Budget: 1999 UAH Deadline: 2 days
contact us
Budget: 9999 UAH Deadline: 4 days
I suggest not only to simply parse products but also to simultaneously connect AI for rewriting unique descriptions, titles, and other elements of the product card. Additionally, I can provide consultation regarding GEO optimization for search through AI. I believe that in 1-2 years, SEO will take a back seat, so we need to prepare for this now. We can continue further in private messages.
Budget: 1000 UAH Deadline: 1 day
Good evening
I have previously collaborated with you
I am ready to perform this project with high quality
I have extensive experience in parsing online stores
Budget: 2000 UAH Deadline: 1 day
Hello! I can complete it by tomorrow (although, just in case, I need to know the website and what exactly to collect).
Budget: 3000 UAH Deadline: 2 days
Hello!
I can do it. I have extensive experience in parsing stores. (I am attaching my last work)
I will prepare a ready CSV for import into Shopify.
To provide an exact price and timeline, please provide a link to the store.
I can start immediately after reviewing the site.
Budget: 998 UAH Deadline: 2 days
Ready to perform this project with quality
Have experience working with product import on Shopify
Ready to discuss details and start working
Budget: 10000 UAH Deadline: 7 days
hello
provide a site to evaluate the work
should it be a parser that works on Windows or on a server?
Budget: 1000 UAH Deadline: 1 day
Hello Ivan, I will do the parsing of products and prepare it for import into Shopify. I have experience working with product import on Shopify. Write me a message, we will discuss the details. I will be happy to collaborate and get to know you.
Budget: 2000 UAH Deadline: 3 days
Hello!
Please provide a link to the website for review and evaluation.
I can complete your task by preparing the file for correct uploading and display in the Shopify store.
Message me privately.
Budget: 3000 UAH Deadline: 3 days
Good day, Ivan.
I am ready to perform parsing of 3000 products from your custom store. I will use reliable tools for web scraping to collect the necessary data. The result will be provided in CSV format, adapted for further import into Shopify. I will focus on the accuracy and completeness of the collected information.
Budget: 3000 UAH Deadline: 3 days
I have experience in parsing large datasets and preparing them in CSV format. I am ready to try to implement this project, agree on the necessary fields, and provide a correct file for import.
Budget: 1000 UAH Deadline: 1 day
Ivan, good day.
I have extensive experience in data parsing.
I will implement it without any problems.
Write to me, we will discuss the details.
Budget: 1000 UAH Deadline: 1 day
Hello.
I have completed a similar project. I will collect and format all the data for further use with high quality.
Budget: 1000 UAH Deadline: 1 day
Hello. I have experience in parsing.
I will implement a script in Python (Playwright/Aiohttp) that will collect all 3000 products and create a clean CSV according to your template.
I am ready to clarify the file structure and start.
Budget: 1000 UAH Deadline: 2 days
Good day!
I have extensive experience in web scraping of various complexities. My portfolio includes several projects related to product scraping, particularly in preparing and structuring data in CSV format for further import.
I am ready to accurately scrape 3000 products and create a correct .csv file according to Shopify's requirements (taking into account variations, descriptions, prices, SKUs, images, and other necessary fields).
I would be happy to discuss the project details.
Budget: 3000 UAH Deadline: 7 days
Good day. I perform website parsing. I will check for duplicate products. I will also format the output file in a format for Shopify. The budget can possibly be negotiated further if you provide a link to the donor site. Although overall the task is more or less clear. Have a good day!
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Budget: 1000 UAH Deadline: 1 day
Good day
I have extensive experience in data parsing.
To provide an accurate estimate, I need to see the website.
Feel free to contact me.
Budget: 2000 UAH Deadline: 1 day
Good day, Ivan
I can do it today
Write to me, I will be happy to collaborate. I will be waiting for feedback.
Budget: 1000 UAH Deadline: 3 days
Ready to complete this task, write to discuss the details. I will create a template for Shopify.
