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How to boost your E-Commerce Sales with Automated Product Listings?‍

The project is about to achieve the goal of automating the product listing process. The user has a Shopify store and the challenge is to enhance the efficiency with data enrichment and automation. By using advanced data scraping techniques, Relu has provided a streamlined solution that saves time and increases client listing accuracy and quality.

Challenge

The client has a growing e-commerce business on Shopify. They struggled to keep the manual product data entry as the process was time-consuming and faced a lot of errors. The team was challenged by maintaining accurate and updated product listings, especially during the inventory expansion.  

Moreover, while enriching product data they have to add details like specifications, pricing, and description for each which is again a tedious process. A solution was needed to streamline the product listing and ensure consistency across the catalog.

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Universal support

Relu eCommerce automation solution is flexible and can be used in various e-commerce platforms. This approach is beneficial to other businesses facing similar challenges like catalog accuracy, and data management.

Relu Solution: Automated Product listing with Shopify data scraping

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Overview

The team implemented a Shopify data scraping solution that automated collecting, organizing, and enriching product data from multiple resources. We also built a custom scraper that extracts the essential product information and structures to match Shopify’s format. With this, we have also integrated data enrichment while adding details of products like descriptions, pricing, and tags. This gave a completed and cohesive product catalog and was ready for launch.

Custom data scraper development: A custom scraper was put into place to capture critical product information. it is then formatted according to Shopify unique product listing structure.

The scraper is used to integrate multiple data sources for a more holistic view of product details.

Enhanced product details: To improve customer experience, Relu has also incorporated data enrichment into the scraping process. This system will automatically add valuable information to the product like in-depth descriptions, comprehensive specification and optimized tags. This process enhances the product visibility on Shopify and also in search engines.

Results

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Overview:

Our eCommerce automation solution reduced the time and effort the client spent on product listing. The automated product listing also ensured the sharing of details of new products to the consumer at the right time. This automation ensures data accuracy, and up-to-date listings with minimal oversight.  

The demonstrated results of the product data scraping solution are adaptable to any e-commerce business facing the mentioned challenges. With the help of e-commerce data scraping by Relu, any business can benefit from increased efficiency and improved sales points.  

Reduced manual entry: With the automation of product listing, the client found a significant reduction in time and effort. This saving helped clients to focus on other critical areas of business.

Increased data accuracy and consistency: The automated scraping solution reduced the human error and led to preparation of accurate product catalog. This consistent listing gained customer trust and contributed significantly in effective inventory management.

Better customer experience: The enriched data helped the customers to view comprehensive product information. This made shopping more informed and enjoyable. Moreover, automation ensures that new products are listed in real time giving immediate access to customers.

Project Overview‍

Over 75% of Americans face challenges in effectively managing their personal finances.  

Now more than ever, Americans want to gain greater and more detailed insights into their spending habits.

This case study explores how we helped mastercard  track and monitor daily credit card expenses, providing them with more visibility and control over their financial habits.

Objectives and Goals

Here are the key objectives and goals mastercard  wished to achieve with an advanced budget control solution:

• Our client wanted a clear picture of daily and monthly spending.  

• It was essential for them to understand their financial habits better and identify areas where they could save more.

• They wanted to reduce the time they spent manually tracking expenses. It would also free up more time to focus on their financial goals.  

Challenges and Pain Points

The client faced several challenges that highlighted the need for a more efficient budgeting tool. Some of these were:

• Inconsistent Expense Tracking: Manually tracking credit card expenses often led to missed entries and incomplete and incorrect financial records.  

• Complexity in Financial Reporting: The client couldn’t clearly understand their spending habits and how they aligned with their monthly budget.  

• Time-intensive Manual Processes: Our client’s ability to maintain an accurate budget was significantly impacted by manual recording.

Conclusion and Future Plans

Implementing an advanced and automated budget control and expense tracking system proved quite beneficial for the client. It helped them gain control over their finances and make proactive financial decisions. With the reduction in manual tracking tasks, they could focus on more important aspects of financial planning.  

Though we implemented this tool for an individual client, we can also tailor it for different organizational needs.  

Solutions Provided

To address these issues, we provided the following solutions:

• Automated Expense Tracking
  The client provided us secure access to their credit card expense data, giving us accurate insights into their financial habits and enabling the setup of an automated expense tracker. This automation was essential, as the client, a business owner with frequent travel, had varied spending across locations using a single card for both personal and business transactions. With automation, each transaction was recorded instantly, eliminating the risk of missing data and ensuring the client had a complete, accurate, and continuously updated expense record.
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• AI-Driven, Daily Expense Categorization
  We asked ourselves: How could we simplify this for the client? To make financial reporting more accessible, we implemented an AI-powered system to categorize transactions by expense type. Categories like ‘Entertainment,’ ‘Groceries,’ ‘Utilities,’ and ‘Travel’ were automatically generated, allowing the client to see a clear spending breakdown. This categorization also provided a detailed financial profile, helping the client understand their spending patterns and quickly spot high-expenditure areas, ultimately supporting their goal of informed budgeting and greater visibility into their habits.
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• Automated, Insightful Report Generation and Analysis
  Our system went beyond categorization, generating insights by analyzing spending patterns and pinpointing high-expenditure areas. The client wanted to eliminate manual tracking, so we introduced an automated daily email report, offering a concise, clear overview of spending patterns. This routine report allowed the client to passively monitor transactions, while our automation continued to track spending trends and identify emerging patterns, supporting their long-term financial planning goals.
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• Multi-Frequency Report Alerts
  To keep the client consistently aware of their spending, we implemented personalized daily, weekly, and monthly reports with alert notifications. These prompts made it easy to track short-term spending and observe broader trends, enabling the client to adjust spending as needed and supporting their long-term financial planning goals.

Results and Outcomes

The client achieved the following outcomes:

• Through the daily report, they noticed an average daily spend of $50 in the first month. This was broken down into different categories, such as groceries ($20), entertainment ($5), dining out ($10), etc. The client also made some occasional larger expenses, like $100 on weekends.  

• Our advanced budgeting helped them realize that by the end of the month, they had spent $1500 on their credit card. Out of this amount, $400 was spent on dining and entertainment when they had originally planned to spend $300 on these categories.

• Eventually, the client could adjust their budget and cut back on discretionary expenses the following month. It helped them save an additional $150. They also gained a clear understanding of how to reach their goal of saving $500 monthly.

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.