Black Friday Exclusive – Start Your Data Projects Now with Zero Setup Fees* and Dedicated Support!
Search here
Can't find what you are looking for?
Feel free to get in touch with us for more information about our products and services.
Use Cases
How a Leading Consumer Electronics Company Leveraged Automated Customer Review Extraction
Customer reviews serve as the backbone of product development and consumer insights.
For one leading consumer electronics brand, these reviews were essential for fueling machine learning models that perform sentiment analysis and inform key business decisions.
However, the frequent removal of reviews by platforms due to policy violations creates significant challenges, leaving gaps in the data and affecting the accuracy and consistency of their insights.
It is like trying to build a house on a shifting foundation, therefore, without a reliable stream of reviews, the client couldn’t trust the data that powered their ML model.
In this case study, we’ll show you how Grepsr’s automated customer review extraction and alert system helped the brand overcome its data challenges, ensuring a seamless flow of high-quality insights for business decisions, without the need for constant manual checks.
About Client
The client is a leading e-commerce brand specializing in electronics, offering a wide range of products including TVs, remotes, streaming sticks and other tech gadgets.
With a presence on major online platforms such as Amazon and Best Buy, they cater to a diverse global customer base. Their commitment to innovation and customer satisfaction drives their use of data for continuous product improvement and market insights.
To stay competitive and aligned with consumer needs, the client relies heavily on customer feedback, specifically reviews because they are a source of valuable insights. These reviews are crucial for understanding customer sentiment as well as for refining products and shaping marketing strategies.
Data requirements
The client’s primary objective was to implement an efficient and automated system for extracting customer reviews from their product listings across major e-commerce platforms like Amazon and Best Buy. The specific data requirements were:
Daily customer review extraction:
The client needed an automated system to extract customer reviews on a daily basis for their own products. This data would serve as the foundation for sentiment analysis and product development insights.
Competitor review monitoring:
In addition to their own products, the client wanted to track reviews for competitor products on an ad hoc basis. This was to keep a close eye on market trends and customer preferences in real-time. Then they could compare customer sentiment across the market and identify potential areas of competitive advantage.
Challenges
We faced several challenges when it came to extraction and maintaining reliable customer review data for their products.
Frequent removal of reviews by platforms:
One of the most pressing challenges was the frequent removal of reviews by the e-commerce platforms they sold on, such as Amazon and Best Buy, often due to policy violations like offensive language. For instance, for a popular TV model on Amazon, 25-30 reviews were removed within a two-week period, representing about 5-7% of the total review count. This caused inconsistent data and a fluctuating review count, making it difficult to rely on the data for accurate sentiment analysis.
Data inconsistencies:
The removal of reviews resulted in gaps in the data, which created challenges for the client’s product development and marketing teams. Inconsistent data meant that the sentiment analysis models were not receiving complete and accurate feedback, leading to skewed insights and delayed decision-making.
Manual review:
To address review removals, the client’s team had to manually track review counts daily to identify discrepancies, which was time-consuming and prone to error. This manual oversight was inefficient and often led to delays in identifying issues with data extraction.
Lack of real-time insights:
Without a reliable, automated system in place to monitor review extraction, the client struggled to obtain real-time insights. This hindered their ability to react swiftly to changing customer sentiment or product feedback, impacting their agility in making necessary adjustments to their offerings.
Solutions
To overcome the challenges of inconsistent review data and ensure reliable, actionable insights, Grepsr implemented a streamlined solution designed to maintain data accuracy, consistency, and real-time monitoring. Here’s how we made it work:
Automated customer review extraction:
Grepsr provided the client with a fully automated solution for daily review extraction of their own products from Amazon and Best Buy.
Our infrastructure ensured that data was consistently collected without the need for manual intervention, providing the client with up-to-date customer feedback every day.
Additionally, our customer success team facilitated ad-hoc extraction of competitor reviews, giving the client the ability to compare sentiment across the market.
