Match & pull columns
Pull matching data from a second file using a shared column. What Excel's VLOOKUP does, built for whole files instead of one cell at a time.
By Operelio team
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What it does
Match & pull columns joins two spreadsheets on a column they share, like email, customer ID, or SKU. It does what Excel's VLOOKUP formula does, for whole files at once.
Upload your primary file (the one you want enriched) and your lookup file (the source of the extra columns). Pick the shared column. Operelio pulls matching data from the lookup file into your primary file and gives you back one combined file.
There's no formula to write. Files can be CSV or Excel, and the file formats don't have to match: you can join a CSV to an XLSX.
What to keep, what to drop
When you run the join, Operelio asks what to do with rows that don't match. There are three options. Most people want "Keep all rows" (the first one in the table below).
| Mode | Plan | What you get | When to use it |
|---|---|---|---|
| Keep all rows (left join) | Free | Every row from your primary file. Where there's a match, the extra columns are filled in. Where there isn't, they're blank. | Default. Use when you want to enrich a list and keep everyone. |
| Only matching rows (inner join) | Pro | Only rows that matched in both files. Unmatched rows are dropped. | Use when you only care about contacts you can enrich. |
| All rows from both files (full join) | Pro | Every row from both files. Unmatched rows from either side are kept with the missing columns blank. | Use when you want a complete picture of both lists. |
How to use it
Upload both files
Drop your primary file (the one you want enriched) and your lookup file (the extra data) into the upload area. CSV or Excel both work, and you can mix them.
Pick the shared column
Choose the column that appears in both files, like email, customer ID, or SKU. That's how Operelio knows which rows go together.
Choose what to keep
Stick with the default (keep all rows) unless you have a reason to change it. The other modes are explained above.
Pick which columns to bring across
By default, every column from your lookup file (except the shared one) comes across. If you only need a few, untick the rest.
Click Run
Operelio combines the files quickly and gives you a download. On Free you get a CSV. On Pro you can choose CSV or Excel.
Match on more than one column (Pro)
Sometimes one column isn't enough. If your contact list has multiple John Smiths, matching on first name alone won't tell them apart, but matching on first name AND last name will.
On Pro, Team, and Agency, you can pick more than one shared column in each file. A row only counts as a match if all the columns line up.
Catching typos and small differences (Pro)
If the shared values aren't identical across files ("Westmarch Trading" in one and "WESTMARCH TRADING LTD" in the other), similarity matching finds the closest match instead of insisting on an exact one.
Operelio measures how similar two values are by counting how many edits (insertions, deletions, character swaps) it would take to turn one into the other. Fewer edits = more similar.
Set a threshold between 50 (loose) and 99 (almost identical). 80 works well for company names; 90 or higher for short codes like SKUs, where one wrong character usually means a different thing entirely.
When similarity matching is on, Operelio picks the best match above the threshold for each row. If no match clears the bar, the row is treated as unmatched.
When both files have the same column name
Sometimes both files have a column with the same name. For example, both have a "status" column. Operelio asks how to handle the collision before it joins. You have three options:
| Option | What happens |
|---|---|
| Add a suffix (default) | The lookup file's column gets a _B suffix. "status" becomes "status_B". You keep both. |
| Overwrite | The lookup file's value replaces the primary file's value in the same column. |
| Skip | The lookup file's column is dropped. The primary file's value stays. |
What the results show
After the job runs, the results page summarizes the join with a sentence like "Matched 1,847 rows from 2,100 (primary) and 1,950 (lookup), producing 2,100 output rows." Below that you'll see the key numbers and the settings you used.
| What you'll see | What it means |
|---|---|
| File A | Total rows in your primary file (File A). |
| File B | Total rows in your lookup file (File B). |
| Matched | Rows from the primary file that found a match in the lookup file. |
| Output rows | Rows in the final combined file. The total depends on which mode you picked above. |
| Warnings | Anything Operelio noticed, like duplicate keys in the lookup file or column names that collided. |
Frequently asked questions
What happens if my lookup file has duplicate keys?
Operelio keeps the first occurrence and ignores later duplicates. A warning on the results page tells you how many duplicates were found, so nothing happens silently.
Can I join more than two files at once?
Not in a single job. To join three files, run the tool twice: join the first two, then use the result as the primary file for a second run against the third.
What plan do I need?
"Keep all rows" mode with exact matching is Free, with up to 2,000 rows. The other two modes, multi-column matching, and typo-tolerant matching all need Pro. Pro is $39/month, or $351/year on annual billing (25% off, equivalent to $29.25/month) and lifts the row limit to 50,000.
What if I make a mistake?
Nothing to undo. Your original files are kept untouched: a join just produces a new file. If you don't like the result, run the job again with different settings.
Ready to get started?
Upload a file and run your first transformation. Free, no credit card required.