🧹 Mapping and cleaning step by step
Successfully launched the app? Great. Now we can start the actual cleaning. The tool's wizard is designed to guide you through the whole process very intuitively. In this article, we will break down the first part of the process in detail – from uploading a spreadsheet to fine-tuning the validators.
Uploading a file to the application
Right on the home screen, the app prompts you to select a source file. We support standard database formats:
- CSV and TSV: text files separated by a comma, semicolon, or tab,
- Excel (XLSX): classic Excel spreadsheets (the app handles them natively, you don't need Microsoft Excel installed on your computer).
You can simply drag & drop the file into the designated area, or click to open a standard file selection dialog.
Advanced file and API settings
In the top right corner next to the language selection, you'll find a gear icon. This opens advanced settings that will come in handy before your first run:
- Default country: if your database doesn't contain a country column, the app will assume the records are from this country (default is CZ),
- Encoding and CSV injection: by default, the tool protects your export from dangerous formulas in Excel (so-called CSV injection protection, where cells starting with an equals sign are escaped). You can also manually force specific text encoding here,
- Foxentry API key: you can enter it right here, but it's most convenient to paste it in the last step (Summary and order) right before starting the validation.
💡 Tip: Check supported countries
At any time during the process, you can click the Supported countries button in the top bar. This way, you can easily verify which countries we currently provide individual validations for in our API.
Column mapping and the magic of "groups"
Once you upload a file, the app analyzes it and displays a preview of your data. Now you need to tell the system what is located in which column.
At the top of each column, you will find a dropdown menu where you assign a specific data type (e.g., e-mail, phone, name, address, company). Leave columns you don't want to validate (e.g., internal customer ID, date of birth, etc.) set to — ignore —. The app will skip them during validation, but will naturally keep them unchanged in the final file.
How do groups work (e.g., Addresses 1, Addresses 2)?
During mapping, you'll notice that services have numerical indexes (e.g., Addresses 1, Addresses 2). This is how you determine which columns logically belong together, as several columns can form a single record for validation.
Example: If your spreadsheet has billing and delivery addresses on the same row next to each other, you assign the street, city, and ZIP code of the billing address to the Addresses 1 group. This helps the system understand they form one unit. You then assign the street, city, and ZIP code of the delivery address to Addresses 2. Foxentry will process them as two separate validations.
Also, make sure the First row is a header option in the top left is correctly checked. If your spreadsheet doesn't have a header with column names, uncheck it so you don't lose the first database record.
Customizing validators
In the next step, you will fine-tune exactly how Foxentry should treat your data. For each mapped service, a separate settings block will appear, corresponding to our API options.
Settings for names, surnames, and addresses
For names and addresses, you primarily determine the level of automatic corrections (whether you want to fix typos, add diacritics, or just strictly check). Furthermore, you can choose the preferred format of the returned data (for example, ZIP code with or without a space, formatting of city districts, etc.).
Settings for companies, e-mails, and phones
For companies, you can determine whether the system should also consider historically dissolved entities. For e-mails, you have the option to strictly discard disposable addresses (e.g., 10minutemail) or known fraudulent domains. For phone numbers, you choose the depth of the check (basic formatting or extended validation with availability check) and the required international output format.
Data enrichment mode (full datascope)
Notice the Enrich data (more info) toggle for most services. If you activate this option, Foxentry won't just fill your resulting file with corrected data, but will add entirely new columns. For names, you will get, for instance, the vocative case (the correct salutation for your e-mailing), name days, or gender determination.
For companies, you will find out their VAT status or exact legal form (see overview of all returned data for companies), and for addresses, you will receive exact GPS coordinates among other things (see overview of returned data for addresses).
ℹ️ Billing for enriched data
Keep in mind that data enrichment (full datascope) is charged at a higher credit rate according to the current pricing. You will always clearly see the estimated price in the next step before launching.
Is everything set up? Excellent. In the final article of this series, we will show you how to start the process itself, how to navigate the final HTML report, and how to properly work with the resulting file.
