I have extensive experience with a variety of content data analysis tools, including Google Analytics, SEMRush, Ahrefs, etc. But sometimes they don’t to exactly what I want them to, or I have a weird idea I’d like to try out, so I dip into Python to build something. Here are a few examples.
GA4 Landing Page Comparison Analyzer
I created this script to make it easier to find blog posts with significant rises or drops in key metrics over time. An interactive version of this script is available for all to use here. No coding skills are required to use it, see the video above for details.
Twitter Bot Using Generative AI and Sentiment Analysis
Back in the days before generative AI was good, I used GPT-2, beautifulSoup and the vaderSentiment library to scrape comments from the website Pinkbike.com, analyze them for “extreme” sentiment, and then train GPT-2 to generate comments based on that data set. Resulting comments – the funny ones – were added to a queue to post to Twitter. I wrote a blog post about building this and what I learned.
A quick script I wrote to make it easy to compare keyword counts in a text file against another file which had a list of suggested keywords and suggested mention counts. (There are many good marketing tools that do this in a more user-friendly way, and I would recommend using them rather than this. But I didn’t have access to any of them at the time I wrote this).
As part of a previous job, I wanted to track the number of job posts on Indeed.com with specific job titles and/or mentioning specific skills. I wrote this scraper to do that. (It may or may not still work; I haven’t used it in a long time).
Charlie Custer 