How to import customer data into TaylorDB

If your team already tracks customers in spreadsheets, CSV exports, or another CRM, TaylorDB can turn that existing data into a usable workspace. The important part is not just uploading rows. It is keeping the structure clear enough that Taylor can help your team work with it afterwards.

This guide walks through a practical import flow for customer data: preparing the file, mapping columns, reviewing the preview, and deciding what should happen after the records arrive.

Prepare your file

Start with the columns your team actually uses. A good import usually includes customer name, company, email, phone, status, owner, notes, and the last meaningful interaction. You can add more fields later, but a focused first pass is easier to validate.

• Use one header row with clear column names.
• Keep one customer or company per row.
• Separate combined fields such as full address or owner notes when possible.
• Remove test rows, blank rows, and duplicate exports before uploading.

Company,Primary contact,Email,Owner,Status,Last interaction
Northstar Studio,Avery Chen,avery@northstar.example,Sam,Active,2026-06-02
River House Supply,Mina Patel,mina@riverhouse.example,Jordan,Needs follow-up,2026-05-28

Choose the right workspace

Import into the workspace where your team will actually operate. For a CRM, that usually means a customer table connected to deals, tasks, support requests, or projects. TaylorDB works best when imported data lands near the workflows it supports.

1. Open the TaylorDB workspace that should receive the data.
2. Create a new table or open the existing customer table.
3. Start the import flow and select your CSV file.
4. Review the preview before committing the import.

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Map columns intentionally

Column mapping is where the import becomes useful. Match obvious fields directly, then pause on anything ambiguous. For example, a spreadsheet column called "Status" might mean lifecycle stage, payment status, support state, or sales priority.

Review the preview

Before the import runs, scan the preview like a teammate would scan the finished table. Names should be readable, emails should look like emails, empty values should be expected, and date columns should land in the same format.

1. Check the first ten rows and a few rows near the end of the file.
2. Confirm required fields are present for the workflows your team depends on.
3. Look for duplicate customers that should merge instead of becoming new records.
4. Cancel and fix the source file if the preview looks noisy.

After the import

Once the records are in TaylorDB, add the views your team needs first: active customers, open follow-ups, recently imported records, and records missing an owner. This gives everyone a calm place to start cleaning and acting on the data.

From there, ask Taylor to help summarize segments, find gaps, create follow-up tasks, or draft the next outreach. The import is the beginning of the workflow, not the end of it.