Web Scraping and Exploration of Gaming Mice Data from Newegg

Posted on Oct 14, 2022

Power BI Dashboard


Research Question

What does the current gaming mouse market look like and what features make a gaming mouse more popular and/or highly rated?

Disclaimer: Do not have data on units sold or profit margin of mouse, therefore will use number of reviews as a proxy metric for popularity. Also have no way of knowing how profitable each product is, for instance a mouse may not be very popular but has extremely high profit margin and therefore the manufacturer may not necessarily care to make changes to try to boost the product's popularity (potentially at the expense of its profit margin).

Target Audience

Gaming mouse designers/manufacturers.

This project can be useful in terms of gauging competitors as well as general market. Can also help uncover the customer base’s desirable features in the product.

Web Scraping and Data Cleaning

This project specifically looks at new, right-handed gaming mice that ship from the U.S.

Web scraping is done using Scrapy and the following fields are scraped from the Spec table of each product:

  • Brand
  • Product Name
  • Model
  • Grip Style
  • Maximum DPI
  • Buttons
  • Connection Type
  • Color
  • Average Review Rating (1-5 Stars to the nearest star)
  • Number of Reviews
  • Price

Data cleaning included:

  • Brand: Make all uppercase to avoid different versions of the same brand being interpreted as different.
  • Style: Replace any style that has multiple types or is "adjustable" to "Multiple".
  • DPI: Extract digits and convert to int.
  • Connection: As long as wireless is available, convert connection to "Wireless".

Exploration of Mice Features


Top 10 Brands with Most Products


Top 10 Brands with Most Number of Reviews (Popularity)


5 out of the top 10 brands with the most products only produces lower price range mice, with the max price for each product not exceeding 40 dollars and median price for all products not exceeding 30 dollars. Despite having the most products, none of these 5 lower price range brands are in the top 10 most reviewed list while 4 of the remaining 5 brands with the most products do have the most reviews as well. It is interesting to see that for brands that pump out low end products, the number of reviews/popularity does not increase with the number of products. However, it is possible that due to the low price, customers do not bother reviewing them since they may be throwaway mice or expectations were low to begin with.

Brands with most products/reviews all tend to have good ratings of at least 4 stars. Exception is gun mouse from Zalman, shown below, which makes sense that it has a lot of reviews since it’s so unique.

Maximum DPI

Most maximum DPIs are between 3000-4000 (specifically 3200 and 4000). Specific DPIs are likely established cutoff points in the industry and thus occur much more frequently than others, these include 3200, 4000, 12000 and 16000. 16000 DPI products have the most reviews, followed by 12000 and 10000. It appears for most gamers, 16000 would be the highest they need.

Number of Buttons

Almost half of all mice have 6 buttons. The number of products generally decreases as the number of buttons increases but there is increase at 11/12 buttons and 19/20. This is likely due to these mice being a specific type (MMO).

From looking at the number of reviews, 6-11 buttons (with the exception of 10) are all very popular. There is little popularity for 12-17 but surge in popularity for 19 - 20, likely for the MMO-specific mice with a number pad on the side such as the one shown below.

Connection Type

Around 80% of the gaming mice use wired connection and conversely only 20% have wireless capabilities. Popularity is similar, with wireless mice having ~20% of the number of reviews. Mean rating is slightly higher for wired mice over wireless. Findings make sense since for gaming purposes, wired mice are considered better due to faster response time, less connectivity issues and do not have extra battery weight or need to charge. The min, max and mean price for wireless mice are all higher than wired which is expected due to the necessity of additional transmitter/receiver components.


224 out of 308 products are black or at least partially black. Second highest color is white and only has 35 products (including Matte White). This is consistent with the current design trend as most modern PC products are black, such as desktop cases, keyboards and monitors. Black mice are a safe bet to go with most systems. Previously most computer products were white/beige but trend died out. Apple products tend to be silver/chrome, but Apple computers are generally not associated with gaming, so it makes sense that the aesthetics of gaming mice align with that of PC.

Price, Number of Reviews and Ratings

Correlation Matrix of Numeric Features


153 out of 308 mice are below $30, meaning most mice are fairly cheap. There are positive correlations between DPI/Buttons to Price, which makes sense as higher DPI generally indicates a better sensor and having more buttons adds to the complexity of the construction and design. The number of reviews also has a slight positive correlation to price which could be explained with previously mentioned reasons for why customers may not care to leave reviews for cheap mice. The rating and price have essentially no correlation, suggesting that customers may not necessarily like expensive mice over budget ones and lower price mice may be generally good in terms of value.

Number of Reviews

161 out of 308 products do not have any reviews and 42% of the products with reviews have less than or equal to 5 reviews. It can be seen that leaving reviews is overall a very rare occurrence. There are slightly positive correlations between DPI, Buttons and Price to Reviews, which makes sense as customers are less inclined to review cheap mice with minimal amount of features. There is seemingly no correlation between the rating and number of reviews.


As mentioned in the Number of Reviews section, more than half of the products are not reviewed/rated by anyone. For products with more than 45 reviews, only 1 product (the gun mouse) didn't have a rating of 4 stars. 126 out of 147 reviewed products are rated 4 stars and above. It appears that much more often than not, customers (at least those that leave ratings) are satisfied with the product they purchased. There is essentially no correlation between rating and any other numerical feature, which is expected given there is such minimal variation in rating.

Closing Remarks

Many interesting observations regarding the gaming mice market were made from this project. It could be seen that companies can have very distinct business strategies whereby some may focus on producing only lower end/budget gaming mice while others can have a lineup of only one very unique product such as the gun mouse. It could also be seen that especially for the lower end mice brands, having more products does not necessarily lead to more customer engagement or popularity in terms of reviews. In terms of feature recommendation for manufacturers, 16000 DPI should be sufficient to satisfy most of customer base and 6-8 buttons is good unless it's targeted towards MMO then up to 20 could be good. Having just wired connection and some variation of black color are safe bets. Price generally increases with DPI and number of buttons. More than half of products have no reviews/rating and for those that do, poor ratings are extremely uncommon. Budget mice with more basic features tend to get less reviews but none of the numerical features seem to have much correlation to the rating.

Future Work

The resolution for the rating is very low since it is only the average rating per product and rounded to the nearest whole star. It would good to scrape individual reviews such that the distribution of ratings for each product could be studied and interesting questions such as which products do the customers have the most polarizing opinions on could be explored. Sentiment analysis could also be done on the scraped text of the review.

There are other potentially important features that contribute to the products' rating and popularity but weren't explored in this project, such as lighting or RGB capabilities, ergonomics and weight adjustability just to name a few. However, since these features are not fields in the spec table, perhaps need to be a bit creative by scraping and searching within the product descriptions.

Lastly, it could be valuable to manufacturers to conduct some SWOT analysis on similar products between competitors.


Project on GitHub

About Author

Cheng Zhao

Certified Data Analyst/Scientist with engineering background in semiconductor and electronics packaging. A detail-oriented problem solver with a passion for analytics and utilizing machine learning techniques to gain insights from data to drive business decisions and to advance automation...
View all posts by Cheng Zhao >

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI