Inspiration
I wanted to understand how relevant a SERP title is to its search query to identify the outliers that can fuel confidence to do content on topics that KR tools will tell you to not do content about. For example, va ery specific long tail query for which a very targeted piece ranks in the 6th position with a very high similarity score. The CTR would be less, traffic would be less but whatever little traffic can be salvaged it would be high converting one.
What it does
The extension runs on your SERP & shows the TF-IDF Vectorized Cosine Similarity score on SERP Titles against your search query
How I built it
I leveraged ChatGPT's 01 Model to build this extension entirely
Challenges I ran into
In my first go the extension was rejected because of issues like Justification reasoning for which again ChatGPT helped me with provided reasoning to Chrome.
Accomplishments that I'm proud of
I organically onboarded 250+ Users within 2 months, had this extension featured on SEO FOMO News, Got positive testimonials, and had some folks share it on Social Media explaining how they are finding it useful, which only motivates me.
What I learned
Creating the extension isn't enough you have to keep promoting it, to keep on onboarding more & more users, your chrome extension page should explain the use cases with screenshots for the user's better understanding.
What's next for TF-IDF SERP Analyzer Chrome Extension
I will try to replicate the same for SERP Meta Description which will help understand which paragraph is being picked considering the query, but this is for the future.
