Dashboard with Web Scraping Customer Reviews

@glanegonsalves

Hey there Glane here, hope you're doing well. I can help you in scraping the data doing sentiment analysis and displaying the same on web ui via streamlit. Feel free to get in touch.

@zafarfarooq612

Hello, I can scrape and structure your customer reviews end-to-end, delivering a clean, analysis-ready Excel workbook plus a clear dashboard that highlights positive vs. negative sentiment. I’ll extract review text, post dates, and location details directly from the live HTML, remove all markup and formatting noise, standardize dates to YYYY-MM-DD, deduplicate records, and organize everything into well-labeled columns. Using a reliable scraping stack (Python with BeautifulSoup/Scrapy or Playwright where needed), I’ll then apply sentiment analysis to classify reviews and build an easy-to-read Excel dashboard that lets you quickly spot trends and problem areas. Accuracy is a priority—I’m comfortable with spot-check validation and will ensure the final .xlsx matches the live site precisely so you can start analyzing immediately. Regards, Zafar

@JaibhanSinghGaur

Hi, I can scrape all customer reviews from the site, clean and deduplicate the data, and deliver a well-structured Excel file with Review_Text, Review_Date (YYYY-MM-DD), City/State, and ZIP Code. I’ll also create a simple dashboard with sentiment analysis (positive vs negative reviews) for quick insights. I can use Python with BeautifulSoup/Scrapy or Playwright depending on the site structure, ensuring accuracy and completeness. Ready to start immediately.

@dtk507

Hello! I understand you're looking to extract customer reviews from HTML pages into a structured Excel workbook for analysis. I've successfully executed similar projects, producing clean, actionable datasets that facilitated insightful dashboards for clients in the past. ****My Plan****** - Utilize Python with BeautifulSoup or Scrapy for efficient data scraping. - Extract Review_Text, Review_Date, and Zip_Code, ensuring no stray markup remains. - Clean and deduplicate the data before final formatting. - Create a comprehensive .xlsx file with clear columns ready for analysis. - Develop a dashboard visualizing the sentiment analysis of both positive and negative reviews. Could you please confirm if there are any specific visualizations or metrics you'd like to see in the dashboard?Regards, Davide

@mahirshaikh88

Hi, I can scrape all customer reviews from the public HTML pages and deliver a clean, deduplicated Excel workbook with clear columns: Review_Text, Review_Date (YYYY-MM-DD), City, State, Zip_Code, and Source_URL. I’ll remove all stray markup/line breaks and ensure consistent formatting so your spot-checks match the live pages. Along with the dataset, I’ll build a simple dashboard inside Excel (pivot/charts) to analyze positive vs negative reviews, including basic sentiment scoring and filters by date/location. I’ll also provide the repeatable script + README so you can rerun the scrape anytime. Share the website link(s) and I can start immediately.

@chiragardeshna

Hi there, I am a strong fit for this task because I have built reliable scraping and analysis pipelines that turn messy public HTML data into clean, analysis-ready datasets. I have direct experience extracting reviews, dates, and location fields, deduplicating records, normalizing formats, and validating accuracy against live pages. I work with Python using BeautifulSoup or Playwright for scraping, pandas for cleaning and Excel export, and sentiment analysis libraries to classify positive and negative reviews. I reduce risk by implementing strict selectors, idempotent scraping runs, validation checks, and spot-check scripts to ensure consistency and completeness. I am available to start immediately and can deliver the Excel file and dashboard ready for review and analysis. Regards Chirag

@wilfrednjorog

Hi there, I’m excited about the opportunity to scrape and analyze customer reviews for your project! With extensive experience in Python and web scraping using BeautifulSoup, I can effectively collect, clean, and structure your data into a well-organized Excel workbook. My approach will ensure that all necessary elements, including Review_Text, Review_Date, and Zip_Code, are accurately captured and formatted for your dashboard creation. I'll also perform sentiment analysis to clearly categorize reviews as positive or negative. Thanks,

