Salesforce Data Recovery – Tips for Preparing Data for Salesforce Import

When you are trying to import data to Salesforce for the first time, recover the old data, or improve the existing data, you have to follow the best practices. Doing it in the proper way will make it easier for you to achieve the optimum outcome. High-quality data is the primary driver of user adoption and get accurate dashboards. This means the users and admins can get a better insight into the sales pipeline and performance with the use of accurate data. The best way to prepare to be an Administrator or a platform app builder is through the Salesforce certification.

You need to also remember that if you import data to Salesforce, you need to prepare a proper template for a winning start. Let us explore a few healthy tips to prepare your enterprise data for a winning Salesforce import.

Data import with a spreadsheet

You cannot do data import into Salesforce from any random spreadsheet. At first, the spreadsheet needed to be structured and formatted properly. You can try downloading some standard templates offered by the Salesforce vendors to get it done well. For spreadsheet import, you need to collate the data from different sources as other existing CRMs, accounting software, user spreadsheets, etc. You have to pull it together into the spreadsheet for import.

If you are trying to enhance the existing data, you may create a tubular report first, which contains the contact and account data you want to upgrade. You may also include Account ID as well as Contact ID etc., which you may need while importing the changes. You may also export the report in CSV format and follow the below stages to improve the data quality. Once done, you can use Data Import Wizard for updating existing data. Here are some of the fields you have to update.

  • Account Name

You may first sort spreadsheet data with Account Name. Scroll through the list and correct any spell errors, check and remove any inconsistencies, and add any missing data if you have it handy. You have to maintain one row for each contact and ensure there are consistent account names for each row.

  • Address

There may be many components to the Street Address. It is important to maintain Street Address for the specific account to be kept in a single cell. You can separate different parts by a comma, for example.

“2nd Floor, 9th Boulevard, Remington Street. Then scroll through the list and strip out any phone numbers, zip codes, etc., from the street column. You can put this data into the corresponding columns in the spreadsheet.

  • City and State

You may further sort the spreadsheet each column-wise. Check the list and ensure that data is consistent in each column. The city column must contain only the city and so for the State, Country, and ZIP code fields. When you attempt the Salesforce data recovery, you get all these data in the CSV format, where you can do this sorting as in a spreadsheet to cleanse data before import. While putting in city names, ensure that abbreviations against values are kept consistent if you use NY for New York or the UK for the United Kingdom. Either one format is kept consistent and not mixing up both.

Telephone numbers and email addresses

Maintain separate columns for phone numbers and email IDs. This is the most important data in terms of customer acquisition, service delivery, and customer support. Most of the time, problems arise due to incorrectly formatted phone numbers and email addresses. While entering phone numbers, ensure it is there in full and add preceding zero, if any. For emails, check if @ is missing and no character space is left within the mail address. You can easily search for these by using the search option on a spreadsheet.

Once updating these, check for any errors by sorting with Names. Ensure first and second names are capitalized and formatted properly so that when you generate an email from the backend, it shows correctly. Ensure all names you have in the sheet are spelled legitimately to avoid any customer dissatisfaction.

Industry types and fields

Next, you may set the apt values for industry fields and types. There are chances that you may not know it, and you may just leave it blank. You may better put standard picklist values for such fields. Some of the standard picklist values may be Customer, Supplier, Prospect, Employee, and so on. There are many such standard values to be put in the industry field. You can also customize the same for your business needs.

Setting field length

It may be frustrating to see that you have put in a lot of effort to streamline your data for import, but in the end, find that it is noted loaded well as the field length is too long. Make sure each field in Salesforce complies with the maximum length. Let us see the maximum field length to be set for the most important fields as below:

Account Name – 255 characters

Street Name – 255 characters

Telephone number – 40 characters

Email ID – 80 characters

First Name & Last Name – 80 characters, etc.

You also need to consider that spaces will be counted as characters while testing Salesforce data.

Once your data preparation is done, next you can go ahead with data import. You may also take the assistance of some of the data import resources if needed. Some of the top utilities are.

  • Account & Contact Import wizard.
  • Template for Excel Account and Contact data spreadsheet.

If you have custom fields on Salesforce and need to import matching data, you may create additional columns accordingly. You may use the field name as column headers. It does not matter where you insert the columns; you need to just locate and map the same in the corresponding spreadsheet. If record types are used for Accounts, then you may create another column for the same. Using Data Loader for import, you have to enter the record type ID and not the name.

Having a proper data import template will make your data loading or recovery much simpler and quicker. A proper data import structure is also necessary in order to ensure that you can use your Salesforce data optimally in the case of analytics and decision-making.

By 12disruptors Admin

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