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To rename an AI product safely in Salesforce, first identify every object, field, article, and external document that can contain the old name. Use Global Search for discovery, but do not treat an empty result as proof that the name is gone: Salesforce indexes only selected fields by default. Export the records you intend to change, retain an untouched backup, update by stable record ID, test a small subset, and inspect both success and error logs. Salesforce Knowledge needs a separate workflow because Data Loader updates draft articles only; published articles must be moved to Draft individually before they can be changed.
1. Define exactly what “replace everywhere” means
Write the old product name and the approved replacement exactly as they should appear, including capitalization, punctuation, spacing, trademark symbols, and any abbreviated form. A literal replacement of one string will not catch variants unless you include them in the scope.
Make a replacement inventory
- Exact text: the old name in names, descriptions, notes, comments, email templates, and article body text.
- Variants: abbreviations, legacy spellings, hyphenation, capitalization differences, and common misspellings.
- Structured values: picklist options, tags, categories, URL slugs, record names, and external IDs.
- Rich content: HTML in Knowledge rich-text fields, embedded images, image alt text, links, and file names.
- Documentation stores: Salesforce Knowledge, custom documentation objects, release notes, shared drives, wikis, and published help sites outside Salesforce.
- Metadata and automation: Flow formulas, validation rules, email alerts, reports, dashboards, page layouts, and integration mappings that may contain the old value as configuration rather than record data.
The Salesforce procedures below cover Salesforce records and Knowledge data. They do not establish that a single operation reaches external document systems, archived data, translations, hidden fields, or configuration metadata. List those systems separately and assign an owner for each one.
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2. Find likely Salesforce records before editing anything
Start with Global Search
Enter the old name in Global Search and review the suggested results and the full search-results page. Use the object filters to inspect likely objects individually, such as Accounts, Contacts, Cases, Opportunities, custom objects, and Knowledge. Repeat the search for each variant in your inventory.
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Global Search is a discovery aid, not a complete field scan. Salesforce indexes only a limited set of fields by default. Picklists, lookup fields, formula fields, and currency fields are typically not indexed, and an unindexed text field can contain the old name without appearing in results. Search results can also be affected by the running user’s sharing access.
Use object list views
Open the relevant object from the App Launcher, choose a list view, and add a filter such as Field contains old name where the field and operator are available. Create a temporary list view for each object or field group rather than changing a production view used by other teams. Review the resulting rows and record IDs before selecting them for update.
Use reports when the field can be reported
Build a report for each object or joined object relationship that exposes the fields likely to contain the name. Filter text fields for the old string or export the relevant columns for inspection. Reports can help expose fields that Global Search does not index, but report type, field visibility, and row-level sharing still limit what you see.
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Plan for non-indexed fields
If staff need to search a value repeatedly and the original field is not indexed, an administrator can create a custom text field and populate it with Flow when a record is created or edited. That approach improves future discovery; it does not automatically backfill existing records. Existing records require a separate update or backfill job, followed by a check that the new field is populated correctly.
3. Choose the least risky update method
| Method | Best fit | Important limits and checks |
|---|---|---|
| List-view inline editing | A small, visible set of supported records | Requires an editable object and view, the right permissions, and a field that supports inline editing. It is slow and error-prone for many different records or fields. |
| Data Import Wizard | Existing records in a supported object, generally fewer than 50,000 | Match each row to an existing record using its ID or another supported matching criterion. Confirm that the object and fields are supported in your org. |
| Data Loader | Unsupported objects, repeatable file-based jobs, or larger updates | Salesforce guidance varies by page: one 2026 overview suggests approximately 50,000–100,000 records, an FAQ suggests more than 50,000 and fewer than 5 million, and the Data Loader overview states support for files up to 5 million records. Treat these as operational guidance, not a universal limit. |
| Partner-assisted or specialized process | More than 5 million records or an unusually complex migration | Salesforce’s mass-update guidance recommends working with a Salesforce partner or finding a suitable AppExchange product above 5 million records. Confirm security, support, and compatibility before using any external process. |
Salesforce’s Help guidance does not provide one universal record threshold. Object support, API limits, permissions, sharing, validation rules, triggers, storage, and the size of the update file can matter more than a headline number. The most important part of an update is preparing a file with correct matching criteria and data.
4. Prepare a safe bulk-update file
- Export the candidate set. Include the Salesforce record ID, the current value, and enough identifying fields to recognize the record. Export only rows that you have decided should change.
- Keep an untouched backup. Save the original export in a controlled location with the export date, object name, filter definition, and operator. Do not overwrite it with an edited CSV.
- Make a narrow update CSV. Include the record ID and only the fields that should change. A narrow file reduces the chance of unintentionally replacing unrelated values with blanks or stale data.
- Normalize the replacement text. Check encoding, line breaks, quotation marks, HTML, and CSV delimiters. Preserve leading zeros in IDs and any field-specific formatting required by the importer.
- Map columns explicitly. In Data Import Wizard or Data Loader, map the ID column to the Salesforce record ID (or the documented alternate matching field) and map each changed column to the intended Salesforce field. Do not rely on similarly named fields being mapped correctly.
- Run a small test subset. Use a few representative records, including records with long text, rich text, translated content, and unusual permissions if those cases are in scope.
- Inspect the output. Keep the generated success and error CSV files. Open several successful records in Salesforce and investigate every error before processing the remaining rows.
- Process the remaining rows in controlled batches. Record the file name, time, operator, tool, and result counts for each batch so that a failed batch can be isolated or rolled back from the backup.
