Remove UTM parameters from a URL list

To remove UTM parameters from URLs in bulk, paste one absolute URL per line into the Bulk URL Cleaner, leave the optional removal settings off and select Clean URLs. Review the original and resulting addresses in the CSV before using the TXT list. The aim is to remove campaign fields while retaining the query values that make each destination useful.

This is a list-cleaning task. The cleaner edits the text you supply; it does not change your website, open the destinations or configure redirects. You can use the output for a link inventory, an editorial reference list or a set of bookmarks. Keep the original tagged addresses when they are still needed for campaign measurement.

1. Keep an untouched input copy. If the addresses come from a spreadsheet, copy the URL column rather than pasting the entire CSV, including headings and notes. Give each working batch an identifier so that the review can be traced back to its source.
2. Paste one full address per line. Use HTTP or HTTPS URLs, including the scheme. You can also read a plain-text URL file through the local file input. A relative path such as /products/mug needs its correct domain added before it can be checked by this tool.
3. Start with UTM-only removal. Leave the click-ID checkbox unchecked and the additional-name field empty. The default removes decoded query names beginning with utm_; unfamiliar names remain available for a separate decision.
4. Run the cleaner and read the decisions. A changed row, an unchanged row, a protected URL and an invalid input mean different things. Do not treat every unchanged result as a failure or assume every changed result is approved for publication.
5. Download the review CSV first. Keep the original-to-result mapping and investigate exceptions. After that review, use the TXT export when you need one resulting URL per line.
6. Keep larger jobs in reviewable batches. The current input limits are 2,000 nonblank lines and 1 MB. If a list exceeds either limit, split it before processing and retain a batch ID with each CSV. The on-screen preview shows up to 100 rows, so use the export to review the rest.

For a product filter, cleaning can look like this:

Before
https://example.com/products/mug?utm_source=newsletter&utm_medium=email&color=blue#details

After
https://example.com/products/mug?color=blue#details

The campaign fields are removed, while color=blue and the #details fragment stay. Deleting everything after the question mark would also delete the colour choice. A general “remove the query string” formula therefore answers a different question from “remove UTM parameters.”

What an eight-line batch actually produced

We checked the following invented example.com inputs in the public cleaner on 22 October 2026, with click-ID removal off and custom names empty. These addresses are test data; no destination was fetched or verified.

https://example.com/products/mug?utm_source=newsletter&utm_medium=email&color=blue#details
https://example.com/search?q=red%20shoes&tag=a&utm_campaign=spring&tag=b
https://example.com/guide?UTM_Source=social&lang=ur
https://example.com/blog?%75tm_source=email&utm_campaign=sale
https://example.com/watch?id=42&ref=partner&gclid=demo
https://example.com/file?signature=demo&utm_source=email
https://example.com/products/mug?utm_source=newsletter&utm_medium=email&color=blue#details
not-a-url

The result was five changed rows, one ordinary unchanged row, one protected unchanged row and one invalid row. The downloaded CSV contained all eight data rows. The TXT contained seven lines because the invalid entry was omitted. Line 7 intentionally repeats line 1, and both remained in the exports.

This gives you several useful checks for your own process. The mixed-case and encoded UTM names were removed; the repeated tag values and search-text encoding were retained. The gclid and ref fields stayed because their removal was not selected. The signature-bearing URL stayed completely unchanged, including its UTM field. A TXT file can therefore still contain a UTM parameter when the complete address is protected.

The test establishes those text-processing and export results for this small fixture. It does not establish that a real shop will interpret a cleaned URL identically, or that a private download link will remain valid. Use the reproducible built-in sample below when you want a smaller starting point, then check the destinations that matter to your actual batch.

Decide why the URL is being cleaned

Removing UTM parameters is useful when you want a readable reference link, an untracked bookmark or a list to review for internal linking. It can be the wrong decision when the URL is about to go into an email campaign and those parameters are how you intend to measure that placement. Write down the destination and the measurement purpose before editing the address.

Our Bulk URL Cleaner removes selected parameter names from supplied text. It does not open the destinations or decide which parameters your application needs. Start with a copy of the original list. The six-line example below deliberately includes a functional filter, a repeated field, an ambiguous referral value, an access signature, an encoded parameter name and an invalid address.

Run the six-line example

1. Open the cleaner and choose Load six-line example.
2. Leave optional click-ID removal unchecked and leave custom names empty.
3. Choose Clean URLs, then compare every original and resulting URL.
4. Download the review CSV before deciding which results to use.

The result is six reviewed rows: three changed, one protected unchanged, one ordinary unchanged and one invalid. The tool preserves the original line number, so you can trace each decision even when the pasted list contains blank lines. These are invented example.com addresses, not a test of any shop, tracking service or live download.

