Add Rows to Excel in Make

What this module does

Add Rows to Excel is a Make module by PDF4me that dynamically inserts JSON data as rows into Excel spreadsheets inside a Make scenario. Use it when you need to populate Excel files from database queries, REST API responses, form submissions, or CRM exports on a schedule or trigger. The module supports both table-based header matching and coordinate-based cell positioning, with automatic type conversion and culture-specific date and number parsing.

Always wrap single objects in an array

The Json Input field requires a JSON array even when inserting just one row. Use [{"Name":"John","Age":30}] not {"Name":"John","Age":30}. Passing a plain object without array brackets will cause an error. Each object in the array inserts one sequential row starting from the configured position.

Table Name triggers table mode, empty triggers coordinate mode

When you provide a Table Name, the module uses Excel table header matching and inserts at the specified Excel Row Number within the table. Leave Table Name empty to use coordinate mode and specify Insert From Row and Insert From Column for precise cell-level positioning. Never mix both modes.

Set Culture Name to match your data source locale

The Culture Name field controls how dates and numbers in your JSON are parsed before insertion. The default en-US expects MM/DD/YYYY dates and period decimal separators. If your data comes from a European API using de-DE or fr-FR conventions, set Culture Name accordingly to prevent incorrect date and number parsing.

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Authenticating Your API Request

To access the PDF4me Web API through Make, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user, enabling seamless integration between your Make scenarios and PDF4me's Excel data insertion services.

Get your API Key

Set Table Name to use header-matched table insertion, or leave it empty and set Insert From Row and Insert From Column for coordinate-based positioning. Enable Convert Numeric And Date to apply Excel type formatting.

How Do I Add Rows to Excel Automatically in Make?

The PDF4me Add Rows to Excel module connects to any Make trigger that produces structured data. A typical flow downloads the target Excel template from Google Drive or Dropbox, then passes the JSON data from a prior module into the Json Input field. According to the Make integration documentation, PDF4me modules process files as binary buffers, so the updated Excel file returns on the Doc Data output ready to upload directly. For the most common use case (inserting database or API results into an Excel table), set Table Name to your named Excel table and set Convert Numeric And Date to Yes to ensure numbers and dates render correctly in the spreadsheet.

Parameters

Important: Parameters marked Required must be provided. Conditional parameters have built-in defaults and apply only in specific modes.

Parameter	Required	What it does	Example
Connection	Required	PDF4me connection holding your API key. Create one from the Make Connections panel.	My PDF4me connection
File Name	Required	Excel filename with .xlsx or .xls extension. Maps to the output filename. Map from a prior download module or use a dynamic expression.	sales_data.xlsx
Document	Required	Binary Excel file content as a Make buffer. Map from Google Drive, Dropbox, SharePoint, or HTTP download module.	1. Data
Json Input	Required	JSON array of objects to insert as rows. Each object = one row. Always use array brackets. Property names match column headers in table mode or define column order in coordinate mode.	[{"Product":"Widget","Qty":50}]
Worksheet Name	Conditional	Name of the target worksheet. Defaults to Sheet1 if omitted. Case-sensitive. Must match the worksheet tab name exactly.	Sales
Table Name	Conditional	Excel table name for table-based insertion. When set, enables header-matching mode. Leave empty for coordinate-based insertion. Never use with Insert From Row/Column.	SalesTable
Excel Row Number	Conditional	1-based row position within the table for insertion (table mode only). Set to 1 to insert at the first data row after headers.	1
Insert From Row	Conditional	1-based row number for insertion start (coordinate mode only). Error if used together with Table Name. Row 1 = the first worksheet row.	3
Insert From Column	Conditional	1-based column number for insertion start (coordinate mode only). Column A = 1, B = 2. Error if used together with Table Name.	1
Convert Numeric And Date	Conditional	When Yes, converts JSON strings to Excel number and date types using Date Format and Numeric Format patterns. Default: Yes.	Yes
Date Format	Conditional	Excel date format pattern applied when Convert Numeric And Date is Yes. Default: yyyy-MM-dd. Common formats: MM/dd/yyyy, dd-MMM-yyyy.	MM/dd/yyyy
Numeric Format	Conditional	Excel numeric format pattern applied when Convert Numeric And Date is Yes. Default: N2. Common: #,##0.00, 0.00%.	#,##0.00
Ignore Null Values	Conditional	When Yes, skips JSON null values instead of inserting empty cells. Default: No. Useful for optional form fields that may be absent from the JSON.	No
Ignore Attribute Titles	Conditional	When Yes, enables case-insensitive matching between JSON property names and Excel column headers. Default: No.	Yes
Culture Name	Conditional	Culture code for parsing dates and numbers in the JSON data. Default: en-US. Set to de-DE, fr-FR, etc. for European data sources.	en-US

Output

The PDF4me Add Rows to Excel module returns two fields on the output bundle:

Field	Type	What it contains
Name	String	Output Excel filename derived from the File Name input. Use in the destination upload module File Name field.
Doc Data	Buffer	Binary Excel content with the newly inserted rows as a Make buffer. Map into Google Drive Upload, Dropbox Upload, SharePoint Create File, or Email Send attachment.

