How to Prepare and Import Client Data

September 08, 202610 min read

How to Prepare and Import Client Data

Client-provided data is rarely ready to import exactly as received. The file may contain valuable names, property details, telephone numbers, email addresses, and notes, but it will usually be missing several internal fields that tell the Meskula system where the records came from, who owns them, which automations should run, and when the contacts may be called.

The staff member preparing the import is responsible for converting the client’s file into a clean, standardized dataset before it reaches the CRM. That means preserving useful information, renaming columns to match our import fields, adding the required internal values, removing duplicates, and validating the final file.

Watch the Training Video

Use the video for the spreadsheet demonstration. The procedure below should be followed as the written standard for future client-data imports.

The Five Fields Most Client Files Will Be Missing

Most client exports will not include these Meskula-specific fields:

  1. Referral Agent

  2. Tags

  3. Time Zone

  4. Source

  5. Property Notes

These are not optional housekeeping fields. They help control ownership, segmentation, calling times, automation, reporting, and preservation of useful information that does not have its own CRM field.

Before preparing an import, determine the correct value or rule for each of them.

Required Discovery Before You Edit the File

Do not guess at the missing internal values. Confirm the following before proceeding:

  • What type of leads are in the file?

  • Which agent should receive the leads?

  • What source name should be applied?

  • Which tags are required?

  • Does the agent have ISA service?

  • Should normal automation run, or should No Automation be applied?

  • Are all records in one time zone, or must time zone be derived record by record?

  • Does the client file contain auxiliary information that should be preserved in Property Notes?

This discovery step determines how the imported contacts will behave after they enter the CRM.

Typical Client-Provided Fields

A client file may already include some or all of the following:

  • Owner or contact name

  • Property street address

  • Property city

  • Property state

  • Property ZIP code

  • Mailing street address

  • Mailing city

  • Mailing state

  • Mailing ZIP or postal code

  • Email address

  • Best callable phone

  • Additional telephone numbers

  • Property type

  • Bedrooms

  • Bathrooms

  • Square footage

  • Year built

  • Estimated property value

  • Absentee-owner status

  • Years at the property

  • Profile tags, notes, or other source-system data

Preserve useful information even when its original column name does not match the destination CRM field.

Step 1: Start With the Approved Import Headers

Use the header row from the appropriate Meskula import template, such as the farm, expired, or other lead-type formula sheet.

The template headers serve two purposes:

  • They identify the fields expected by the CRM.

  • They provide the exact column names used during field mapping.

Insert or copy the approved header row into a working copy of the client file. Do not modify the client’s original source file.

Step 2: Rename and Map the Client’s Columns

Review every client column and rename it to the matching CRM import field.

Common examples include:

  • Owner NameName

  • Property AddressProperty Address

  • City for the property → Property City

  • State for the property → Property State

  • ZIP for the property → Property ZIP

  • Best Callable PhonePhone

  • EmailEmail

  • Year BuiltProperty Year Built

  • Estimated ValueProperty Estimated Value

Mailing-address fields must remain separate from property-address fields:

  • Mailing street address → Address

  • Mailing city → City

  • Mailing state → State

  • Mailing ZIP → Postal Code

This distinction is critical. Property Address identifies the real estate. Address identifies where the owner receives mail. They may be different when the owner is absentee.

Step 3: Standardize the Primary Name, Phone, and Email

If the client provides a complete owner name in one column, map it to Name. Separate First Name and Last Name fields may be used when reliably available, but a valid complete Name field is sufficient for this workflow.

Map the preferred or best callable telephone number to Phone. Preserve additional callable numbers when they are useful, but do not create several competing primary phone fields.

Before import, normalize phone numbers to the CRM’s accepted format. Confirm whether the current import workflow requires the United States country code 1. Do not add or remove a country code without checking the applicable import standard.

Map the primary email address to Email. Retain additional email data in an approved secondary field or notes when appropriate.

Step 4: Preserve Unmapped Information in Property Notes

Client files often contain useful data that does not have a dedicated import field. Examples may include:

  • Original profile tags

  • Secondary phone numbers

  • Source-system comments

  • Other relevant property or contact indicators

Do not discard this information merely because it does not map directly.

Create a Property Notes column and combine the useful unmapped values into it. In a spreadsheet, this can be done with a concatenation formula such as:

=G3&" "&M3&" "&N3

The actual column letters will depend on the client file. Verify each referenced column before filling the formula down.

Use separators or labels when needed so the combined notes remain understandable after import. Never move legally sensitive flags, consent information, Do Not Call indicators, or other compliance data into a general notes field if doing so would prevent the system from enforcing the correct restriction.

Step 5: Add the Source

Create a Source column and enter a consistent value for every record.

The source should identify where the data originated. Depending on the project, that may be:

  • The client or agent’s name

  • A named database or vendor

  • A campaign or list source

  • A combination of client and lead type

Use one approved spelling throughout the import. Inconsistent source names fragment reporting and make later analysis more difficult.

Step 6: Add the Time Zone

Create a Time Zone column.

Use the property ZIP code and the approved ZIP table to determine the correct CRM time-zone value. Copy the value from the lookup table exactly; do not invent an abbreviation or use a casual label such as “East Coast.”

