Budget: 700 UAH Deadline: 1 day
Ready to take on the project for the minimum price, I have experience working with similar data collection.
There is a list of products (for example, watches). It is necessary to check the accuracy of the specifications for each product. The product can be found on Google by the factory article number of the model.
If necessary, enter the correct value of the specification into Excel for the corresponding product.
The price should be specified separately for 1 verified specification, separately for 2, and for 3+

Budget: 700 UAH Deadline: 1 day
Ready to take on the project for the minimum price, I have experience working with similar data collection.
Budget: 1000 UAH Deadline: 1 day
Good day.
I can offer a manual solution if the number of products is not large.
For a large number of products, I can create an automated process. Collecting product specifications by SKU, after which comparison (by SKU, for example) and correcting existing data if necessary.
Feel free to reach out, we will negotiate.
Budget: 700 UAH Deadline: 1 day
Good day. I ran an online watch store, so I have relevant experience. But I need a little more information to assess the cost. I would appreciate it if you could write to me privately.
Budget: 1000 UAH Deadline: 1 day
Good day.
I am ready to complete your task.
We can work hourly, or 5-10-15 in advance.
Feel free to reach out.
Budget: 2000 UAH Deadline: 3 days
Good day. I have worked with parsing and entering data into Excel multiple times.
I have a question - in what format will the input data be? JSON, CSV, or a link to a website where the information needs to be parsed?
I am ready to start collaborating! :D
Budget: 700 UAH Deadline: 1 day
Good day, I am interested in your project. I see several options for storing the required information: excel, google sheets. I have extensive experience in parsing various websites, both unprotected and with different protection systems. If your site is simple, the cost of developing a parser is 600-700 UAH. If a one-time parsing is needed, the price is 400-500 UAH. Please write, I would be happy to collaborate.
P.S. If you need a price for each characteristic, then 1 characteristic - 5 UAH, 2 characteristics - 7 UAH, 3 - 8 UAH, more than 3 - the cost does not change ;-)
Budget: 1000 UAH Deadline: 5 days
Good day. I have worked with this category and brand of watches. I can complete your task for 1 price -5, 2 price -10, for 3+-20 UAH.
Budget: 1000 UAH Deadline: 1 day
Good day, I am interested in this project, I have experience in similar tasks and also in collecting large sets of product specifications through Python parsing. The price can be discussed further, I would be very happy for a long-term collaboration.
1 - 20 UAH
2 - 35 UAH
3+ - 15 UAH
Budget: 700 UAH Deadline: 1 day
I have experience in data search
I will do everything quickly and efficiently.
I work for rating :)
1 = 20 UAH
2 = 30 UAH
3+ at 15 UAH each
Budget: 1000 UAH Deadline: 1 day
Hello, I am interested in your project, please write in private messages to discuss the details.
Price for 1 - 40 UAH; 2 - 60 UAH; 3+ at 25 UAH each.
Budget: 1000 UAH Deadline: 1 day
Hello! I have experience in data verification and analysis. I will do it quickly and efficiently!
Budget: 1000 UAH Deadline: 1 day
Hello! I am ready to complete it, currently completely free in terms of time. What is the volume of the product? Regarding payment, we will base it on the volume.
I have extensive experience in content and in finding shortcomings, I have worked as a curator.
Budget: 700 UAH Deadline: 1 day
Hello, I am ready to perform the check, the price is 1-40 UAH, from 10-30 UAH.
Budget: 1500 UAH Deadline: 3 days
Hello! I am interested in your task. I am ready to start working right now. Please write regarding the details. I will be happy to collaborate!)
Budget: 1000 UAH Deadline: 1 day
Good evening, I am ready to complete your project with quality and within the agreed deadlines. I have work experience. Prices for: 1-50 UAH For 2 -80 UAH For 50+ from 1000 UAH
Budget: 700 UAH Deadline: 1 day
Good day. I am ready to take on your order. We have agreed on the payment. How much time is there for completion, and what will the volume of work be? I am ready to start working tomorrow. I am waiting for your response.
Budget: 1000 UAH Deadline: 1 day
Oleg, good afternoon, I am ready to check, I have experience. I suggest working hourly. How urgently does it need to be done?
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;
Channel requirements: 1. Content language: Russian or Ukrainian (mixed RU/UA content is allowed) 2. Number of subscribers: At least 500 subscribers 3. Activity: The last post published no later than 32 hours ago 4. Comments: Comments must be open under the posts (through a group or embedded) 5. Quantity: Minimum 15,000 lines 6. Theme: War, news, politics, fights, trash/gore, sports, cars, crypto, fishing, and others Data to be collected for each channel Mandatory fields: Channel name username (link) Number of subscribers Theme (news, crypto, humor, business, etc.) Language (RU / UA / MIX) Date and time of the last post Presence of comments (yes) File format: Google Sheets / Excel (.xlsx)
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).