Scenario Examples

The PDF4me Add Rows to Excel module in Make provides comprehensive scenario templates for real-world data automation needs:

Database Export

Automated Daily Sales Data Export Scenario

Transform your sales reporting with automated database-to-Excel data insertion:

1. Trigger: Scheduled trigger runs daily at 11 PM
2. Query Database: Execute SQL query to fetch today's sales transactions
3. Format JSON: Convert SQL results to JSON array format
4. Get Excel Template: Fetch sales report template from Google Drive
5. Add Rows: Insert JSON data into DailySales table, TableName set, ExcelRowNumber = 1
6. Upload Result: Save to Google Drive daily reports folder
7. Email Report: Send updated Excel to sales managers

Business Benefits: Inserts 200+ daily sales records automatically, eliminates 2 hours of manual data entry, ensures consistent date and currency formatting.

Create Scenario

API Data Population

Automated REST API to Excel Integration Scenario

Populate real-time dashboards from API data on a schedule:

1. Trigger: Scheduled hourly data refresh
2. Call REST API: Fetch JSON array from analytics service
3. Get Excel Dashboard: Retrieve dashboard file from Dropbox
4. Add Rows: Insert at coordinates, InsertFromRow = 3, InsertFromColumn = 2
5. Enable Conversion: ConvertNumericAndDate = Yes for metrics formatting
6. Upload Updated: Save refreshed dashboard to Dropbox

Business Benefits: Refreshes Excel 24 times daily, provides near real-time visibility in familiar Excel format, eliminates manual API data extraction.

Create Scenario

Form Response Logging

Automated Form Submissions to Excel Logging Scenario

Log every form submission into a running Excel tracker:

1. Trigger: Webhook receives new form submission
2. Parse Submission: Extract form field values from webhook payload
3. Get Excel Log: Retrieve form responses log from Google Drive
4. Add Row: Insert in coordinate mode, IgnoreNullValues = Yes for optional fields
5. Upload Log: Save updated Excel log to Google Drive
6. Email Confirmation: Send receipt to form submitter

Business Benefits: Logs 500+ form submissions monthly, eliminates manual transcription, handles optional fields with null value skipping.

Create Scenario

CRM Export

Automated Weekly CRM Data Export Scenario

Export CRM pipeline data to Excel for sales leadership every Monday:

1. Trigger: Scheduled weekly on Monday at 8 AM
2. Query CRM: Get new opportunities from last week via API
3. Get Excel Template: Fetch weekly opportunities template from Dropbox
4. Add Rows: Insert into Opportunities table, IgnoreAttributeTitles = Yes for flexible matching
5. Format Currency: NumericFormat = "#,##0.00" for deal values
6. Email Sales Team: Distribute Excel to sales leadership

Business Benefits: Exports 100+ CRM opportunities weekly, ensures accurate currency and date formatting, reduces manual reporting time by 95%.

Create Scenario

Industry Use Cases & Applications

Sales & Marketing

• CRM Pipeline Reports: Insert opportunity data into Excel sales pipelines
• Lead Tracking Sheets: Add new leads from forms to Excel tracking logs
• Campaign Analytics: Populate marketing results from analytics APIs
• Customer Database: Export customer data from databases to Excel lists

Finance & Accounting

• Transaction Logs: Insert daily financial transactions into Excel ledgers
• Expense Tracking: Add employee expense submissions to Excel reports
• Budget vs Actual: Populate actual spending data into budget templates
• Invoice Line Items: Insert invoice data into Excel invoice templates

Human Resources

• Employee Records: Add new hire information to Excel employee databases
• Attendance Tracking: Insert daily attendance data into Excel timesheets
• Payroll Processing: Populate hours worked into Excel payroll templates
• Performance Data: Add review scores and metrics to Excel trackers

Operations & Supply Chain

• Inventory Updates: Insert stock level changes into Excel inventory sheets
• Production Logs: Add production run data to Excel manufacturing logs
• Quality Metrics: Populate QC results into Excel quality reports
• Maintenance Records: Insert equipment maintenance data into Excel logs

When Should I Use Add Rows to Excel in Make?

Use Add Rows to Excel when you need to append structured data from any Make-connected source into an existing Excel spreadsheet as part of an automated workflow. This module is ideal for database exports, API polling, form logging, and CRM reporting where the target file already exists and you are adding new records. If you need to create a new Excel file from scratch or convert data to a different format, check the other PDF4me Excel modules available in Make. According to Microsoft's Excel data model documentation, using Excel named tables (versus raw coordinates) gives you automatic header matching, formula propagation, and structured reference support, which is why table mode is the recommended approach for most workflows.

Common Questions

How do I add rows to an Excel file in Make automatically?

Add the PDF4me Add Rows to Excel module after a trigger that delivers your data. Download the target Excel file from Google Drive or Dropbox in a prior module, map File Name and Document, set Json Input to a JSON array of objects, configure the insertion mode, then map Doc Data from the output to an upload module. For detailed setup guidance, see PDF4me Make documentation.

What is the difference between table-based and coordinate-based insertion?

Table-based insertion (set Table Name) uses Excel named table header matching: JSON property names map to column header names regardless of column order. Coordinate-based insertion (leave Table Name empty) uses Insert From Row and Insert From Column for precise cell-level positioning where JSON object property order determines column placement. Never combine both modes in the same module call. For structured data with consistent column headers, table mode is more robust and easier to maintain.

Why must I wrap a single row in an array for Json Input?

The module always expects a JSON array because it iterates over the array items to insert multiple rows in a single call. A plain JSON object without brackets is not an array and causes a parsing error. Use [{"Field1": "value1"}] for a single row and [{"F1":"v1"}, {"F1":"v2"}] for multiple rows. The JSON specification treats arrays and objects as distinct types, and this module requires the array type to support batch row insertion.

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