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Data Science Blog > Web Scraping > Cruelty -Free brands vs None Cruelty-Free brands

Cruelty -Free brands vs None Cruelty-Free brands

Jo Wen (Iris) Chen
Posted on Jan 16, 2019

Project GitHub | LinkedIn:   Niki   Moritz   Hao-Wei   Matthew   Oren

The skills we demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Objective

We are living in a society where younger generations are more health-conscious than any other previous generations. We are bound to make hundreds of decisions everyday and it has become important for us to center these decisions around our health. Making health-conscious decisions is not just limited to adhering to a healthy diet and committing to routine exercise. It also includes shopping ethically so that we can achieve a more sustainable environment. A year ago, I discovered that animal testing in cosmetic was conducted not only on common laboratory animals but was also conducted on dogs and cats. It is shocking to me how it is still a common industry practice and I believe it is unnecessary to use animals to test cosmetic products. There are humane alternatives that cosmetic companies can pursue to achieve the same results and these products are clearly marketed as cruelty -free. I understand, as a consumer, it is my responsibility to voice this concern through my purchases so I started to pay attention to the product choices that are available on the market in order to stop supporting the ones which conduct animal testings.

What does Cruelty-Free mean?

In short, โ€œcruelty-freeโ€ simply means that a product and its ingredients were not tested on any types of animals.

Process

In order to compare cruelty-free products and non-cruelty free products I scraped Sephoraโ€™s website using Selenium. Sephora is a mainstream multinational chain of beauty stores that offers beauty products including cosmetics, skincare, fragrance, nail and hair products. As a result, I scraped close to 5,000 products out of 81 brands. The brands breaks down to 38 cruelty-free and 43 non-cruelty-free. Out of these brands there are 1,343 cruelty-free product and 3,587 non-cruelty-free product.

My biggest challenge is to overcome the websiteโ€™s scrolling mechanism in order to load everything on the page for the scrape. This challenge is present on both the brand pages and product pages. In order to get the rating section and the reviews I will need to make sure the page scrolls down to the exact location of the respective sections. The second challenge I have is speed - Selenium is slow. I did not end up scraping the reviews as I planned to since most products have more than 1,000 reviews and some have close to 15,000 reviews. For one product that has 4,000 reviews it took 6 hours to scrap all the reviews and this proves to be an impossible task to complete given the timeframe I have for the scope of this study.

Findings

  1. Myth:  Cruelty-free product costs more.

Since the group is categorical data and the price is numeric data, I used Seaborn to do a box plot.

The right side of the plot is after the data being standardized. It can be observed that cruelty-free product actually cost less on average and most cruelty-free product is priced in a more reasonable price range.

The left side is before the data being standardized. The interesting finding here are the outliers on the left box plot. These outliers fall within a price range of $400 to $600 and it is worthy to note that these outliers are products from luxury brands such as Tom Ford or La mer and the $600 ones are beauty devices.

  1. Does price affects number of reviews and rating? Does โ€œLoveโ€ counts affects number of reviews?

I want to find out whether a relationship exists between โ€œLoveโ€ counts (akin to the โ€œLikeโ€ concept on Facebook), price, number of reviews and product rating. As you can see from the regression plots on the left side and the scatter plots on the right, the regression line is pretty flat, so there is no linear relationship between the variables. Please note that due to the length of this article I only included a few plots.

  1. Is there any pricing strategy between non-cruelty-free brands versus cruelty-free brands which are owned by the same parent company?

I want to find out the price distribution among brands owned by the same parent company which are cruelty-free versus its non-cruelty-free counterparts (ie: Estee Lauder, Smashbox, Clinique, and Bobbi Brown). I believe by supporting the cruelty-free brands that are owned by a parent company which also offers non-cruelty-free brands, we can send the right message to the parent company and create impact through our purchases. From the chart below you can see Smashbox (owned by Clinque) price range is close to Clinique which means the cruelty-free brand costs almost the same as the parent companyโ€™s non-cruelty-free lower tier brand and cost much less than itโ€™s higher tier brands such as Estee Lauder and Bobbi Brown.

  1. Which type of product has the highest average product rating? Cruelty-free vs non-cruelty-free

I used pair plot to see the relationship, scatterplots for joint relationships, and histograms for univariate distributions. As the chart below shows, the brand that has the most reviews and highest average product rating is a cruelty-free brand - u-le Hendrickson.

Improvements

First is to scrap all the reviews. The rating areas have user data such as user age, location and time-stamp so it may be interesting to see if anyone mentioned cruelty-free. Due to Seleniumโ€™s speed I will need to incorporate this with other framework.

Second is to scrap websites that carry generic drug store products since Sephora does not sell generic products. Generic drug store products are generally more affordable.

Third is to find alternatives at the product category level and make recommendations for consumers. Such an example would be to find the best rated mascara from the cruelty-free brands and recommend it to people who purchased the non-cruelty-free mascara based on the highest rating.

About Author

Jo Wen (Iris) Chen

View all posts by Jo Wen (Iris) Chen >

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