The Importance of Reviews

E-commerce reviews are not only an important reference for consumers’ shopping decisions, but also an important way for businesses to collect consumer information. According to the content of online review research, it mainly includes:

Motivation research and usefulness research
Summarize the current status and forecast future trends
Analyze existing problems and make targeted suggestions
Analyzing customer attitudes and profiles to build a persona model

How to Scrape Online Reviews

There are ways to get review data online at scale:

Primitive copy-and-paste method (hopefully not);
Writing your own scripts by coding;
Outsourcing the data project to a data provider or a web scraping team;
Using a web scraping tool to help you automatically scrape review data.

Believe it or not, web scraping is no longer the sole privilege for coders. Some web scraping tools like Octoparse have translated complicated script-writing processes into easy point-and-click operation and you can easily build your own review scraper for voluminous data scraping.

Check these cases to find out how to scrape reviews online:

Research on Ecommerce Reviews

E-commerce is prospering. More and more consumers are keen on online shopping. The concept of “Internet +” has enabled the rapid development of the e-commerce industry, attracting more merchants to sell goods online. And, the sales status of merchants’ products is closely related to the reputation – words of consumers or users’ online comments.

Customers share their own personal shopping experience on ecommerce product pages, review websites and social media. Obtaining online reviews is simple and easy. It has become one of the most influential factors in consumers’ purchasing decisions and an opportunity for merchants to approach consumers.

According to the existing works done by researchers, the analysis of e-commerce online reviews falls into two categories, namely motivation research and usefulness research.

Research Content	Research Perspective	Research Method
Motivation Research	Motivation for online reviews: platform support, emotional expression, reciprocity, self-image, social interaction, reward policy, etc.	Questionnaire survey method, social exchange theory, hypothesis testing, model construction, empirical research
Usefulness research	Factors affecting the usefulness of online reviews: individual characteristics of reviewers, characteristics of review content	Network data collection, comparative research, hypothesis testing, sentiment analysis, model construction, empirical research

How Researchers Use Review Data for Research

1. Online review research

(1) Motivation research

Online reviews in e-commerce platforms can not only provide consumers with decision-making assistance, but also help merchants understand product conditions. However, without certain incentives most consumers would rather stay silent for a good shopping experience and User Generated Content will not come to you without efforts (Well complaints may do).

Insufficient user reviews have become a headache for businesses. The prerequisite for effectively solving this problem is to accurately understand the reasons why users participate in online reviews. In view of this, some researchers have conducted research on the motivations of online reviews.

They used empirical research methods to explore the motivations of user reviews on a hotel website. Based on social capital theory and social exchange theory, scholars found that the motivations for users to comment were mainly reciprocity, self-improvement, focus on community image, and altruism. Some of them have found that the motivation behind reviews is often related to social psychological factors such as the social status, self-image displayed, perceived entertainment, and reward factors such as points and gifts. However, foreign literature mainly focuses on the research of non-profit online review sites, and there is less online research on e-commerce platforms.

Online review motivation research is the foundation of e-commerce online review research, and the research results can provide references for the optimization and improvement of consumer review systems on e-commerce platforms.

(2) Usefulness research

In the era of information explosion, consumers cannot evaluate the authenticity and effectiveness of reviews in the face of massive product information. At the same time, the commercial value of reviews is valued by businesses. Some businesses will use false reviews to obtain improper benefits. This requires further study of the usefulness of comments. Researcher Mudambi et al. defined the usefulness of reviews as the help of product reviews perceived by customers in their purchase decision-making process.

By crawling online review data of a product on the e-commerce platform, and using statistical analysis methods for verification based on their own hypotheses, and conducted regression analysis and research on related indicators, researchers concluded that

Extreme reviews are more useful than neutral reviews for experiential products
Long comments are more useful than short comments

Research on the usefulness of online reviews will not only help consumers quickly identify useful real reviews and improve their shopping efficiency.

3. Conclusions

To sum up, although e-commerce online reviews have received widespread attention from scholars, there are still some areas that need improvement. With the continuous development of new technologies and new fields, businesses and consumers hope to obtain value from online reviews. Information requirements are getting higher and higher, so the research on e-commerce online reviews needs to be in-depth.

References:

[1] MUNZEL A, KUNZ W H. Creators, multipliers and lurkers: who contributes and who benefits at online review sites ［J］． Journal of service management, 2014 (1): 49-74.

Author
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Cecilia W

I am a content writer and a digital marketer in data science who believes in the power with which data can endow people’s businesses. I am working on writings that convey real values. If you have any feedback or ideas about web scraping and data analytics, talk to me at cecilia@octoparse.com.