This page is about my fintech marketing research. I’m creating Python scripts that predict how many likes an article will get by analyzing the text it contains. These scripts help me write articles that deliver better results for clients. It takes a while to explain how these scripts work and how I check whether they provide accurate results, so I wrote an eBook about it. It’s called “Sentiment Analysis in Fintech Marketing” and you can download it by filling out this form.
If you fill out the form, you’ll not only get the eBook, you’ll also be subscribed to my newsletter. In this newsletter I write about my ongoing experiments. In the eBook I studied whether I could predict the popularity of a post by using sentiment and word count. In the newsletter, I write about tests that consider additional metrics such as the grade level of the document. My ultimate goal is to build a model that will show me how to write an article that gets the highest possible amount of engagement from readers.
I’m not doing this to write fluff or clickbait, or other thin, low-quality articles that get a lot of likes. I’m researching ways to write about fintech topics like money transfer and payment processing apps while still making the articles exciting enough to attract readers. If this is a topic you’d be interested in reading about, you can download the eBook and sign up for the newsletter by filling out this form.