Root cause analysis (RCA) is changed forever.
For a newsletter, wanted to understand the correlation between parameters such as subject length, emojis, numbers, dollar signs with open rates and click rates
Instead of doing it in excel or asking a data analyst to crunch the numbers, I just ran this table through Open AI’s code interpreter (advanced data analysis) on ChatGPT.
And it gave me a decent correlation matching some of my intuition and breaking some others.
Intuitively:
- numbers, dollar signs performed better
- certain keywords that were meant to perform better, did
Counter intuitively
- longer subject lines performed better than shorter ones
- question marks didn’t work in subject lines
This no doubt saved me time so I could quickly get to the root cause and fix the issue for the new
Even though I tested it out on a few newsletter editions, I still think that the correlation makes sense, but will test out with more data
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