Data Comparison Between Honda and Toyota
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
Honda and Toyota. Data shows it's two of the biggest car companies in the world. On the surface, they are similar companies that offer similar products. Why would you buy one over the other? Competition between these companies must be fierce, so how do they market themselves to differentiate themselves from each other? How does their marketing influence consumer perception of their brand?
To do some research into possible answers to these questions, I scraped user reviews from cars.com for every model currently offered by Honda and Toyota for model years 2013 to 2018.
To aid in the analysis of the scraped data, I made a shiny app, which I encourage you to open and reference as you read this blog post.
Comparing Score Categories
Looking at score categories over all reviews, Honda is ahead in every category but reliability. The difference is only significant the style categories and value for money. The pattern is similar for model years 13-14, but difference in value for money is no longer significant. For model years 17-18, Honda is ahead significantly in all categories except for reliability.
For model years 13-16, Toyota is rated significantly higher in reliability and performance, with other categories being fairly even. While for model years 15-16, Toyota is also ahead significantly in the overall and comfort categories.
So Honda has been doing an excellent job marketing their cars in the last two years, however Toyota is consistently rated higher in the reliability category. Toyota should consider why Honda are generally perceived more favorably the last two years, and continue to push their brand as the most reliable.
Comparing Categories' Data Across Model Years
There seems to be an upward trend in positive reviews. Some possible explanations would be that negative reviews become more likely over time. Perhaps reviewers write negative reviews when problems that take time to appear arise, or having problems with the dealership. Perhaps buyers attitude towards their purchase is most positive just after buying, then decreases over time.
Another explanation might be a greater proportion of fake positive reviews for more recent model years. If potential buyers are persuaded by user reviews, then it makes sense that the companies would have an incentive to flood the site with glowing reviews. This incentive would be strongest for the most recent model year. Consequently, the proportion of fake reviews would decrease over time. These relationships require further investigation.
The only exception to the upward trend is the reliability category, which is fairly stable.
Data 0n What Reviewers are Saying
The most common words used are "great" and "love". This is not surprising since the majority of reviews are positive
Restricting to when the reviewer does not recommend the car, we see the words "engine" and "noise" more commonly among Honda reviews. A potential problem with their cars? Restricting additionally to used cards, the word "vibration" now appears prominently on the Honda side. Perhaps you should be concerned if considering the purchase of a used Honda.
Looking at recommended reviews for model year 2018, after removing the words "love", "great", "good", features", and "comfortable", the words "safety" and "reliable" become noticeably more prominent among Toyota reviews. If Toyota is marketing their cars as safe and reliable, then it looks like they are succeeding. I don't know what their marketing strategy is, but if they want Toyota to be the safe and reliable brand, then it's working. Perhaps they believe that consumers purchase the car that they perceive to be safe and reliable with their actual money at the end of the day.
Did you find an interesting pattern in the data? If so, please leave a comment about it below.
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