SEO analysis prompts to analyse existing content in order to get optimization suggestions.
Repurpose Content
Use our prompt chains to repurpose content, e.g. for social media posts.
Browser Agents
Use and refine prompt chains that can operate your browser and create agents that perform redundant tasks like link outreach.
Replace staff
Replace some of your staff members with ChatGPT or browser agents or make your staff much more efficient.
Embed Knowledge
Use our integrated vector database to embed unique company knowledge into prompt chains. Useful to create chatbots.
Learn
Tutorials
Explore our tutorials and learn how to work with SEOTraffic.
Youtube
Check out Youtube for bite sized videos that show you how to operate SEOTraffic.
Facebook Group
Be part of a community of SEOTraffic users, ask questions and get help.
Chatbot Helper
Unsure how to use SEOTraffic? Talk with an AI chatbot that tells you how to use SEOTraffic.
Scraper
Scrape content from url
Example Prompt: <<Step1>> {{url:https://seotraffic.ai}} <<Step2>>Summarize the received parts.
Scrape content from tab
Example prompt: <<Step1>>{{tab:8}} <<Step2>>Summarize the received parts.
Scrape html from url
Example prompt: <<Step1>>{{h2}} from {{urlsource:https://cnn.com}}
Scrape html from tab
Example prompt: <<Step1>>{{title}} from {{tabsource:4}}
Scrape PAA from Google
Example prompt: <<Step1>> {{paa:keyword}} <<Step2>> Extract all questions from the received parts.
Scrape top1 for keyword
Example prompt: <<Step1>>{{google1:keyword}} <<Step2>> Summarize the received parts.
Extract within top1 html for keyword
Example prompt: <<Step1>> {{h2}} from {{googlesource1:keyword}} <<Step2>> Generate headlines similar to the received parts.
Pricing
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Extract HTML from TAB
Explore Random Prompts
Write an extensive service
description for a local client in
markdown format.
Local Service Description
Pretend you own {{Name of company}} in {{location}} and you are writing a service page for {{service that the company offers}}. Use the following structure: 1. SEO optimized headline 2. SEO optimized description of the service 3. 100 word Company introduction 4. Compelling tag line 5. Write out the following as bulletin list - including Free Estimates - Over 500 5-Star Reviews - 100% Satisfaction Guarantee - Honest Up-Front Pricing By The Job 6. 100 words about how the company helps its clients 7. 100 words about why a client should choose this company 8. 100 words about being known in the area 9. 5 FAQ questions and answers for the topic of the page. Write using the format: Markdown.
Extract parts of the HTML code of
a given URL. Then counts how
often the element was found.
HTML Extractor [not functional]
Extract the complete html content in between the opening html tag and the closing html tag of the target element "<h2>" from: <!DOCTYPE html> <html> <head> <title>Example Page</title> </head> <body> <h2>Heading 1</h2> <h2>Heading 2</h2> <h2>Heading 3</h2> <h2>Heading 4</h2> <h2>Heading 5</h2> </body> </html> Just answer with a list of the complete html code that you find between the opening and closing html tags of the target element. Do not reference BeautifulSoup or any python library. Do not explain how such an extraction could work. Do not answer with just the target element. Just do the actual extraction. Then always write "Amount of elements found:" followed by the amount of how many times you found the complete html content in between the opening html tag and the closing html tag of the target element.
Myth-Busting FW
Myth-Busting FW
Using the 'Myth-Busting' framework, please write a marketing campaign outline that identifies and debunks common misconceptions or myths about our {{product/service}}. Provide {{facts}} and {{evidence}} to support your claims.
Review Analysis from TAB
Review Analysis from TAB
<<Step1>> {{tab}} <<Step2>> Find all reviews within the received parts and extract the most frequently used positive sentiment based words. Find all reviews within the received parts and extract the most frequently used negative sentiment based words. Find all reviews within the received parts and extract the most frequently used keywords and entities.
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