Budget: 2000 UAH Deadline: 3 days
Good day. Ready to complete your project. From you - an example of the structure of the specified files. I will be glad to cooperate.
It is necessary to copy products from the website https://prom.ua/ua/c2112336-limoninua-internet-magazin.html, https://limon.in.ua/p1823524944-hotwav-note-8128gb.html, or another similar website, (links provided) all products, i.e., images, descriptions, specifications, in a format for uploading to an online store, i.e., xml, csv, xlsx. We also consider the option of purchasing software with this functionality
Budget: 2000 UAH Deadline: 3 days
Good day. Ready to complete your project. From you - an example of the structure of the specified files. I will be glad to cooperate.
Budget: 1000 UAH Deadline: 3 days
Good day.
Ready to work on Zenoposter. Actively engaged in parsing for the last 4 years. A separate parser will need to be developed for each website. Then they can be combined into one universal multi-threaded parser. I suggest discussing the terms of reference in more detail in personal messages.
Budget: 1500 UAH Deadline: 3 days
Good day!
Parsing is my specialization. Check the reviews.
I have a couple of questions, write in private. Let's agree.
Budget: 500 UAH Deadline: 3 days
Good day, I can help; I have experience in execution, I will earn everything quickly and qualitatively, write in PM.
Budget: 4000 UAH Deadline: 4 days
Hello!
I propose to develop a program, a parser for you that will collect information and store it in the selected format.
I will help set it up and deploy it on the server.
I will write in NodeJs, I have 3+ years of experience.
I will be happy to cooperate.
Budget: 500 UAH Deadline: 2 days
I worked with the industrial website. I was engaged in laying out goods with a description and characteristics of the product. Ready to quickly post a product with a description, price, photo.
Budget: 1000 UAH Deadline: 2 days
Good day.
I am engaged in writing scripts. I have experience in creating files for importing goods for various platforms. Reviews in the profile.
Contact me, we will discuss a more specific project.
Budget: 1000 UAH Deadline: 1 day
Congratulations!
If the site is on OpenCart, I have several ready-made solutions for parsing.
Contact me privately to discuss.
Budget: 1000 UAH Deadline: 1 day
There is an option to create automatic parsing, which will parse images, descriptions, characteristics into a Google spreadsheet...
And from the Google spreadsheet, you will be able to save in another format
Budget: 2500 UAH Deadline: 5 days
I am ready to discuss the details of the work in private messages. I work quickly and efficiently. Feel free to contact me.
Budget: 1500 UAH Deadline: 4 days
Good day, I am interested in your project. To perform your task qualitatively, I need a link to the website (in a personal message). Have a nice day.
Budget: 500 UAH Deadline: 1 day
Good day!
Ready to perform the task in Python.
Can start right now.
Budget: 12500 UAH Deadline: 10 days
Good day!
I am ready to create a parser for copying products into a table.
I have experience in developing similar projects.
I write in Python. I am ranked 9th on the platform in this language.
I will be happy to cooperate!
Budget: 500 UAH Deadline: 1 day
Good day.
Ready to take on the task.
Write me privately, we will discuss.
Budget: 700 UAH Deadline: 5 days
Hello! I have experience working with prom, both parsing goods and loading, write, I will be happy to cooperate.
Budget: 4000 UAH Deadline: 2 days
Hello.
Ready to parse.
Write me a personal message.
Let's discuss the details.
Budget: 600 UAH Deadline: 3 days
Good day! After studying your project with great interest, I am ready to start working on it. Let's discuss the details to achieve the best result.
Budget: 1000 UAH Deadline: 3 days
Hello. Interested in your project. Ready to discuss and execute!
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. .
It is necessary to perform parsing from Viber channels (Total number - 49 channels, about 80 thousand subscribers).
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).