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Project Overview

Businesses like comic books are very niche markets. They are required to have access to up-to-date and accurate data. This keeps them competitive in the market and approaches the challenge better. Our client is a comic book retailer. He approached us with the challenge of streamlining the data sourcing.

The challenge area also includes poor inventory management and meeting customer demand. We implemented a comprehensive data scraping solution that allowed them to collect and organize the comic book data in real-time automatically. The challenges in detail and the solution by Relu are mentioned further for better understanding.

Challenges faced by the client

The challenges faced by the client are scattered to different areas of their business operations. The impact area is inventory, meeting customer demand levels, and competition. To come up with the solution we needed a present process scenario.

Firstly, the team was manually gathering the data from multiple distribution websites. This was both time-intensive and error-driven.

Secondly, the new comic book issue and special editions were constantly released. This created a hurdle to keep the inventory updated and make informed stocking decisions.

Thirdly, they manually extracted data, which gave them outdated and incomplete information.

Lastly, the lack of automation in the process made the entire transformation process slow for them in the event of any changes in comic book availability, reprints, or limited-edition releases.

Our Solution to their problems

To solve the challenges we designed a custom data scraping system that looked into the client’s needs first. This solution involved creating a web scraping tool that can gather live comic book data from different sources.

The solution also caters to the release date, pricing, availability, and special edition information. Relu also configured the tool to handle high-frequency updates. This allowed the client to access in real-time at the time of new releases and stock changes.

We equipped the system with useful filters that will capture relevant information and eliminate unnecessary data. This streamlined the process of inventory management.

In the end, we implemented an easy-to-use interface that helped the client to extract data in one structured format. This made the data analysis simpler especially at the time of identifying the trends and adjusting the inventory.

Results and Impact

Relu data scraping solution has measurable results for the client's problem. With live updates and accurate data on book availability to customer response, we reduced the missed sales opportunities.

This enhanced customer satisfaction rate and the client could offer new and in-demand comic book titles to them.

Moreover, the client noticed a reduction in the time spent on manual data entry. This gave time to most of their resources who can now focus on other strategic aspects of the business like marketing and customer engagement.

The solution also helped the client to prepare a tool that could adapt to future changes in the comic market, proving efficient data extraction is a powerful asset to any business.

Why can this solution work for any business?

The data scraping approach extends beyond the comic book industry. Businesses with fast-changing and updated products frequently need inventory updates and accurate information.

This solution is the blueprint for using data scraping to solve inventory issues, and customer management issues as well. With the list of solutions, businesses of all types can stay competitive by leveraging the data in their decision-making process.

Project Overview

Extraction and analysis of multiple reports is time-consuming, especially for 19 locations. Cameron Ray, the COO and Co-founder of Sparkle Express Car Wash Company, faced this issue. Relu stepped in to provide a solution that streamlined the extraction and analysis of operational and financial data, reducing Cameron’s workload.  

Company Background

Sparkle Express Car Wash Company offers top-notch car wash services in 19 different locations across the USA via their three different websites. The company relied on a manual process of data collection, extraction, and analysis.  

Challenges Faced By The Client

Sparkle Express Car Wash's distribution to 19 locations increased the number of reports to manage and analyze. The manual approach of recording and analyzing the data challenged the team with the compilation of revenue, labor count, and conversion from different locations. This not only took a toll on time but also introduced potential errors. Moreover, the key members couldn’t get the data at the right time to process as the company doesn’t have a dashboard.

Our Solution To The Problems

Relu Consultancy developed a custom script solution that automated data extraction from the three different websites used by Sparkle Express Car Wash. The solution then catered to three areas:

Data extraction scripts- The customized scripts pulled raw data from all the websites.

Data processing function- We introduced the functions to process the extracted data by generating it as per the metrics Cameron suggested such as ledgers, each location performance, and weekly reports from Monday to Sunday.

Automated report- We introduced an email function as well to send automated reports to all key members on Sunday. This clear approach helped key members with a clear overview of which location was performing well and which needed attention.

Results And Impact

The implementation of these solutions resulted in significant time savings and better data accuracy for Sparkle Express Car Wash Company.

The real-time data generation and weekly report helped them analyze each location's profit, performance, and areas of improvement. This solution is not only for streamlined operations but also a template that can benefit any business facing similar challenges in data management and reporting.

Relu Consultancy's solution gave Cameron and Sparkle Express Car Wash Company more time to focus on operations rather than report management and analysis. 

The challenge

The job market is huge and ever changing. Thousands of jobs are listed online, on various job portals every day. To list out these job alerts manually from job portals according to the requisite keywords, is extremely time consuming and tiring. In addition to this, it requires human resources exclusively dedicated to this work, which puts more financial strain on a firm.

Our client, suffering from the same issue, was looking for options to automate job listing based on keywords and organizations across different job search sites, primarily Google Job Search and welcometothejungle.com. The client wanted a job scraping tool, to scrap three main data points, the job title, the job URL, and the date when the job was posted, from these job search platforms.

The Solution

So, to simplify their search for employment opportunities, we came through with a job scraping software which would undertake web scraping on the websites mentioned by the clients in order to gather data on job listings in a simple, time and cost-efficient way.

Firstly, we created a job scraper bot to perform all the manual processes from searching for the companies and keywords on the listed job portals. We also built an API, which acts as a trigger that initiates the process.