Alert system for data inconsistencies:
To address the issue of frequent review removals, Grepsr implemented an alert system that monitored review counts in real-time. If the system detected a 5% drop in review count compared to the previous day, the run would automatically stop. This ensured that anomalies or missing reviews were flagged immediately.
Many times, no fixes are required, as the drop in review count may simply be due to reviews being removed from the site. When an alarm is triggered, the QA team will verify whether it’s a true or false alarm.
The client can then ensure that the data they receive is accurate and reliable. By verifying whether a drop in review count is due to actual site changes or other anomalies, we prevent unnecessary errors or confusion and provide clean, trustworthy data for their decision-making.
Data completeness and accuracy monitoring:
With the alert system in place, whenever it detected a 5% drop in total reviews, the extraction process would automatically halt.
This proactive approach prevented the delivery of incomplete or inconsistent data, and the data would only be delivered after the anomalies were verified and resolved where required, ensuring the final dataset was complete and ready for analysis.
Real-time insights:
The automated extraction and delivery system provided real-time tracking of review counts, ensuring the client always had access to current insights. By automatically addressing data anomalies, we allowed the client to receive timely and consistent insights for more informed decision-making without delays.
Impact on Business
The solution had a significant impact on the client’s ability to collect and analyze customer feedback, providing numerous business benefits.
Improved data integrity:
With Grepsr’s automated customer review extraction and alert system in place, the client was assured that the review data they received was both complete and accurate. The automatic halting of runs when data anomalies were detected prevented the delivery of incomplete information, ensuring only reliable data was processed.
Increased efficiency and time savings:
By eliminating the need for manual monitoring, the client saved valuable time. The automated system provided real-time tracking and ensured data integrity without requiring manual oversight, allowing the team to focus on more strategic tasks.
Faster decision-making:
The real-time insights empowered the client to make timely decisions about product improvements and marketing strategies based on the most current customer sentiment data, without waiting for manual checks to be completed.
Seamless integration with business processes:
The seamless integration of review data into the client’s existing analysis tools enabled continuous, automated processing of customer feedback. This made it easier for the client to incorporate insights into product development, marketing, and customer service strategies, ensuring a more efficient workflow and faster response times to market demands.
Struggling with inconsistent review data or time-consuming manual monitoring?
Grepsr provides automated data extraction and intelligent alert systems, delivering complete, accurate, and real-time insights to your team. Make faster, data-driven decisions with confidence and stay ahead of the competition.
Contact us today to automate customer review data extraction!
Shaping a prosperous future with data-driven decisions
How Proactive Communication Scaled a Product Data Extraction Project for a Dental Supplier
The dental products retail industry is thriving in the online business sector. As more dental professionals turn to digital platforms for sourcing products, those who can harness the power of big data are gaining a competitive edge. One of the most effective ways to leverage this data is through product data extraction—the process of automatically […]
How a Travel Startup Powered Its Booking Intelligence System with Grepsr’s Real-Time Hotel Data Extraction
In the travel industry, booking data is the pulse that reveals how markets move. It captures the patterns of demand, competition, and consumer intent like who’s booking, where, when, and at what price. This information fuels dynamic pricing, helps forecast occupancy, and enables travel platforms and hotels to anticipate market shifts rather than react to […]
How ESG Advisory Firms Can Leverage Automated Article Extraction for Smarter Insights
Government websites and official press releases are goldmines for ESG (Environmental, Social, Governance) intelligence. Every update – whether it’s a new regulation, policy amendment, or court directive can shape how ESG advisory firms advise their clients. Yet, these updates are scattered across hundreds of government portals, each with its own format, language, and publishing schedule. […]
Seamless Vehicle Data Extraction for a Leading Automotive Intelligence Provider
In the automotive industry, having access to comprehensive, real-time vehicle information is essential for making informed decisions. However, gathering this data from online sources comes with many challenges, such as security barriers, IP restrictions, and complex firewall configurations. These can significantly disrupt the flow of critical data needed to support key business operations. In this […]
High-Coverage POI Data Extraction For Powering FMCG Market Strategy
Finding the right retail locations is a lot like navigating a city without street signs – you might eventually reach your destination, but not without wasted time, missed turns, and lost opportunities. Points of Interest (POI) data acts as those street signs, offering clear visibility into where consumers shop, dine, and gather. For global brands […]
POI Data Enrichment for a Leading Hospitality Management Company
Data is valuable, but enriched data is priceless. Data enrichment is the process of adding value and further information to an existing dataset to improve its quality, accuracy, and completeness. It involves taking raw, incomplete data and enhancing it with additional and meaningful information from external sources. It turns a basic dataset into something richer, […]
Location Intelligence in Retail: Real Use Cases From Grocery Stores
Do you know what separates successful retailers from the ones that are closing down? One key factor is using location intelligence in retail to make informed decisions. Modern retailers scrape the internet to find out competitor store hours, demographic shifts, and foot traffic patterns to find impactful location strategies. And the numbers back it up. […]
How Web Scraping Saved a Vehicle Data Platform
How Grepsr rescued a vehicle data platform from a major OEM block—restoring 100% uptime, 99.9% data accuracy, and real-time API performance for VIN checks and insurance quotes.