@ducthodg

With over a decade of diversified programming experience and proficiency in various languages including C++, Python and VBA, I am confident that I can deliver an efficient and precise web-scraping application tailored to your needs. My thorough understanding of data structures combined with my command over web scraping tools such as BeautifulSoup and Scrapy is a testament to my capability. Moreover, my industrial engineering background ensures data's cleanliness, consistency, and overall integrity throughout the extraction process. I understand the cruciality of comprehensive information for your dashboard analysis which is why I ensure zero stray markup or line breaks in your final Excel file, enabling you to use the data immediately without any hiccups. Lastly, my extensive experience with Excel will be invaluable for you in terms of structuring your dashboards for sentiment analysis. In addition to providing clear columns as per your requirements- Review_Text, Review_Date (YYYY-MM-DD), and Zip_Code- I can assist in creating useful insights based on positive/negative reviews. My commitment to quality and precision promises prompt accomplishment of the task while ensuring complete satisfaction at every step. I look forward to joining hands with you in this project!

@KirtikaKataria

Hi there, I understand you need all customer reviews from a public website extracted, cleaned, and structured into an Excel workbook for immediate analysis. Each review must include the text, posting date, and ZIP code, with all HTML markup and line breaks removed, ready for use in a dashboard. Additionally, you require sentiment analysis to distinguish positive and negative reviews. My approach is to use a reliable scraping method, such as Python with BeautifulSoup or Playwright, to systematically extract all reviews while maintaining accuracy and order. I will clean and deduplicate the data, format the dates consistently as YYYY-MM-DD, and ensure ZIP codes, cities, and states are correctly aligned. After that, I will build a user-friendly dashboard in Excel or Power BI that visualizes trends, highlights negative versus positive reviews, and allows interactive filtering by location or date. Deliverables: A fully structured Excel workbook with Review_Text, Review_Date, Zip_Code, and sentiment classification, and a clean, interactive dashboard for quick analysis of review trends. QUESTION: Would you like the sentiment analysis to be simple polarity-based or include nuanced scoring and categorization? If you want a comprehensive, analysis-ready extraction and dashboard for your customer reviews, I’m ready to start immediately. Regards, Shehwani.

@sadam61

Hi there, I’m excited about your project! With over 9 years of experience in Python development, particularly in web scraping and data processing, I can efficiently extract customer reviews from the HTML pages and format them into a clean, structured Excel workbook. I've successfully completed similar projects, ensuring data consistency and clarity. I will employ BeautifulSoup or Scrapy to achieve accurate scraping, ensuring the final .xlsx file includes clear columns for Review_Text, Review_Date, and Zip_Code. Additionally, I'll implement sentiment analysis to categorize reviews based on their positivity or negativity. I can start immediately and work diligently to meet your expectations, delivering comprehensive results within 5 days.

@craigd43

With my extensive experience in web scraping and data processing, I'm confident I can tackle your task of extracting and organizing customer reviews impeccably. My skills with Python, Scrapy, BeautifulSoup would ensure a reliable, accurate scraping process resulting in a clean and deduplicated Excel file that incorporates all crucial review details; Review_Text, Review_Date (YYYY-MM-DD), and Zip_Code; exactly as you require. In addition to the technical aspect of this project, I'd like to emphasize my expertise in Data Analysis and Visualization which will be instrumental in generating your desired single-dashboard presentation. To help you better understand the customer sentiment trends, I will also include sentiment analysis for both negative and positive reviews. Being a proficient user of Excel, I will ensure the final workbook is well-organized, easy to analyze and the data is ready for immediate use. I am excited about this project as it aligns perfectly with what I do best – extracting value from raw complex data through smart coding. My strong commitment to delivering quality work on time would ensure consistency and completeness while also accommodating any future adjustments you may need. With me onboard, you can trust that not just 5% but entirety of your data will be thoroughly validated against the live pages. Let's join hands in making this dashboard a game-changer for your business!

@ryans084

Hello, sir As a seasoned full-stack software engineer, I bring unique abilities and insights to your project that will ensure unrivaled quality and efficiency. With 8+ years in the industry, I have honed my skills in Python, web scraping, and automating data extraction from HTML pages like what you require. The thoroughness with which you seek to mine and organize your customer reviews map impeccably with my deep understanding of backend development and deduplication techniques. In addition to proficiently executing traditional development tasks, I’m also comfortable implementing AI-powered solutions. This can come in handy for running sentiment analysis on the collected review data to distinguish between positive and negative feedbacks as well as creating a reliable dashboard for visualization and intuitive analysis—a combination that can add immense value to your business decision-making process. Moreover, I believe that excellent coding should go hand-in-hand with effective communication and total accountability. Rest assured that not only will your reviews be accurately sorted into the required Excel workbook but you will also be kept abreast of every task and milestone reached. I genuinely care about the impact of my work beyond just lines of code, and selecting me guarantees a partnership where your goals become my own. Let's get started on making valuable dashboards out of your customer reviews!

