Merge Rows by ID

Consolidate Scattered Data into Single Records

Databases often generate multiple rows for a single user if they perform multiple actions. You might have three rows for 'John Doe': one listing his email, one listing his phone number, and one listing a recent purchase. Standard deduplication would simply delete the extra rows, causing you to lose valuable data. The Merge Rows by ID tool groups rows sharing a common identifier and smartly consolidates their unique data points into one master row.

How the Grouping Engine Works

You select a 'Primary Key' column (e.g., 'Customer ID' or 'Email'). The engine scans the document and groups all rows that share that exact key. For the remaining columns, it looks at the data within the grouped rows. If one row has a blank cell and another has data, it merges the data into the master row. If multiple rows have conflicting data (e.g., two different phone numbers), you can configure the tool to either keep the newest one or concatenate them together (e.g., 'Phone1, Phone2').

Step-by-Step Usage

1. Upload your .xlsx or .csv dataset.
2. Select the 'Primary Key' column to group by.
3. Choose conflict resolution: 'Keep First', 'Keep Last', or 'Concatenate'.
4. Click the 'Merge Rows by ID' button.
5. The engine consolidates the scattered data.
6. Review the condensed, data-rich master rows.
7. Download your unified spreadsheet.

Key Benefits

• Prevents Data Loss: Unlike simple deduplication, this ensures fragments of data are saved and combined.
• Creates Master Profiles: Perfect for building unified customer views from scattered CRM logs.
• Conflict Resolution: Total control over how overlapping data is handled (override vs concatenate).
• Cleans Databases: Radically shrinks row counts while maximizing data density per row.

Real-World Use Cases

CRM managers use this to build 'Golden Records'; if a user filled out three different lead forms over a year with different pieces of info, this tool merges them all into one rich contact profile. Event managers combine multiple ticket purchase rows by a single 'User ID' and concatenate the ticket numbers into one cell. Financial analysts group multiple micro-transactions by 'Account ID' to prepare data for summing.

Pro Tips for the Best Results

The success of this tool relies heavily on the 'Primary Key' being an exact match. If grouping by 'Email', run the 'Trim Whitespace' and 'Change Text Case' (lowercase) tools on the email column first. This ensures 'John@email.com' and 'john@email.com ' are recognized as the exact same ID, guaranteeing all of John's scattered data is successfully merged into a single row.

Top Use Cases

• Creating unified 'Golden Records' from scattered CRM logs
• Concatenating multiple purchase IDs to a single customer row
• Merging incomplete survey submissions from the same IP address

Frequently Asked Questions