The sales productivity platform SMBs and startups actually love.

Digitalization has opened up multiple channels for companies to reach out to their potential clients and target audiences to expand their reach. However, manual and traditional marketing methods are less effective when clients expect personalized and unique campaign strategies. As a marketing company, imagine creating personalized marketing campaigns for each of your leads to showcase your expertise with a motive to convert them into your client base.  

Sounds too time-consuming, right? One of our clients faced the same thing who caters to dental institutions to enhance their online presence and boost conversion rates using digital marketing tactics. Targeted podcasts are emerging as a powerful tactic to gain consumer’s attention and increase engagement rates.  

Dental clinics often struggle with time-consuming podcast creation and high costs. However, this process could be digitalized entirely and drive revenue growth with AI-based data scraping solutions.  

Project Overview‍

The client’s primary objective was to create personalized landing pages for dental care organizations and clinics. They wished to feature tailored podcasts that described each institution on the landing page.  

While business automation with AI can streamline the creation of landing pages for personalized marketing, the main challenge lies in producing high-quality, cost-effective, and dynamic podcasting.

Below, we combine challenges related to manual podcast recording and data extraction for automated podcast creation.  

Challenges in Podcast Recording and Production

From issues faced in podcast recording and production processes to collecting data of dental organizations, here are the challenges that lead to the development of dynamic podcasting solutions:

1. Balancing Information with Promotional Content :
   Dental consumers prioritize informative content over promotional material, which makes it crucial to craft value-driven and engaging narratives. In a Pew Research Center podcast listener survey, 74% of all podcast consumers also stated that the main purpose of listening is to learn new things, indicating a clear preference for content with teaching objectives.
2. Maintaining High Production Standards : 
   Issues like poor sound quality, background noise, and inconsistent audio levels can reduce listener engagement by a great percentage. Post-production editing is also a significant component of podcast production costs. It often requires substantial time and resources.
3. Expensive Setup and Resource Allocation :
   Professional podcasting equipment costs can vary widely. On the low end, you can use a simple USB microphone that costs $50. From there, you can spend up to $2,000–$3,000 on studio-grade microphones and audio mixers. These expenses make manual podcast production unsustainable for businesses aiming to scale operations.
4. Time-Intensive Manual Processes : 
   Creating and editing podcasts manually can take 20–40 hours per episode. It leads to massive and annoying delays in campaign launches and limits scalability.
5. Data Collection Complexity : 
   Approximately 98.9% of all websites use JavaScript as a client-side programming language, which can complicate data extraction through conventional methods. Besides, most of the time, the data we need are enclosed in PDF or HTML format with inconsistent structures, which makes organizing the data for podcast production difficult.
6. Non-Standardized Terminology : 
   The use of different terms by different websites complicates the formation of a standardized database. Such variability does not present a well-defined standard for structured information extraction and, therefore, results in errors. To achieve effective message sending and receiving, ensuring data duplication is avoided and maintaining the completeness of the received data becomes vital.
   
   Podcast data duplications or missing values distort the accuracy and quality of mouth podcasts, which in turn requires extra data cleaning & validation episodes.
7. Time-Intensive Data Scraping : 
   Collecting data through multiple dental clinics can be tedious and cumbersome. This leads to prolonged delays in campaign launches and implies many operational complexities. Solving these issues implies establishing a plan of work that can help choose the best technologies for effective data gathering, decrease production costs, and improve the quality of the content.
   ‍
   These challenges are common, and they also hindered our client’s efforts and impacted their podcast recording and production processes.‍

Conclusion

With the help of automated podcast creation, businesses can ensure continued, consistent and constant steady revenue growth with the quality and degree of personalization that these advertisements will need to keep dental readers interested.

Relu’s team can also transform your business into an effective, fully scalable market using the power of AI podcast solutions. Take the next step toward innovation and growth today!

Technology Used to Create AI-Powered Dynamic Podcasting

Solution

Airtable | Python | OpenAI API | NotebookLLM| React  

Our Strategy for Creating High-Quality Podcasts

Here’s how Relu designed and implemented an agile and intelligent dynamic podcasting tool that includes data collection and podcast generation.

• We employed Python scripts such as BeautifulSoup and Selenium to scrape data from dynamically loaded and complex website structures common with JS-dynamic content, achieving 95% accuracy.  

• The extracted data was curated by removing duplicates and applying data validation rules; missing values were handled using AI algorithms' missing value functions.  

• These findings were then translated into another data organization structure format that fit podcast specifications and classified into structural databases that facilitated querying and integration, employing Airtable and relational data warehouses.  

• OpenAI API was used to generate personalized scripts while ensuring consistency and quality in the language used.  

• For podcast production, data was encoded in JSON and CSV formats for NotebookLLM-compatible bulk podcast script generation.  

• The final audio was created using NotebookLLM, where the voices were auto-generated and auto-refined.  

• Moreover, React frameworks were employed to develop fully functional landing pages with integrated podcasts to increase click-through rates and retention for dental clinics.

Results and Impact

‍

Relu’s dynamic podcast solution, powered by advanced AI tools, the client achieved the following measurable results:

• (Number of) personalized podcasts produced within three months compared to six months using traditional methods.

• There was a (percentage) increase in user retention rates, a (percentage) boost in listener retention, and a (percentage) rise in click-through rates on landing pages.

• Annual cost savings of (amount) USD, achieved by reducing reliance on manual labor, expensive equipment, and post-production editing.

• Scaled operations to serve (number of) dental clinics annually, significantly enhancing engagement and revenue growth.

Why Switch to an Automated Podcast Solution?

Any business can benefit from an automated AI podcast solution by leveraging advanced technologies such as Python, NotebookLLM, OpenAI API, and React. This solution automates the entire process from data extraction to final podcast creation, eliminating the need for manual intervention.  

The use of AI podcast solutions relieved many endeavors and operating costs that defined the creation of podcasts earlier. Key benefits included:

1. Efficient Data Collection : 
   When it came to issues surrounding scraping dental office websites, Python scripts, and AI algorithms proved useful in sidestepping those problems with JavaScript. We also learned that processing and normalizing information from dental organizations which are often embedded in PDFs or messy HTMLs, AI-driven data scraping and algorithms provide high data cleaning accuracy.
2. Cost Reduction : 
   Since podcasting was fully manual before working with the client, the automated implementation allowed the client to cut around (USD amount) in equipment and editing costs per year, a huge decrease in operating costs. Through automation, manual labour time was cut by 60%, allowing the team to prioritize more on a higher-value area of work.
   

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.

‍

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

‍

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

‍

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.
  ‍
• 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.
  ‍
• 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.
  ‍
• 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.