If the entire list is genuinely in one time zone, the same verified value may be filled down. If the file spans multiple time zones, derive the value for each record.

Time zone is operationally important because it helps the calling and messaging systems contact leads at appropriate local times.

Step 7: Add the Required Tags

Create a Tags column and confirm the tag set before importing.

The tags will vary by client and lead type. They may identify:

  • Lead category, such as Farm or Expired

  • Service status, such as Has ISA

  • Automation control, such as No Automation

  • Other approved campaign or operational classifications

Separate multiple tags using the format required by the import process, typically commas.

The training example required three operational decisions:

  • The contacts were farm leads.

  • The client had ISA service.

  • The client did not want automation.

Therefore, the file required the applicable equivalents of Farm, Has ISA, and No Automation.

Do not copy the example blindly. Ask which tags apply to the current client.

Step 8: Add the Referral Agent

Create a Referral Agent column and enter the exact approved agent name for every applicable record.

This field controls lead ownership and reporting. Before filling it down:

  • Confirm the correct agent.

  • Confirm the spelling used in the Meskula system.

  • Make sure the same person is not represented by two name variations.

  • Verify that the file does not contain leads belonging to multiple agents.

If several agents are represented, assign Referral Agent record by record or separate the file into clearly controlled imports.

Step 9: Fill the New Values Through the Dataset

After validating the formulas and fixed values in the first actual data row:

  1. Select the cells containing Source, Time Zone, Tags, Referral Agent, Property Notes, and any other added values.

  2. Fill or copy them through the final data row.

  3. Check several records near the beginning, middle, and end of the file.

  4. Confirm that formulas adjusted correctly and fixed values remained consistent.

Do not assume a fill-down succeeded merely because the first few rows look correct.

Step 10: Remove Extra Headers and Blank Rows

Client data may have been combined from several worksheets or exports. This can leave repeated header rows and blank separator rows inside the dataset.

Remove:

  • Repeated headers

  • Blank rows

  • Section titles

  • Totals

  • Notes outside the contact records

  • Formatting-only rows

The final file should contain one header row followed immediately by one lead per row.

Step 11: Remove Duplicate Properties

Deduplicate the data using the complete property location rather than the contact name.

In Google Sheets, use Data > Data Cleanup > Remove Duplicates and select:

  • Property Address

  • Property City

  • Property State

  • Property ZIP

Confirm that the range has a header row before running the cleanup.

Using the complete property address prevents one property from being imported several times while reducing the risk of deleting different properties that happen to have a similar street address.

Record how many duplicate rows were removed. A large or unexpected number should be investigated.

Required-Field Summary

Before import, the file should include or intentionally address these field groups:

Internal fields commonly missing from client data

  • Referral Agent

  • Tags

  • Time Zone

  • Source

  • Property Notes

Core identity and contact fields

  • Name

  • Phone, when available

  • Email, when available

Property fields

  • Property Address

  • Property City

  • Property State

  • Property ZIP

  • Property Type, when available

  • Bedrooms, when available

  • Bathrooms, when available

  • Square Feet, when available

  • Property Year Built, when available

  • Property Estimated Value, when available

Mailing fields, when available

  • Address

  • City

  • State

  • Postal Code

Common Mistakes to Avoid

  • Importing the client file without first identifying the lead type.

  • Assuming client column names will automatically match CRM fields.

  • Confusing the property address with the owner’s mailing address.

  • Forgetting Referral Agent, Tags, Time Zone, Source, or Property Notes.

  • Applying the wrong agent name or an inconsistent spelling.

  • Copying tags from another client without confirming automation and ISA status.

  • Applying one time zone to a multistate list.

  • Discarding useful unmatched fields instead of preserving them appropriately.

  • Moving compliance restrictions into notes where automation cannot enforce them.

  • Filling formulas down without checking the last row.

  • Deduplicating by name instead of the complete property address.

  • Leaving repeated headers or blank separator rows in the import file.

  • Overwriting the original client file instead of working from a copy.

Final Pre-Import Checklist

Confirm all of the following before uploading the file:

  • The lead type is known.

  • The correct Referral Agent has been confirmed.

  • Required tags have been confirmed, including ISA and automation controls.

  • Source is populated consistently.

  • Time Zone is populated correctly for every record.

  • Useful unmapped information has been preserved in Property Notes or another approved field.

  • Client columns have been renamed to the exact CRM import fields.

  • Property and mailing addresses are mapped separately.

  • Primary phone and email fields are mapped correctly.

  • Phone formatting follows the current import standard.

  • Added values and formulas extend through the final record.

  • Repeated headers and blank rows have been removed.

  • Duplicate properties have been removed using Address, City, State, and ZIP.

  • The duplicate-removal count has been reviewed.

  • The original client file remains preserved.

  • The cleaned working file contains one header row and one lead per row.

Final Takeaway

A successful client-data import is not simply a column-mapping exercise. It is the point where raw client information becomes operational Meskula data.

The client will often provide the property and contact facts. Staff must add the internal context that makes those facts usable: who owns the leads, where they came from, when they may be contacted, which services apply, which automation should run, and which extra information must be preserved.

When Referral Agent, Tags, Time Zone, Source, Property Notes, field names, and duplicate controls are handled correctly, the file is ready for the next stage of import.

Demitri

Demitri

Real Estate Coach, Author

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