Budget: 3900 UAH Deadline: 1 day
Hello, I am developing scripts for website parsing. I parse data using both API and Selenium. I have parsed Pexels, SoundCloud, Government of Canada. You can see my work in the portfolio. I reviewed the technical specifications and can record data in any format. The first 1000 products will cost 1300 UAH. Please contact me.
Budget: 1500 UAH Deadline: 2 days
Hello. I am interested in your project. I am ready to discuss and complete it. I will create a file for import into Shopify, I have enough experience for this!
Budget: 2000 UAH Deadline: 1 day
Hello.
I develop parsers in NodeJS. I am ready to take on the task. Write to me, we will discuss.
Budget: 1111 UAH Deadline: 2 days
Hello. I can do it, I need to take a look at the website for evaluation, I will make the format as you need. Write to me, we will discuss the details.
Budget: 1000 UAH Deadline: 1 day
Regarding Shopify - I don't know which template, but I can parse everything qualitatively into csv/xls. Over 10 years of experience.
Regarding Shopify - I don't know which template, but I can parse everything qualitatively into csv/xls. Over 10 years of experience.
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Current freelance projects in the category Data Parsing
Good day! Two tasks need to be completed: 1. Develop a product parser from an external website (10–40 thousand items, marketplace) with structured data saved in MySQL for subsequent output in WordPress. 2. Install and configure n8n on VPS, as well as organize AI content processing: prompt setup, text rewriting, image processing, SEO optimization, and text checking for AI detection. You can estimate the cost of completing both the entire project and each task separately. .
It is necessary to perform parsing from Viber channels (Total number - 49 channels, about 80 thousand subscribers).
An independent service handler for Excel files is required for the existing microservices system. The task involves creating a reliable pipeline for receiving, validating, and transforming data from tables into a structured database format. Functional tasks: Development of an API based on gRPC for receiving processing commands and returning execution statuses. Implementation of file parsing logic: reading large volumes of data (XLSX), cleaning, type checking, and mapping to business models. Implementation of a data access layer (Repository/Unit of Work) for saving results in PostgreSQL via Entity Framework Core. Ensuring thread safety and efficient resource usage (especially when processing large files). Technical requirements: Platform: .NET 10. Architectural patterns: Dependency Injection, CQRS, modular project architecture. Communication: Strictly gRPC. Working with Excel: Use of efficient libraries (e.g., EPPlus, OpenXML, or similar of your choice). Modularity: Code should be organized so that the service is easily scalable and testable. Expected results: A fully functional microservice ready for deployment in a containerized environment. A clean codebase adhering to SOLID principles. Documented .proto files. Basic unit tests for critical data processing nodes. Candidate requirements: In your response, please specify: Your experience with .NET in microservices architecture. Examples of how you organize DI and modularity in your projects. Experience with Excel libraries in .NET. Willingness to work with gRPC contracts.
Good afternoon. I need a keyword parser that outputs results through a Telegram bot. How it should work: Automatic search on 4 websites for keywords that change from time to time. Search queries are sent every few minutes. The words are uploaded in the form of a .txt file. The Telegram bot should have buttons: start bot, stop bot, download file (downloads a file with active keywords), upload file (uploads an edited file with new words). The bot should ignore previously found results, i.e., it should not indicate the same ad twice. The result comes to the bot in the form of a link with a photo, but just a link is sufficient. P.S. searching websites without API, VPS with 6TB and 50 IPs are already available. For detailed information, please contact me via private message.
