How Products Reviews can Drive Marketing and Product Design?

After the exploratory analysis, it's time to search for insights on product reviews!

The aim here is to search for Product Features / Product Characteristics within reviews. Here my approach:

>> select product with most reviews

>> data engineering (text into numbers)

>> split the data set (train and test)

>> train the model (Logistic Regression)

>> plot SHAP value

>> re-run the model (nltk -- removing adjectives equal to "JJ")

Conclusions:

- The word "love" is the most powerful word defining a review rate

- Removing adjectives, the second most powerful word is "price"

- Product characteristics >> "easy to use", "great price", and "battery life"

- Impact of important dates >> "black friday"

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