When we talk about customer review analysis or building a product review strategy that yields results, we can’t skip over one of the most important steps in the process: Review scraping.
So, what is review scraping?
Customer review scraping is the process of obtaining the actual review data, extracting the relevant fields of information, and organizing it into a format that can be more easily analyzed.
Typically, the data that is collected includes data such as seller name, merchant ID, title, ASIN, URL, image URL, brand, product overview, description, sizes, colors, styles, availability, product category, price, images, features, ratings, promotional information, and (of course) reviews text.
This data is collected straight from a retail website, and organized into a sheet or database that companies can use for internal purposes, such as review analysis.
Sounds simple enough, right? Wrong - when it comes to product review scraping, there’s a lot more than meets the eye. Between accessing the data in the first place, accounting for high quantities of disorganized information, and adequately organizing it in a way that is useful - review scraping is much easier said than done.
That said, it’s one of the most widely used and most important processes in any eCommerce review strategy. So let’s pull back the curtain and dive in.
Before we get into the nuts and bolts of product review scaping, it’s important to understand the reasons why companies do it in the first place.
Online customer reviews have become one of the most valuable data sources for consumer packaged goods (CPG) brands. Why? Because unlike any of the traditional forms of market research, product reviews provide companies with free, unbiased opinions on their products and their competitor's products.
Using online product reviews as a source of Voice of Customer data allows brands to make tactical and strategic decisions that directly appeal to their shoppers and customers, ultimately driving sales.
In eCommerce marketing, reviews play an important role in curating messaging and optimizing product description pages (PDPs). By analyzing customer feedback, marketers are able to uncover real-world use cases, language, and pain points that contribute to customer-centric marketing strategies.
Product development is another area that can be hugely impacted by listening to customer reviews. By analyzing feedback, product teams can understand what features and updates customers are looking for, enabling them to prioritize development and create product roadmaps that respond to the wants and needs of customers.
Product review analysis offers insights teams not only the fastest time to insight, but also the most accurate, unbiased information from real shoppers. Unlike other sources of customer insights, such as focus groups or surveys, product reviews provide unsolicited feedback from people using products in real life, rather than in a vacuum.
Now that you understand what review scraping is, and why it’s important for eCommerce and CPG companies, let’s talk about how it’s actually done.
Scraping reviews is a multifaceted process, with three major components:
Typically, companies use a tool or multiple tools to carry out this process for them. In many cases, a service provider that utilizes review data for another purpose will include review scrapers within their platform.
Yogi is an example of this. Since customer sentiment analysis requires organized review data, Yogi has custom scrapers for every major retail platform, such as Amazon, Target, and Walmart, and is constantly building new ones.
Another example of tools with in-house scrapers is engagement tools such as BazaarVoice, which need the data for review syndication, although a drawback is that Amazon scraping is not included.
If you’re wondering about the prospect of manual review scraping, you’re not alone. Manual review scraping is an option, albeit not a viable one for most companies (considering its many drawbacks).
The first is sheer time. With thousands of reviews and ten-plus data points for each one, manual review scraping is extremely arduous and time-consuming. Not to mention the high potential for human error.
However, the difficulty with manual review scraping goes beyond time and human accuracy.
Unfortunately, many websites have become wise to a variety of review scraping tactics and responded by employing as many restrictions to the practice as possible. These include limiting content after a certain number of scrapes, adding CAPTCHAs and logins for each screen, and strategically labeling HTML tags and CSS class names to increase the difficulty of data pulls.
Additionally, to ensure the legality of review scraping practices, it’s key that review scraping practices do not violate a website's terms of service. Things like intellectual property, complete text, and correct source attribution are important to be aware of, as they can vary from source to source.
As you can see, due to the many downsides and potential pitfalls of manual review scraping, it’s uncommon for brands to carry it out on their own.
As we’ve discussed, review scraping is the most foundational aspect of utilizing reviews in an eCommerce strategy - and online customer reviews are an extremely valuable resource for CPG brands.
Scraping online customer reviews allows brands to analyze their customer feedback and make strategic decisions that appeal directly to the trends and preferences of their customer base. This is part of what we call the product review flywheel.
The review flywheel is an advantageous cycle with three key steps:
If you’re interested in building a product review strategy for your brand, check out our Reviews 101 Course!
Yogi is a customer sentiment analysis platform that carries out each step of the review process, from scraping, to analysis, and generating useful insights for CPG brands.
Yogi has scrapers for every retail source imaginable, but that’s not even the best part. Yogi’s proprietary AI generates state-of-the-art visualizations, review summaries, and custom insights that empower customer-centric decision-making in record time.
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