Task: one dashboard with all business metrics — advertising, funnel, payments, manager performance, revenue planning. Data is pulled automatically via API. Scope: only the YCL direction (employment in Europe). Kommo has other directions — only YCL funnel deals will be included in the repository (filter by funnel/tag to be agreed upon).1. Data Sources (Integrations) Kommo CRM — leads, deals, funnel stages, responsible persons, sources, dates of transitions between stages (must keep history), reasons for refusals, custom deal fields (see point 2). Stripe — payments, amounts, statuses (success/failure/refund), linked to deals. Meta Ads — expenses, impressions, clicks, CPL, leads by campaigns (currently operational). Google Ads, Reddit Ads, LinkedIn Ads — planned; architecture — extensible connectors without core rework. SEO/organic— Google Search Console + GA4. Cross-link: traffic source → lead in Kommo → payment in Stripe (UTM, deal ID in Stripe metadata — propose the mechanism). 2. Mandatory Cuts (Deal Fields in Kommo) Each metric must be filtered/grouped by: Client Citizenship (Kenya, Nigeria, India, etc.). Residence Status: lives in their country / expat (already in Europe). These are two different segments with different cycles, conversion rates, and checks. Country of Placement / Service: Poland, Serbia, Slovakia, Germany (ZAV). Manager, team, traffic channel, period. If any fields are missing in Kommo — the executor indicates which fields need to be added, the client adds them.3. Funnel and Leading Indicators Data by funnel, for each stage — summary and leading metrics: Traffic → lead: leads, CPL by channels + day-to-day expense/click dynamics. Lead → qualification: conversion + first response speed, touches/calls to the manager per day, unanswered leads. Qualification → contract/invoice: conversion + sent offers, stalled deals (days in stage above norm). Invoice → payment: payments, average check + unpaid invoices, failed payments. Summary: revenue, ROMI by channels, run rate to monthly plan. 4. Deal Cycle Average and median lead → payment cycle (business benchmark ~4 weeks), cycle trend over time. Breakdown of cycle by stages (how many days a deal sits at each stage) — to see which stage is dragging. List of deals that have stalled at a stage longer than normal. Cycle breakdown by segments: citizenship, residence status, country of placement, manager. 5. Early Warning of Decline (Key Block) Since the cycle is ~4 weeks, today's leads = payments in a month. The system must: Compare leads/qualifications of the current week with the moving average (4 weeks) and issue an alert if there is a downward deviation: “leads -X%, with a 4-week cycle expect a payment decline in the week [date].” Build payment forecast for 4 weeks ahead from the current pipeline: deals at each stage × historical conversion of the stage × remaining cycle. Highlight in red weeks where the forecast is below plan — with time to react. 6. Additional Payments and Sales Planning In the Kommo deal card, the date and amount of the planned additional payment are stored. The system must: Collect a calendar of upcoming additional payments: total expected, by weeks/months. Highlight overdue additional payments (date passed, no payments in Stripe) — a separate list for follow-up. Calculate the monthly plan as: plan − already paid − scheduled additional payments = how many new sales are needed (in money and in deal units at average check). Weekly schedule: additional payments + forecast of new payments against the weekly plan. 7. Manager Performance Daily snapshot for each manager: touches/calls, conversations, sent offers, payments — for each day separately, with a chart over the period. Progress on personal plan compared to monthly pace (ahead / on pace / behind). Benchmarking with colleagues. 8. Visualization and Roles “Traffic lights” (green/yellow/red) for key metrics relative to norms/plans; progress scales; trend graphs; mobile adaptive. Roles: CEO — everything; COO — entire funnel and managers; team lead — their team; manager — their metrics and position relative to colleagues. 9. Reports and AI Automated reports on schedule (daily summary, weekly report) in the dashboard and/or messenger. Free-form queries (“how has CPL from Meta changed over 2 weeks?”) — LLM over the repository. Alerts in the red zone and according to the rules from points 5–6. 10. Technical Expectations and Staging Repository (PostgreSQL/BigQuery or equivalent) + ETL: Kommo webhooks + periodic synchronization (15–60 min). Frontend: custom or BI tool — propose with justification; requirements for roles, traffic lights, forecasts, and AI queries must be implementable. Stages: (1) audit and metrics map → (2) MVP: Kommo + Stripe + Meta, funnel, traffic lights, roles → (3) deal cycle, early warning, additional payments and plan → (4) SEO, AI reports, alerts → (5) new advertising channels. Payment is staged, with a demo for each stage. In the response, indicate: similar projects (end-to-end analytics), stack with justification, timeline and cost estimates by stages, monthly ownership cost (hosting, tokens, licenses).