Keep parameters that control the page

A product ID, search phrase, language, page number or filter can change the content a visitor receives. A link to /watch/?id=42 is not interchangeable with /watch/ simply because the second address looks shorter. Treat unfamiliar parameter names as functional until you have evidence for removing them.

The default cleaner matches decoded names beginning with utm_, without case sensitivity. It keeps other names unless you enable the six listed click identifiers or supply exact custom names. A custom name of ref does not remove referral. This explicit policy is easier to review than a rule that deletes every query string.

Do not assume every UTM field is harmless in your own system. A website can use a parameter for custom behavior. Ask the owner when necessary, test the resulting page and keep campaign links tagged when measurement is the purpose. The tool’s default list is a text-editing rule, not evidence about the receiving website.

Preserve the remaining query text

For the second example, the output is:

https://example.com/search/?q=red%20shoes&tag=a&tag=b

The space remains %20, both tag fields stay in the same order and the removed UTM field is the only query segment dropped. The cleaner validates the address with the browser URL parser but filters raw ampersand-separated query segments for its output. It does not sort parameters, collapse duplicates, normalize host spelling or remove fragments.

This choice matters because query serialization can change spelling. MDN documents that editing a URL through URLSearchParams can serialize spaces as plus signs and change other encoding. See the URL query serialization reference listed in the sources below. Equivalent-looking encodings still deserve care when an application expects a particular byte sequence.

Stop before altering an access link

The fourth line contains a literal signature parameter. The cleaner leaves that entire URL unchanged, including its UTM field. It also protects a limited list of common signing and access-key names, including sig, token, access_token, auth, authorization, policy, key-pair-id and names starting x-amz- or x-goog-.

This is a conservative review aid. It cannot recognize every signed URL format, and an unflagged URL is not proof that editing is safe. A temporary document link, password-reset link or paid-download address needs its owner’s review. Never share a real access URL as a public example. A locally processed input can still be sensitive when you copy it or send the exported file elsewhere.

Use the export that retains the evidence

The CSV contains every nonblank input row, original URL, resulting URL, status, removed names and review note. The TXT contains only usable resulting URLs; invalid rows are omitted, while protected URLs remain unchanged. Duplicate lines stay duplicated in both outputs. The table previews the first 100 rows; the exports cover all rows within the 2,000-line, 1 MB limits.

Choose CSV for a review handoff and TXT for a list you have already approved. Formula-like CSV cells receive an apostrophe prefix, which changes those cell values for spreadsheet safety. Keep the original input if you need an exact archive. Use the URL cleanup decisions worksheet to record the intended use, owner and evidence for each removal.

Before replacing a published link, open the intended destination, check the visible content and exercise the relevant filter or action. Compare the original campaign’s measurement requirements separately. If the destination or behavior differs, retain the original URL and investigate. A shorter address is useful only when it still serves the task you intended.

Separate cleaning, deduplication and approval

UTM removal can make two different input strings produce the same address. Imagine one guide linked from an email and from a social post: after their campaign fields are removed, both rows may point to the same guide. Keep both rows in the review file until you have decided whether the task needs a source-to-result mapping or a unique destination list.

For an editorial handover, the mapping is often more useful because it shows where each original address came from. For a later crawl inventory, you may want a separate deduplicated copy. Make that a second operation with its own record count. The cleaner intentionally retains duplicate lines, and a repeated destination is not automatically a processing error.

Before approving the output, reconcile the input count with the review CSV. Explain each invalid row and each protected row, then check a sample of changed destinations that covers your important page types. A product, a search page and a language-specific guide deserve different checks. Increase that review when a failure could prevent a customer reaching the intended page.

A compact handover can record the batch ID, original file, selected removal policy, number of reviewed rows, unresolved exceptions and owner of the next check. Keep the review CSV with the source list, rather than leaving a shortened TXT file as the only evidence. If a setting changes, create a new output version so that reviewers know which policy produced it.

Do not add names such as ref, id or lang simply because they look like tracking. Check what they do in the receiving application. Similarly, optional advertising click IDs should have their own measurement decision. For links intended to track a new campaign, use the UTM naming workflow instead of cleaning the fields away.

Sources and verification

The eight-line public-tool test and both downloaded exports were checked on 22 October 2026. The scenarios and review workflow are original ProSEO examples. Google Analytics documents how campaign parameters identify referring campaigns; MDN documents URL query handling and serialization. These sources explain the underlying concepts, rather than certifying any particular website’s response to an edited address.

• Google Analytics: collect campaign data with custom URLs
• MDN: URL query strings and interaction with search parameters