Friends, I'm doing a manual comparison of SGE vs traditional SERPs and am seeing that many of our SERPs no longer have 10 standard organic positions. For example, this is what the results look like for outdoor rocking chairs: - Brand filters - Shopping carousel, 8 - Organic shopping, 8  - Organic 1-2 - PAA - Organic #3 - Image pack, 4 + scroll (3 / 4  are product images w/shopping) - Buying Guide  - Explore brands - Videos - Organic 4-6 - Organic shopping, 8  - Organic 7-8 - Deals But the only SEO tool I have is ahrefs and it doesn't allow for bulk analysis and their scraper only shows a limited number of rich features so it's really not a complete or accurate picture. I'm hoping there may be a better way to automate extracting these SERPs at scale and then maybe I can schlepp it into chatgpt to play around with the data. Any ideas?

Hello, everybody! I wanted to share a Python script I've created to automate the extraction of Core Web Vitals metrics for multiple URLs. This script is designed to help you gather essential metrics for both Desktop and Mobile from the Lighthouse API and save them in an Excel file. The cool thing is that the script has an asynchronous function, allowing it to run all of the URLs almost simultaneously, making it a very fast script. Here is the link to the script, which includes a detailed guide on how it works: https://github.com/sundios/SEO-Lighthouse-Multiple-URLs Here's how the script works: Basic Usage: - You'll need to obtain access to the Lighthouse API. - Edit the list of URLs that you want to analyze. What I've implemented in my agency is as follows: - Custom URL List: I customized the URL list to include the most important URLs from each category of our clients' websites. - Data Storage in Google Sheets: I configured the script to save the data into a Google Sheets file. You can find a helpful tutorial for this process here. - Scheduled Execution with Google Cloud Function: I set up a Google Cloud Function to run the script automatically every day. While I plan to create a tutorial on how to do this, there are existing tutorials on YouTube that can guide you through the process. - Dashboard in Looker Studio: To visualize and analyze the metrics, I created a dashboard in Looker Studio. - Alerts via Microsoft Power Automate: I established a workflow in Microsoft Power Automate to send me an email notification whenever a score experiences a significant decrease. I hope it can make your life easier by automating this type of analysis. If you have any doubts, feel free to ask me! :)

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Had a great chat with Tom from SEOWind today. He is building a comprehensive AI content platform for SEO. Here are my 10 takeaways: - AI Content Tools: Most AI content tools rely heavily on OpenAI's pre-trained knowledge. This means they often overlook crucial information found on Search Engine Results Pages (SERPs). - SEOwind's Unique Approach: SEOwind stands out because it follows a natural SEO content process: research, SERP insights, briefing, and page creation. In contrast, many other tools merely prompt ChatGPT without conducting research. - ChatGPT's Limitations: ChatGPT has no memory and starts from scratch with each prompt. It repeatedly feeds the entire conversation back to itself, which can lead to issues when it hits token limits. (Tom conducted extensive research on ChatGPT's architecture.) - Extensive Prompts: Tom's prompts can be as long as 7,000 words to generate a 3,000-word article output. Using a vectorizing approach to create higher-quality output. - AI Limitations: All AI struggles to replicate personal experiences effectively. - AI Internal Linking Tools: Currently, there are no reliable AI tools for internal linking. - AI Development on GitHub: Tom mentioned an AI tool on GitHub that simulates a development team, assigning roles and goals to AI agents. He's working on a similar approach for SEOwind's future. - The Future of Content Writers: Content writers may evolve into hybrid editors collaborating with a team of AI writers. - AI and Jobs: We both agree that AI is both fascinating and concerning, particularly in terms of job security. It's not AI alone but individuals skilled in AI who pose potential job risks to others. If you have any questions for Tom, drop them in the comments! 😁