Budget: 2000 UAH Deadline: 1 day
I will gladly do it in any format, contact me
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Budget: 2000 UAH Deadline: 1 day
I will gladly do it in any format, contact me
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Budget: 700 UAH Deadline: 1 day
Good day. To evaluate the order, it is necessary to review the website itself. I will be happy to cooperate.
Budget: 4000 UAH Deadline: 5 days
Good day, I am ready to perform high-quality parsing of product cards from the website. I will receive the following data:
Name
Photo
Description
Article number
Characteristics
Filters
✅ In two language versions
I will deliver the data in CSV/Excel format or a database (upon request).
Parsing experience — 4+ years, I work with Python (Selenium / BeautifulSoup / lxml). I can bypass protection and adapt to the structure of your website.
🔐 I can also add a system for re-collecting new products upon update.
Deadline: 3–5 days
Cost: 3,000 – 4,000 UAH (depends on the number of categories and website structure)
Budget: 700 UAH Deadline: 2 days
Good day!
I can create a parser, but I need to review the website.
I will perform product parsing from your site by specified categories in two languages. I will collect the name, photo, description, article, characteristics, and filters.
I will provide the result in a convenient format — Excel or JSON.
I have experience working with Python, requests, BeautifulSoup, and pandas.
I am ready to start immediately after agreeing on the details.
Budget: 700 UAH Deadline: 2 days
Hello! I will complete the task without any problems.
I will do everything quickly and qualitatively!
Budget: 17000 UAH Deadline: 7 days
Hello
I am a developer in the field of AI/ML & WEB SCRAPING. I can complete your project. Write to me, let's discuss.
Budget: 700 UAH Deadline: 1 day
Good afternoon, I can manually scrape very high quality and on time! Just need to understand the number of products
Budget: 1000 UAH Deadline: 1 day
Hello.
Ready to gather data on all specified keys in two languages.
If needed, I can organize the results into a convenient format for further import.
Budget: 700 UAH Deadline: 3 days
Good morning, Larisa!
Overall, the task is clear, but to provide an accurate response regarding deadlines and price, I would like to clarify some questions that arose after analyzing your task.
Please message me privately – we will discuss the details and your preferences.
Budget: 800 UAH Deadline: 1 day
Good day!
Ready to join the execution of your task.
I have experience in parsing multilingual websites, including collecting information about products: names, photos, descriptions, articles, characteristics, and filters.
Details — I am happy to discuss in private messages.
Budget: 1000 UAH Deadline: 1 day
Good day. I have been working with parsers for quite a long time. We can discuss in more detail
Budget: 1500 UAH Deadline: 1 day
Good day.
I will write a parser that you can run yourself. The products will be stored in Excel.
If you have any questions, you can write to me in private message.
Budget: 1200 UAH Deadline: 2 days
Good day, I am interested in this project, I have experience in parsing and recently returned to freelancing. I work with Python libraries BS+requests, and if the site has bot checks, I use Playwright. I would be very happy to collaborate!
Budget: 1500 UAH Deadline: 2 days
Good evening, I can scrape the website and collect all the products you need, I work in Python, I have experience in product scraping. There are similar jobs in my profile. I can start right away and I also have a couple of questions regarding your task
Budget: 1111 UAH Deadline: 1 day
Good day!
Ready to start cooperation!
Experience in similar projects - yes.
*details in private*
Attention!
If I indicated in the total rate "1111" or "777", it means I need more information to evaluate the project (also, deadlines may change depending on the scope).
Budget: 700 UAH Deadline: 2 days
Ready to take on the task.
But I need to clarify the order details, write to me!
I will implement with a Python script.
Budget: 997 UAH Deadline: 1 day
Hello. Interested in your project. Ready to discuss and execute!
Budget: 700 UAH Deadline: 1 day
Good evening
Provide a link to the website for work assessment.
Write in private messages
Budget: 1000 UAH Deadline: 1 day
I can parse it. but you need to understand what kind of site it is. and what you mean by filters.
Budget: 1000 UAH Deadline: 2 days
Good day.
Please tell me what CMS you have and specifics in private, I will look from where to parse.
I deal with parsing every day.
Set up automatic daily updates of product availability on our website on prom.ua. We have a supplier who sends a price list of products in Excel format to our email every day. The items on our website and in the supplier's price list are the same. The values in the "stock" column are either out of stock, a number, or more than a box - these need to be updated on the site to either Ready for shipment or Out of stock. Items that are not in the supplier's price list should remain unchanged. Please propose a solution, timeline, and budget. Thank you in advance for your response, I look forward to collaborating with a specialist.
Hello! I am looking for a performer for ongoing collaboration who is knowledgeable about Opencart. A person who is available and has a positive attitude) Parsing, uploading products in two languages UA + ru, as well as forming the necessary markup immediately I want to complete the work in several stages. 1. Update stock for all suppliers and completely remove outdated products from the site and database. 2. Refinement of the product category, specifically parsing subcategories. 3. Parse new items in old categories. 4. Parse new suppliers into new categories.
A project needs to be implemented for collecting and structuring a large array of images from open web sources (initially 2000 images). The task includes: - automated image collection; - uploading files in the highest available quality; - classifying images by categories. Expected results: - a structured image database; - a clear cataloging system; - delivery of the results via Google Drive or another agreed method;
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. .
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).