Data Scraping Pet Supplies Portal Chewy.com

Posted on Dec 13, 2017
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Introduction

With spending on pets in the United States rising annually and projected to reach almost $100 billion by the end of the decade, data shows the pet industry is considered virtually recession-resistant. It feeds on factors such as the multi-generational appeal of pets, the positive correlation between good human health and pet ownership, and a pet culture that spawns spending on luxury goods for animals and global expansion. Data Scraping Pet Supplies Portal Chewy.com

Riding on the back of the lucrative pet supplies industry is the online portal Chewy.com. With a wide product offering from leading brands, it is where pet lovers shop. For this project, I used Scrapy to Web Scrape pages on Canned Dog Food at Chewy.com.

Objective

The main objectives were to uncover:

  • Market Shares
  • Product Segments
  • User Ratings of Product
  • Product Marketing Strategies

Data

Key targeted information obtained include Product Name, Maker, Food Texture, Price, Weight, Rating, Number of Reviews, Product Key Benefits.

Food Texture

A total of 780 products are offered by the Top 20 Brands in this segment. Most notable are Bill's Buffalo and Purina with about 100 products each. They are followed by names like Cesar, Wellness and Hill's.

The Canned Dog Food segment is a highly differentiated market. Owners can choose from a selection of food texture to match their pet's discerning palate. Presumably the most favored texture is Pate followed by Stew, Chunks in Gravy, Minced and Shredded in descending order.

Number of Reviews and Average Ratings are both equally important indicators of the Product Popularity. A combined score was formulated with components of both metrics using the equation

Score=Rating + 5*(1−e(Reviews/Q))
where Q is a tuning constant
(Score : 0 - 10)

Distribution of Ratings and Reviews

Highly skewed Distributions of Ratings & Reviews are transformed into a Normally Distributed Score. The upper range of the distribution approaches a score of 10 for products.

Based on the Formulated Score, I was able to distinguish the Top 30 Best Scoring Products across Brands and Food Texture. Hill's Prescription Diet emerges as a clear winner in the most popular segments, that is Pate and Stew. Purina holds it on its own in the Minced segment. Royal Canin deserves to be mentioned with popular products in Chunks & Gravy as well as Pate. Notably, Cesar is missing from this list despite having a large number of Products.

Sentiment Analysis

It is undeniable that Customer Reviews and Feedbacks are highly valuable encompassing both Positive and Negative ones. Sentiment Analysis was performed on selected reviews.

Word Clouds

Additionally, Word Clouds were used to provide interesting insights on most commonly used words in: Positive Reviews

Negative Reviews

Product Key Benefits (Marketing)

 

About Author

Chung Meng Lim

Chung Meng has a Masters in Electronics Engineering. He is forging a path in the exciting field of Data Science.
View all posts by Chung Meng Lim >

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