TikTok & Google Reviews Scraping

@malika335

I have done it before I have a solution ready to test for Building a robust, automated Python pipeline to efficiently scrape on-screen captions from specific TikTok URLs into clean .txt files, alongside a dedicated workflow to extract Google Business Profile reviews (text and date) into a structured format like CSV or JSON, is right in my wheelhouse. I regularly build advanced Python automation scripts, Web Scraping pipelines, and Data Extraction tools, so feel free to check my profile portfolio. Before we get started, do you already have a preferred premium proxy or scraping API service (like Apify or BrightData) you’d like to use to prevent rate-limiting, or would you like me to include a cost-effective recommendation in the documentation to ensure the solution remains functional beyond the handover? Once you share the details, I can map out everything cleanly and deliver the modular scripts, setup instructions, and a live demo step-by-step. Looking forward to working together! Best regards, Ahmad Hassan

@muneeb6767

Hey, this is exactly the kind of work I do day to day - anti-bot bypass, browser automation, and building scraping pipelines that keep running after handover. For TikTok: I'll pull each video with yt-dlp, grab the audio, and run it through Whisper (or the platform's own auto-caption track when it exists) to get a clean, correctly-ordered transcript, saved as one .txt per URL. Re-running for new links is a one-line change. For Google reviews: I'd go through a licensed reviews API (Outscraper or SerpApi's Maps Reviews endpoint) so it stays within policy and doesn't get blocked - pulls review text + date cleanly into CSV/JSON. Cost is usage-based, roughly $0.01-0.03 per review pulled - I'll confirm exact numbers once I know rough volume. I can have a working demo of both ready in 3-4 days, with a short recorded walkthrough plus docs on adding new URLs/locations later. Quick questions - roughly how many TikTok URLs and Google locations per run, and is this a one-off build or something you'll want running on a schedule? 44+ five-star reviews on my profile if you want to check my track record. Happy to start as soon as you're ready. Muneeb

@Jennycreation

Hello Sir, I have already worked on similar types of website and software development projects and I am confident that I can successfully handle your project. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * ASP.NET C# web and software development * Android app development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@WebXcellance

Hi there! I am a senior Web developer and I am ready to build reliable automation for your TikTok and Google review data requirements. I have 13+ years of experience in PHP and JavaScript and I am also familiar with Python, REST APIs, databases and third-party API integrations. I can create a simple Python-based workflow to process selected TikTok URLs and export transcripts as individual TXT files, and a separate solution to collect permitted Google review text and dates into CSV/JSON. I will focus on platform-compliant methods, rate limits and reliable error handling rather than unstable scraping techniques. I can also provide setup instructions and a screen-share/recorded walkthrough showing how to add new URLs and locations. Any required third-party API or SaaS licensing costs will be clearly identified before implementation. Please message me for more discussion about your project. This is just a placeholder price for now. We’ll discuss the requirements in detail and provide you with the final price accordingly. Thanks, Sachin.

@gopalkrgautam

Hey, I can provide a nice desktop or web application which does both tiktok and google reviews scraping for you. Best service, fast, and reliable. Lets connect and I would love to help you and you will love my work. thank you.

@MuhammadAkif8

Hello, I can build reliable Python automation for both TikTok caption extraction and Google review data extraction. The solution can process selected TikTok URLs into individual TXT files containing the captions, and export Google review text with the corresponding review dates in CSV or JSON format. My process will be to build the extraction workflows, handle rate limits and platform requirements, test both tasks with your supplied URLs and locations, then provide simple setup instructions and a demonstration of the complete workflow. Which TikTok and Google locations will you use for the first demo run? I will keep the solution easy to run and maintain, with clear documentation for adding new TikTok URLs and Google locations. I can also work with a suitable licensed API or tool if required. Best regards, Akif U.

@jiyayadav

As an experienced and versatile Python developer, my name is Sanjay Kumar of MSM CoreTech and I am confident that I have the skills and expertise to deliver on both aspects of your project. For the TikTok video captions scraping, I am knowledgeable in various data extraction methodologies and can create a script tailored to your specific needs. Furthermore, my proficiency extends to web scraping tasks such as the one involving Google reviews. My approach will focus solely on retrieving reviewer's text and corresponding dates for you; leaving out any unnecessary data like names. I will ensure the output is neatly organized in a format that suits you best, be it CSV, JSON or a database import. Finally, using my in-depth understanding of scaling digital products, your solution will not only meet your acceptance criteria but will remain functional beyond the initial handover, respecting TikTok's and Google's platform policies. With MSM CoreTech, you're not only paying for a completed project but for reliable service & support. Let's get started on automating these scraping tasks efficiently and successfully!

