by Andrius Palionis, VP of Enterprise at Oxylabs
Customers love reviews because they provide critical information about the quality, features, benefits, and drawbacks of a product or service. Marketers love them because they reveal insights into consumer sentiment, brand reputation, industry trends, the buyer’s experience, and more. In this article, I will explain how to extract public customer review data via web scraping and integrate it into your marketing strategy.
What is web scraping?
Web scraping is the automated process of extracting large amounts of public data from the internet using scripts and software tools. The quality of data gathered via web scraping directly correlates to the effectiveness of the scraping process. Besides costing time and resources, low-quality data might take your strategy off track and lead to bad decisions.
How to scrape review data effectively
While scraping data is complex and challenging, the following steps provide a useful summary to help you better understand the process and configure your tools.
Step 1: Determine the target website
The first step is to identify the websites containing public customer reviews you want to extract. Common sources of public customer reviews include:
- Online marketplaces
- Search engine services
- Social media platforms
- Discussion forum threads
Choosing a website where your target audience is most likely to leave reviews is essential. For example, if you want insights on luxury leather goods, it’s probably best to scrape a large upscale department store like Bloomingdales instead of Etsy.
The website size might also be important if you are willing to scrape reviews from multiple sites, as it can be resource-intensive. Other important factors to consider are the website’s complexity, accessibility, Terms of Service, and robots.txt files. You should always adhere to the best scraping practices and extract data ethically.
Step 2: Examine the website structure
The second step is to identify what kind of information the scraper will have to return and where this data is located. For these tasks, you will have to choose selectors that will be used to target specific elements in the websites you scrape. It’s an extensive topic that goes beyond the scope of this article. However, if you want to learn more, we created a guide that teaches you how to choose between XPath and CSS selectors.
Step 3: Write a customer script or use a ready-made web scraping tool to extract the data
Again, this is another broad topic. However, if you want to build a simple scraper with Python yourself, we have you covered with our Python Web Scraping Tutorial.
Step 4: Parse and store the extracted data in a structured format
Web scraping typically produces an illegible “mess” of information that’s difficult to read. The parsing process performed during the last step transforms that data into a structured format, such as a CSV or JSON file.
Once you’ve gathered and parsed the information, the next step is to correct errors, remove duplicates, and perform other tasks that optimize data hygiene. Doing so ensures accuracy, completeness, and consistency.
Five ways to integrate customer review data into your marketing strategy
Scraped public review data can provide valuable insights into customer behaviour, preferences, and future trends, enabling you to:
Improve product and service offerings and catalogues
Performing text analysis on scraped data lets you extract keywords that identify common patterns. For example, an online store selling jeans can analyze data from a large marketplace to identify products with the best fit. Likewise, they can use text analysis to determine high-quality items that wash well and last longer.
Discover trends
Staying on top of trends is essential to boosting sales and avoiding the accumulation of stale inventory. To identify trends, you can use text analysis to group similar pieces of text based on common themes.
For example, a large ecommerce business selling sports apparel may be interested in knowing which players are being actively followed on social media platforms. By doing so, they can stock jerseys and sneakers the athlete wears in anticipation of growing demand.
Create a better customer experience
According to a report published by Salesforce, 47% of customers that experience a substandard experience will stop buying from a company. As a result, businesses are increasingly focusing on improving customer satisfaction.
Web scraping reviews helps companies gather data that provides insights into what parts of the customer experience need improvement. These might include packaging, delivery times and prices, online support, chatbots, and refund policies.
Safeguard your brand from negative publicity
Online controversies and scandals in social media can severely impact sales. Identifying adverse situations early and responding effectively is the best way to avoid permanent brand damage.
Sentiment analysis on recently scraped user comments might be the best weapon against negative publicity. If a potentially serious situation is identified, the brand can take action that includes:
- Requesting comment removal if the allegations are false
- Issuing statements or press releases to counteract the claims of misconduct
While the above strategies are integral to maintaining a solid business reputation, sometimes it’s best to avoid taking any action. This is especially critical in cases where the users making the comments have low follower counts. By not responding, businesses can avoid directing more attention to the negative issue.
Develop valuable content for your target audience
Creating relevant content that speaks to your target audience is an effective way to establish authority, develop trust, and direct traffic to your products and services. Web scraping and text analysis can be used to extract popular keywords and topics for use in website articles, social media posts, newsletters, promotions, and influencer campaigns. As a result, your brand can consistently release compelling content that engages your audience and encourages them to interact with your business.
