Makeup Product Data Exploration

This project analyzes a dataset of makeup and fragrance products from a public Sephora dataset on Kaggle.

The data includes product ratings, popularity metrics ("loves"), review counts, and brand information.

Goal: Understand what drives product popularity.

Core Dataset

Below is a portion of the dataset used for this analysis.

Product Brand Loves Rating Size
La Habana Eau de Parfum19-6938274.153.4 oz
Rainbow Bar Eau de Parfum19-6932534.253.4 oz
Kasbah Eau de Parfum19-6930184.483.4 oz
Purple Haze Eau de Parfum19-6926913.233.4 oz
African Beauty Butter54 Thrones190284.336 oz
Mini African Beauty Butter54 Thrones33924.521 oz
The Cape PerfumeABBOTT31184.611.7 oz
Crescent Beach PerfumeABBOTT16084.591.7 oz
Crescent Beach Travel SprayABBOTT19574.780.33 oz
Sequoia PerfumeABBOTT13224.621.7 oz
Mojave PerfumeABBOTT8254.091.7 oz
Yuzu Eau de ParfumAcqua di Parma19534.670.7 oz

Highest Rated Product Example

Crescent Beach Perfume Travel Spray

  • Rating: 4.78 / 5
  • Brand: ABBOTT
  • 1957 Loves

Even with relatively few reviews, the product maintains a very high rating. This suggests strong satisfaction among customers who purchased it.

Price vs Popularity

Higher price does not guarantee popularity.

The Yuzu Eau de Parfum by Acqua di Parma is significantly more expensive than some competitors.

Despite its strong rating, it receives fewer "loves" compared to more affordable fragrances.

This suggests consumers consider reviews and perceived value when making purchasing decisions.

Key Takeaways

What the data reveals about beauty product trends

💄 High ratings do not always require large review counts.
Some products maintain excellent ratings even with fewer reviewers.

⭐ Brand reputation influences perception.
Brands like ABBOTT appear frequently among top-rated products.

💰 Higher price does not equal higher popularity.
Some lower priced fragrances receive more engagement and customer interest.

📊 Data helps consumers make better decisions.
Ratings and engagement metrics reveal insights beyond marketing or price.

Makeup Product Data Exploration · Sloan Kimel