---
schema_version: "1"
id: 6b286cad25147f5d6fdba6d4363309d99013ca3f0e77bb9bcb414caf0a60f5cc
title: Prepare to Convert State, Country, and Territory Data
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/xcloud/264-0-0/admin_state_country_picklists_convert_overview.md
canonical_url: https://help.salesforce.com/s/articleView?id=xcloud.admin_state_country_picklists_convert_overview.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: bfd3c51b6a449585724ccbc9162c9b06425718e7d352728b485c505930297e5b
description: If your Salesforce organization includes text-based state, country, and territory values, you can convert that data to standardized picklist values.
products:
  - Salesforce Platform
  - Cross Cloud
release: "264"
---
# Prepare to Convert State, Country, and Territory Data

If your Salesforce organization includes text-based state, country, and territory values, you can convert that data to standardized picklist values.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: both Salesforce Classic and Lightning Experience</td></tr><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: <strong>All</strong> Editions except Database.com</td></tr></tbody></table>

Converting existing data allows you to keep working with the data after you switch to picklists. For example, say you have a report that culls all your sales reps’ leads in Washington state. The report is generated from state picklist value Washington. To ensure that records with text-based state values such as Wash., WA, and Washington are included in the report, convert text-based state data to standardized picklist values.

Converting existing state, country, and territory text data into standardized picklist values helps ensure data integrity after you enable picklists in your organization. Your users encounter validation errors when saving records that contain state, country, or territory values that aren’t in your picklists. Also, reports become unreliable when records created before you enable state and country/territory picklists contain different state, country, and territory values than records created using picklists.

When you convert data, Salesforce starts with countries and territories, then goes on to states. As you go through the conversion process, here are a few things to keep in mind:

- Save frequently. You can exit the conversion tool and return to it at any time.
- You can continue to work normally in your organization while converting data.
- You can’t convert data while you’re scanning for affected data and customizations, or while state or country/territory picklists are being deployed.
- Steps can be repeated and undone at any time until you enable the picklists for users. After the picklists are enabled, you can’t undo the conversion.

#### See Also

- [Convert State and Country/Territory Data](https://help.salesforce.com/s/articleView?id=xcloud.admin_state_country_picklists_convert_data.htm&release=264.0.0&type=5 "To convert text-based state and country/territory data to picklist-compatible values, select specific text values and choose the standard values you want to map them to. For example, you can select all occurrences of “USA” and change them to “United States.”")
- [Let Users Select States, Countries, and Territories from Picklists](https://help.salesforce.com/s/articleView?id=xcloud.admin_state_country_picklists_overview.htm&release=264.0.0&type=5 "State and country/territory picklists let users select states, countries and territories from predefined, standardized lists, instead of entering state and country/territory data into text fields. State and country/territory picklists offer faster and easier data entry. They help to ensure cleaner data that can be harnessed for other uses—in reports and dashboards, for example. They protect data integrity by preventing typos, alternate spellings, and junk data—even in records updated through the API.")