@Mobarak303

I can help build a reliable workflow for extracting TikTok captions and Google Business reviews according to your requirements. My approach: Create a simple automation/script to process TikTok URLs and export clean caption text files Build a Google Reviews extraction workflow that outputs review text with posting dates Provide clear setup instructions and documentation for future runs Include a demo showing the complete process I will focus on creating a maintainable solution that is easy to run whenever new URLs or locations need to be processed.

@Ahmadw208

Hi, What specific TikTok URLs do you want to scrape for captions? Also, could you share the Google Business Profiles you are targeting for reviews? I can create a custom Python script that will reliably extract on-screen captions from the TikTok videos and gather review text with dates from Google Profiles. I’ll ensure the output is in plain .txt files for TikTok and a preferred format for Google reviews, like CSV or JSON. I’ll provide a thorough setup guide and can do a demo run to walk you through the process. It’s essential that the solution works throughout, respecting platform policies. With over 2 years of experience in web scraping and automation, I’m confident I can deliver what you need efficiently. Let me know how you’d like to proceed! Best Regards, Ahmad

@linhitdcn

Hi, I can build a reliable Python-based automation solution for both TikTok caption extraction and Google Reviews collection. For TikTok, the tool will accept a list of video URLs, extract the available spoken captions/transcript in the correct order, clean unnecessary metadata, and save each result as a separate .txt file. For Google Business Profiles, I will build an extractor that collects only: * Review text * Review date The results can be exported to CSV or JSON in a clean structure ready for further processing. My approach will prioritize official/licensed APIs or compliant third-party services where appropriate, with a fallback architecture so the solution is easier to maintain if platform behavior changes. Deliverables: * Python source code for both workflows * Batch URL/location processing * Clean TXT/CSV/JSON output * Error handling and logging * Rate-limit handling * Setup and usage documentation * Demo/walkthrough * Clear information about any paid API/SaaS costs before implementation I have 10+ years of software development experience and work with Python, APIs, web scraping, data processing, automation, OCR, and AI-based document processing. I can start by testing a small sample of TikTok URLs and Google locations to confirm extraction quality before completing the full solution. Best regards

@abhayautomation

Hi, I can help you build both scraping workflows using Python + Playwright browser automation. 1. TikTok captions → .txt files For this, The script will take a list of TikTok URLs, open each video, extract the available captions/transcript, clean the text while keeping the correct order, and save one .txt file per video. Adding new videos will be simple—just update the input file and run the script. 2. Google Reviews → CSV/JSON I’ve already worked on Google Business Profile review scraping and have a Playwright script ready, so I mainly need to customize it for your requirements. I’ll extract only the review text and date, skip unnecessary data, handle pagination, and export it to CSV or JSON. What You’ll Receive: • User-friendly SaaS interface where users can add URLs/locations, start the process with one click, and download the generated files. • Easy setup with input examples • Short demo/walkthrough • Clean, maintainable source code If you’d like, I can also provide a small demo/sample of my approach. Thank you!

@eternitech

Hi, New on Freelancer — 20 years of development experience behind us. We're taking our first few projects here at a fraction of our normal rate purely to build our review history. You get senior agency work at junior pricing; we get a review. Straight trade. to effectively automate scraping TikTok video captions, using TikTok's API with Python scripts can ensure consistent data extraction without violating terms. For Google Reviews, using a proxy service might prevent IP blocking during data retrieval. Can you specify if you have existing API keys or need assistance obtaining them?

