Home and mobile are both phone columns

The first version of bulk detection made a bad assumption. It looked for the best phone column in a file. If the file had both mobile and home, one could win and the other would be skipped.

I wanted it to handle both. A second phone column is still part of the file someone asked us to check, and the same problem applies to two email columns or two postal columns.

Detection now considers each source column separately. If both mobile and home contain phone numbers, both appear on the quote. Each gets its own carrier, caller ID, and live-status choices, so you can ask different questions about each column.

The result headers use the source names to keep them readable. For example, a file headed mobile and home can get parse_mobile_valid beside the first column and parse_home_valid beside the second. You should be able to follow a result back to its input without counting columns.

A repeated value still needs a result in both places

Suppose the same phone number appears under both mobile and home. If carrier lookup is selected for both columns, that is one unique number for the carrier check. It is counted once across those selected columns, and the answer can appear beside both inputs.

Carrier and caller ID remain separate checks, even when they use the same number. Reusing a value across columns does not combine different products into one charge.

That distinction matters on the quote as well as in the download. Removing a check from one column leaves the other selected column able to run it. A column containing only repeated values can still get its results, even when it adds no new billable values.

The bulk preview shows which columns will run before you start. Both phone columns belong there.