Do not use a CSV containing only the replacement text. Without a stable ID or other matching criterion, the tool cannot reliably know which existing record to update.
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5. Update a small set with inline editing
Inline editing is appropriate when the target rows are visible in one list view and the field is supported. Open the object list view, select the target record, click the field value, enter the replacement, and save. Repeat for each field and verify the record after saving.
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6. Handle Salesforce Knowledge articles separately
Knowledge articles are not ordinary CRM records for this operation. Salesforce’s documented process is to export the article data, edit the exported content externally, and update it with Data Loader.
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Use the correct Knowledge object
- Lightning Knowledge: the article object shown in Salesforce documentation is
Knowledge__kav. - Classic Knowledge: use the article-type-specific object, written as
ArticleType__kav.
Your actual object and field names can differ by Knowledge setup and article type, so confirm them in your org before building the CSV.
Preserve valid rich-text HTML
Rich-text fields export as HTML. Replace visible text without breaking tags, entities, links, lists, or image markup. A missing closing tag or malformed attribute can change the article’s layout or prevent a successful update. Keep a copy of the unedited export so the original HTML can be restored if needed.
Move published articles to Draft one at a time
Data Loader can update draft Knowledge articles. Published articles must first be set to Draft individually, then included in the export and update process. Salesforce states that there is no standard supported mass-update operation for changing published articles to Draft. Custom or third-party approaches described in Salesforce Help are not supported out-of-the-box Salesforce solutions, so treat them as a separate governance decision rather than part of the standard procedure.
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Account for article versions and translations
Inspect the article version, publication state, language, and archived status in your export. A replacement in one language or version does not prove that every translated, archived, or separately published version contains the new name. Track exceptions and assign a follow-up owner for each one.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Verify that the old name is gone where you intended
- Read the success CSV. Confirm that the number of successful rows matches the intended batch and that the IDs are the IDs you exported.
- Resolve the error CSV. Group errors by cause, such as validation rules, permissions, required fields, invalid HTML, duplicate matches, locked records, or automation failures. Correct the source data or process configuration, then retry only the failed rows.
- Search again. Re-run Global Search, object list-view filters, and reports for every old-name variant. An empty Global Search result is useful evidence only for indexed fields and accessible records.
- Inspect representative records. Open records from each object, field type, and update batch. Check that unrelated fields, links, formatting, and automation-driven values were not changed.
- Check Knowledge states. Review updated draft articles and the publication workflow. Confirm that articles intentionally moved to Draft are republished only after editorial approval.
- Check outside Salesforce. Search the external documentation stores listed in your scope. Salesforce tools do not establish coverage of those systems.
- Document exceptions. Record translated versions, archived content, hidden fields, non-indexed fields, records excluded by sharing, and any external or configuration locations that were not changed.
Declare completion only for the objects, fields, article versions, and external stores you actually checked. “No search results” is not equivalent to “no occurrences” when a field is not indexed or was outside the export.
8. Troubleshoot common failures
| Symptom | Likely cause | Action |
|---|---|---|
| Global Search finds nothing, but users still see the old name | The value is in a non-indexed field, an inaccessible record, or an unsearched variant | Search the object’s list views and reports, export candidate fields, and verify sharing and spelling variants. |
| Data Loader reports “no match” | The ID is wrong, truncated, reformatted, or mapped to the wrong field | Compare the ID with the untouched export, preserve it as text, remap the column, and retry failed rows only. |
| Rows update but unrelated fields change | The CSV contained extra columns or blank values that were mapped for update | Restore from the backup if necessary, then create a narrow CSV containing only the ID and intended fields. |
| Knowledge update fails on rich text | Exported HTML was malformed or altered incorrectly | Compare the edited HTML with the original, repair tags and entities, test one draft article, and inspect the rendered result. |
| A published Knowledge article cannot be updated | Published articles are not eligible for the documented Data Loader update flow | Set the article to Draft individually, then export and update it. Follow your editorial approval process before republishing. |
| Some records remain unchanged after a successful batch | They were excluded by the filter, failed validation, were inaccessible, or contain a different variant | Compare intended IDs with success and error files, search variants, and process the remaining IDs after correcting the cause. |
9. Volume guidance and operational controls
For fewer than 50,000 records in a supported object, Salesforce Help (2026) says to consider Data Import Wizard. Another Salesforce mass-update overview describes Data Loader for approximately 50,000 to 100,000 records, while a separate FAQ recommends Data Loader above 50,000 and below 5 million. The Data Loader overview states that files up to 5 million records are supported, and Salesforce’s mass-update FAQ directs customers above 5 million toward a Salesforce partner or AppExchange option.
These figures come from different Salesforce pages and contexts. Before a production job, verify your org’s current API and storage limits, object support, validation and automation behavior, maintenance windows, and any internal change-control requirements. A smaller, staged update is often safer than one large transaction when records have complex automation.
Quick Recap
10. A practical completion checklist
- Old and new strings, variants, and exclusions are written down.
- Objects, fields, Knowledge article types, versions, languages, and external stores are inventoried.
- Global Search, list views, and reports were used with an understanding of indexing limits.
- Candidate IDs were exported and an untouched backup was retained.
- The update CSV contains only the intended fields and a stable matching ID.
- A representative test subset was processed first.
- Column mappings, success files, and error files were reviewed.
- Knowledge articles were treated according to publication state, with published articles moved to Draft individually.
- Post-update searches and record/article inspections were completed.
- Exceptions such as translations, archived content, hidden fields, and external documentation were recorded.
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