Along with that, we integrated an n8n automation tool to give the process and environment a smooth and uninterrupted run. When the client clicks start in the n8n tool, it will initiate the process, and the scraper bot will run through the website and gather the required data.

When the scraper set is ready, the web crawlers start providing the data in the client’s required format. If the client provides the company name and keyword, the scraper will collect the job title, URL and data posted. If the company is not found, then it will give the result otherwise.

Advantages

• Swift Work Ethic: within a week we designed the technical aspects and set up the web crawlers, allowing the client to gather data in a shorter time.
• Industry Expertise: our hands-on experience in web scraping helped us design a solution that can quickly perform all the manual processes and control a vast amount of data.
• Affordable Alternative: the job scraper will be more affordable in terms of cost and time than the manual listing.

The challenge

If all the seller profiles are opened and checked manually, the task seems to be nearly impossible because of the huge number of sellers selling their products on bol.com.

The Solution

So, to fulfill their needs we developed a tool called ‘Bol scraper’ which automates the whole process of going through all the pages of the e-commerce website and extracting the details of the seller according to the client’s need. Bol Scraper is a GUI-based tool which means after the tool is delivered to the client, even a user without much technical knowledge can make changes to the parameters (such as the number of reviews, SKUs, and rating) for filtering out the sellers and operate it without any hassle. The client can either select the category through the UI which is to be scraped otherwise, he also has the option to scrape all the categories at once.

We use scrapy, a python-based framework, to scrape through all the pages of the e-commerce website. Along with that, we have integrated various extensions in the module to avoid getting blocked by the bol servers that may happen after making repeated requests for data within a small amount of time.

The scraper shows the details of the sellers meeting all the criteria in real-time as they are scraped through a table in the UI and the user has the option to export all the scraped data to a CSV file at any point during the scraping process.

Using this scraper, we were able to scrape more than 1000 subcategories from bol.com.

Advantages

• Thousands of pages can be scraped at once, allowing the client to gather data in a shorter time.
• The scraper can be used for lead generation and approaching different sellers according to the different requirements of the client.

The Challenge

There was a requirement of the details of golf courses which was all available on a website. If that data was to be used for any process, it was first required to be exported in a proper format from that website. This could’ve not been manually possible to do as there were hundreds of golf courses.

The Solution

So, this process was automated and details was extracted from the website and an approach was used to also include the latitudinal and longitudinal coordinates of the location of the golf course. It takes few minutes to extract the details of hundreds of golf courses in a format required by the client.

Advantages

• A lot of time and human effort is saved through this process.
• Another similar site can be scraped with minimum changes in the main script.
• The client can get or update existing data within minutes through this process.

The challenge

The client requested that we generate leads from a Taiwan-based e-commerce website called “Shopee.” Our client wanted to expand their business by providing their delivery service to the sellers selling their products on this particular website. Therefore, they asked us to extract a list of all retailers and their details so that they can extend their services to them. They also asked us to find the e-mail addresses and phone numbers to contact the sellers.

Because of the large number of sellers selling their products on Shopee, manually opening, and checking all of the seller profiles appears to be nearly impossible.

The solution

As a result, we used web scraping and web crawling technologies to automate this process. Our data processing technology assisted in extracting the data much faster and without making the targeted website suspicious. To find the contact information we used our in house email and phone number finder code so that our client can contact his customers easily. When the process was completed, we provided a list of seller names, along with their number of followers, joining history, rating, page URL, usernames, product category, number of products sold, number of items sold, email addresses, and phone numbers. We provided this information in an Excel file that the client could easily access.

The outcome

We were able to extract information from that website from around 700+ sellers thanks to this scraper. EZIE can now directly contact the potential sellers and broaden their client base with the scraped data. Web scraping saved a lot of time, money, and effort for all the parties involved by searching and analyzing every detail of the sellers. Given that the entire procedure is automated, this method also produced accurate data, which also makes it more reliable.

This web scraping service can be extended to any website or application. If you want to gather such information from any online business or website, just let us know and we’ll be happy to assist.

Why to use our web scraping service?

1. To enable dynamic pricing models in real-time, compare the costs of comparable items across all competitors.
2. Utilize competitive knowledge and expertise to completely transform your pricing approach.
3. Find the list price, selling price, and discount for every product at each rival’s current price.
4. For every SKU, find the exact match, and keep an eye on price changes. Chart each product’s price evolution.
5. Be informed of fresh discounts and offers.
6. Set the appropriate pricing for each SKU that is neither too high nor too cheap and applies to all channels and times.
7. Utilize real-time matching and product discovery to maximise your inventory.
8. Keep up with your own precise product profiles.
9. Find new markets for your items or categories.
10. Know as soon as your suppliers launch a new brand line so you can instantly add the SKUs to your website.
11. Extract all product information and gain access to the competitor’s product catalogue and inventory status
12. Measure consumers ’ opinions
13. Recognize changes in customer demand and rapidly pinpoint products that are becoming more or less popular with consumers.
14. Find out which products and sectors are popular in each country.
15. Verify design, variety, and merchandising choices to make sure the commercial offer is appropriate.
16. Recognize the obstacles potential clients confront by understanding their path.
17. Concentrate your marketing initiatives on top sales.