liminals.
Analyze·Beginner·Playground·15 min·Updated Sep 30, 2026

Clean messy customer data

Excel×ChatGPTClaudeCopilot

Scenario

You inherited a CRM export filled with duplicate entries, inconsistent formatting, and missing fields.

Mission

Standardize the dataset and identify the true number of unique customers.

Start Files

customer-data-messy.csv
Raw CRM export with 1000 rows.
FirstNameLastNameEmailPhoneNumber
FinleyDubois finley.dubois667@example.com 597.901.3660
SkylerLarsenskyler.larsen114@example.com(772) 371-9647
AveryMorettiavery.moretti536@example.com(768) 440-4479
JordanFischerjordan.fischer155@example.com(505) 730-8626
JamieMorettijamie.moretti658@example.com(440) 428-2879
Preview — first 5 rows of customer-data-messy.csv

Your task

  1. Standardize all email addresses to lowercase.
  2. Remove duplicate rows based on email.
  3. Fix the formatting in the "Phone Number" column.

Prompt idea:

Here are 20 sample rows from a CRM export. Write an Excel formula (or a short Power Query step) that lowercases the email column, flags duplicate emails, and normalizes phone numbers to a single format. Explain each step.

Check Your Result

After deduplicating, how many unique customers are in the dataset?

Need a hint?

Normalize case and whitespace on the email column before counting duplicates.

Reveal Solution

The solution files contain the completed challenge. Review the approach to see if you missed any edge cases.

customer-data-solution.csv

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