Web scraping, data cleaning & Excel reports
Competitor prices, property listings, supplier catalogues or your own messy exports — I turn them into clean, structured data and ready-to-share reports.
Get a free quotePricingThe problem and the solution
Data from several sources is hard to compare when formats differ. I define the required fields, collect accessible data within the agreed permissions, remove duplicates and deliver a repeatable export. A sample is checked before the full run; refresh frequency and source changes are part of the scope.
Define the task and test the result
Before quoting, I need the current workflow, a sample input, the expected output and who will use it. We agree the systems involved, access requirements, what counts as success and which exceptions need human review. The delivery includes the agreed implementation, a walkthrough and instructions for running or maintaining it. We test a normal case, missing or invalid data and a failure of an external service where relevant. Access, recurring costs and support arrangements are confirmed in the scope. New sources, extra features or changes in a third-party service may require separate work.
What’s included
- Data collection from websites and public sources
- Cleaning: duplicates, dates, currencies, names
- Excel / Google Sheets with charts and summaries
- Scheduled updates (daily / weekly)
- Price and stock monitoring with alerts
- Import into your shop, CRM or database
Frequently asked questions
Is scraping legal?
I only collect publicly available data and respect each site's terms and robots rules.
What format will I get?
Excel, Google Sheets, CSV, JSON or a direct import — whatever suits you.
What should I provide for a data collection quote?
Send source URLs, required fields, an example of the desired spreadsheet, approximate volume and refresh frequency. Confirm that you can use the data. We check whether an export or official API is available before designing collection from web pages.
How is the exported data checked?
We agree field types, duplicate rules and handling of empty values. Example workflow: collect an authorised catalogue, normalise prices and identifiers, flag missing entries and export CSV or Excel. A sample is compared with the source before processing the agreed volume.
Can collection keep working after a source changes?
A website layout, login requirement or rate limit can change. The delivery should identify incomplete runs and avoid silently presenting missing records as complete data. Monitoring and adaptation are separate maintenance work unless included in your quote; uninterrupted access cannot be promised.
How is handover and acceptance handled?
We review the agreed examples together and record any issue against the written scope. You receive instructions and the agreed files or access needed to use the result. Confirm who will operate it after delivery and which support period is included. A new feature is scoped separately from correcting a failure to meet the agreed requirement.