@razqa16

saya seorang profesional yang telah mempunyai pengalaman bekerja lebih dari 8 perusahaan besar di berbagai bidang

@Mayanks010

Hi there, You’re absolutely in the RIGHT PLACE. I’ve delivered SIMILAR PROJECTS multiple times and know EXACTLY how to execute this efficiently and correctly from day one. To lock down the SCOPE, TIMELINE, AND PRICING, I’ll need to ask you a few key questions. Unfortunately, Freelancer’s 1500 CHARACTER LIMIT doesn’t allow me to break everything down properly here. Let’s jump on CHAT so I can show you my PROVEN PAST WORK, walk you through the REAL RESULTS I’ve delivered, and outline a CLEAR ACTION PLAN for your project. You’ll immediately see why my approach is DIFFERENT and EFFECTIVE. If you’re serious about getting this done RIGHT, I’m ready to move forward. Looking forward to CONNECTING and WINNING TOGETHER. Cheers, Mayank B

@alexismanuelt

I currently perform data analysis at my company, such as information visualization using PowerBI, SQL, and Python tools. I guarantee a job well done according to the specifications you share with me later.

@baskarrajendran

Hello, this is a clear and interesting data project, and I’m curious to help you turn these reviews into clean, analysis-ready insights. I can scrape all customer reviews from the provided HTML pages, extract review text, posted date, city/state/ZIP, clean all markup and line breaks, and store everything in a well-structured Excel file with clear columns: Review_Text, Review_Date (YYYY-MM-DD), City, State, Zip_Code. I will also fully deduplicate the data to ensure accuracy. For scraping, I’ll choose the safest method based on the site structure (BeautifulSoup, Scrapy, or Playwright if dynamic loading is used) so no reviews are missed. Deliverables you will receive: • One fully cleaned and deduplicated Excel (.xlsx) file • Sentiment analysis for positive and negative reviews • A simple dashboard in Excel showing trends, counts, and comparisons • Well-organized columns ready for further analysis I will also validate data consistency and do internal spot checks before delivery, knowing you will verify 5% against live pages. I’m comfortable handling pagination, multiple URLs, and large datasets, and I focus on accuracy, not just fast scraping. Once you share the review page URLs, I can quickly confirm the structure and start building the scraper.

@msaqibimran

Hello, I can turn your HTML based reviews in multiple files into a single Excel file. All I need is those HTML files. I am available to start as soon as you are ready. Best Regards, Mohammad

@shivanshs393

This is a clear and well-defined task, and I’ve completed many similar projects involving web scraping, data cleaning, sentiment analysis, and dashboard creation. I will scrape all live customer reviews from the public HTML pages using Python (BeautifulSoup/Scrapy or Playwright if needed). The extracted fields will include review text, review date (standardized to YYYY-MM-DD), and ZIP code (along with city/state if present). All data will be cleaned to remove HTML tags, line breaks, and duplicates, ensuring accuracy and consistency. The final output will be a fully deduplicated Excel (.xlsx) file with clearly structured columns ready for immediate analysis. I’ll also perform sentiment analysis to classify reviews into positive and negative, assign sentiment scores, and create an easy-to-use dashboard for visual analysis and insights. I’ve handled similar end-to-end pipelines recently, including a college recommender system project where I scraped review data, processed it with Python, and built analytical dashboards. This gives me full clarity on both data extraction and analysis requirements. I understand you’ll validate the data by spot-checking against live pages, so precision and completeness will be my priority. If this works for you, I’m ready to start immediately.

@viveksingh8290

I can scrape and clean all customer reviews from the provided HTML pages using Python (BeautifulSoup / Playwright), deduplicate the data, and deliver a well-structured Excel (.xlsx) with normalized fields. I’ll also build a sentiment analysis (positive/negative) and a simple dashboard for quick insights. Please share the review page URLs to proceed.