Mapping LA Wildfire Impact with POI Data
POI data extraction and reverse geocoding transformed wildfire impact maps into precise addresses, enabling targeted disaster relief.
How a Real Estate Agency Gained Competitive Intelligence with Real-Time High-Quality Datasets
Gathering structured real estate data from various government sites and public records at scale poses significant challenges.
Unraveling Job Market Dynamics: Leveraging Data Analytics for Competitive Edge
The notion of hiring the “right” candidate needs clarification of what’s “right” for your organization. Starting from the alignment of values, motivation, ambition, and technical skills required for the position.
Introduction to Web Scraping & RPA
Web scraping automatically extracts structured data like prices, product details, or social media metrics from websites. Robotic Process Automation (RPA) focuses on automating routine and repetitive tasks like data entry, report generation, or file management.
Car Rental Data Unwrapped: Merry Miles and the Christmas Story in the UK
Delve into the festive drive as we analyze 50K+ car rental records from ‘Sixt – Rent a Car’ during December 2023. From the holiday surges on Christmas Eve to discovering budget-friendly gems like the Kia Picanto, come with us as we decode the Merry Miles of Christmas car rentals in the UK.
NYC POI Data Dynamics: Decoding Impermanence
Geographical locations or POIs are not entities that last for posterity. We collected NYC POI data to decode the various dynamics that may help executives make informed decisions within the backdrop of impermanence.
Revving Up for E-commerce Success in Q4: Leverage Web Scraping
Inflationary pressures, rising prices, and the looming possibility of an impending recession have dealt an unwarranted blow to e-commerce sales over the last three quarters.
Harnessing POI Insights: The Web Scraping Advantage
Points of Interest (POIs) are more than just points on a map. They are filled to the brim with actionable data like addresses, names, contact details, and working hours. POI data also includes images, which add a visual component to the data. With web scraping, you can get the advantage you need to harness POI insights.
Top Six E-commerce Datasets: Web Scraping Use Cases
The irreversible rise of e-commerce has been a similar phenomenon around the world. In 1998, the entirety of the e-commerce market stood at just $5 billion.
Analyzing US Job Postings Data to Understand Job Market & Economy
The US economy was forecast to spiral into a recession in 2023. Yet, despite fears, if current job listings and hiring trends are to be believed, the current economic reality appears to be quite different. The robust nature of the current US job market is proving to be one of the main drivers of the country’s strong economy.
Enabling Market Expansion: Data Refinement at Grepsr
Any data is only as good as the insights derived from it. However, before we begin the analysis, the data must be put through adequate pre-processing techniques that standardize, aggregate, and categorize the dataset.
Impact of Shipping Data in the Shipping Industry
Before the pandemic, the global supply chain relied on predictable inventory flows. There was high schedule reliability, which meant the carriers usually followed the same schedules. This ensured the arrival of inventory in time, replenishment of stores, and constant operation of the factories.