@EthanKCK

Automating the extraction of TikTok captions and Google reviews can significantly enhance your workflow, ensuring you have the data you need at your fingertips. I can provide a reliable solution tailored to your requirements. For TikTok, I will create a custom Python script that pulls on-screen captions from specified URLs and saves them as .txt files, ensuring each file contains only the necessary text. For Google reviews, I will implement a method that extracts review text and dates, outputting the data in your preferred format, whether it’s CSV or JSON. To ensure smooth execution, I will include clear setup instructions and a short demo run on your machine, ensuring you can operate the solution independently. All work will be thoroughly tested for accuracy and compliance with platform policies before delivery. Please feel free to reach out so we can connect and further explore how I can contribute to your project's success. Kind regards, Ethan

@hyoungdoonk

The part most bids will get wrong is what "TikTok captions" means. There are two different things: the subtitle/CC track TikTok serves with the video (cheap, reliable to pull), and words burned into the frames or only spoken (needs speech-to-text). I'd pin that down before writing code - it changes the whole approach. Plan: 1) TikTok - if a caption track exists, pull it directly: one clean .txt per URL, captions only, in order. If spoken/on-screen, transcribe the audio with Whisper, which stays accurate when TikTok changes its page. 2) Google reviews - instead of a scraper that dies at the next layout change, use a paid reviews API (Outscraper/SerpApi) since you're open to licensing cost. Output: review text + date, CSV or JSON. I'll quote the exact per-run cost up front. 3) Recorded walkthrough + docs so you can add URLs/locations yourself. Honest note: both platforms discourage raw scraping, so I lean on caption tracks and licensed APIs - that's what keeps it working beyond hand-over, as you asked. Two questions: - TikTok captions: the CC track, or spoken/on-screen words needing transcription? - Roughly how many URLs and Google locations per run? Milestones: (1) TikTok .txt export on your sample URLs. (2) Google reviews export + walkthrough and docs. I work in Python; small, well-scoped automation like this is exactly what I build.

@bitfumes

Hi, I can build both scrapers exactly as described: 1) TikTok captions - a Python script that pulls each video's on-screen caption/transcript from a URL list and saves one clean .txt file per video, in order. 2) Google reviews - a script hitting the Google Places API to export review text + post date (no reviewer names) to CSV, ready to point at new Business Profile IDs later. Plan: Day 1: Build + test the TikTok caption extractor on your sample URLs Day 2: Build + test the Google reviews exporter, write short setup docs, record a screen-share walkthrough, handover I build Python/API automation pipelines day to day (AI agents, LLM tools, API integrations at Bitfumes), so this fits squarely in my regular work. If the Google Places API has usage costs at your review volume, I'll flag that separately upfront - no surprises added to my fee. Could you share 2-3 sample TikTok URLs and a Google Business Profile link so I can confirm the caption format and start immediately once awarded?

@joharashu0

With my expertise in API integration and extensive experience in building custom scripts, I'd be the perfect fit for automating your TikTok and Google reviews scraping tasks. I have a proven track record of developing reliable applications and systems—the kind you're looking for. My proficiency in Python, especially with web scraping libraries, combined with my ability to efficiently work with APIs makes me well-equipped to handle this project. Over the years, I have honed my skills in not just building functional tools but also in making them user-friendly and easily maintainable. So, you can rest assured that the solutions I provide will be user-intuitive and accompanied by lucid documentation explaining the process from setup to ongoing use. Additionally, let me highlight that respecting platform policies will be my utmost priority throughout this project. I understand the importance of complying with usage restrictions and ensuring long-term functionality. Therefore, apart from providing a working script or method for each platform, I’ll also furnish any relevant information about rate-limit considerations or any other dependencies to ensure the longevity of this solution.

@AlonzoLeeeooo

Hi, To extract TikTok captions and Google reviews, I can build a Python workflow that outputs ordered caption-only TXT files per video and structured CSV files with review text and dates per Google location. The delivery includes deployment documentation, resilience controls (e.g., retries and rate-limiting), and a remote walkthrough. For the first milestone, I can complete a feasibility check and deliver sample exports (3 test videos and 2 locations) within two days. For captions, I will first verify whether native transcript tracks are available or whether burned-in text requires an OCR fallback. For Google reviews, we will confirm an authorized access route or licensed provider upfront, with any third-party service fees itemized for approval once URL volume is finalized. I hold a PhD in Engineering and authored 10+ peer-reviewed papers in multimodal large language models and computer vision. Recently, I built an automated text extraction pipeline for mixed media sources using source-specific parsers, timestamp ordering, and error logging, eliminating manual cleanup. This modular structure applies directly to your project for caption sequencing and date-ordered review extraction. If this technical direction aligns with your vision, let's have a quick chat to finalize the milestones.