Data Import and Export

Whether you are migrating from another system, uploading a list of leads from a trade show, or exporting data for analysis in a spreadsheet, Ambivo's import and export tools help you move data in and out of the platform efficiently. This guide walks you through the entire process — from preparing your file to reviewing results.

What Is Data Import and Export?

• Import — Upload records from a CSV file (spreadsheet) into Ambivo. You can import leads, contacts, accounts, opportunities, products, and custom objects.
• Export — Download records from Ambivo as a file for use in spreadsheets, reports, or other tools.

Importing is especially useful when you are:

• Migrating from another CRM or business tool
• Uploading leads collected at an event or from a marketing campaign
• Adding a large list of products to your catalog
• Bulk-loading data into a custom object

Getting There

Import

• Open the object you want to import into (e.g., Leads, Contacts) from the left sidebar
• Click the Import action in the list toolbar (or actions menu)
• To review past imports, go to Settings > Import Log

Export

• Navigate to any object list (e.g., Leads, Contacts)
• Look for the Export option in the toolbar

Prepare Your CSV File

Good preparation is the key to a smooth import. A few minutes of cleanup in your spreadsheet can save hours of fixing records afterward.

File Format Requirements

• File must be in .csv (comma-separated values) format
• The first row must contain column headers (e.g., First Name, Last Name, Email, Phone)
• Each subsequent row represents one record
• UTF-8 encoding is recommended to support special characters

Formatting Guidelines

Cleaning Your Data Before Import

• Remove completely blank rows
• Standardize date formats across all rows
• Remove duplicate rows in the spreadsheet
• Trim extra spaces from text fields
• Ensure email addresses are valid
• If your data is in Excel (.xlsx), save it as CSV first

Import Data Step by Step

Step 1: Select Object Type

1. 1

   Open import wizard

   Go to Settings > Objects and click Import (or use the Import action from any object's list view).

2. 2

   Select object type

   Select the Object Type you want to import from the dropdown — standard objects (Leads, Contacts, Accounts, Opportunities, Products) or custom objects you have created. Click Next or Continue.

Step 2: Upload Your File

1. 1

   Upload CSV

   Click Upload File or drag and drop your CSV file. The system reads the file and shows a preview of the columns and first few rows.

2. 2

   Verify preview

   Verify the preview looks correct before proceeding.

Step 3: Map Columns (Field Mapping)

This is the most important step. Field mapping is the process of telling Ambivo which column in your CSV file corresponds to which field in the system. Your spreadsheet columns may have different names than Ambivo's fields — mapping bridges that gap.

Your CSV might have a column called "Company" but Ambivo stores that data in a field called Employer Name. Field mapping lets you say: "My column called Company should go into the Employer Name field."

• The system auto-matches columns with similar names (e.g., a column called Email automatically maps to the Email field)
• For unmatched columns, use the dropdown menu next to each CSV column to select the correct Ambivo field
• Columns you do not want to import can be set to Skip or left unmapped — they will be ignored
• Pay special attention to Owner, Status, Email (required for leads, contacts, and accounts), and required fields

Mapping Tips

• Column names do not need to match exactly — map them to the right Ambivo field
• One CSV column maps to one Ambivo field. You cannot map two CSV columns to the same field
• Unmapped columns are not imported. Your original CSV file is not changed
• Phone and email fields accept various formats
• Address fields — separate street, city, state, and zip columns can be mapped to address subfields
• Date fields — use YYYY-MM-DD format for best results

Step 4: Map Values (Status and Stage)

This step appears only when your CSV has a column mapped to a status or stage field. It lets you translate the values in your file to the values Ambivo expects.

Your CSV might call a lead's status "Available", "Tried Calling", or "Reached Out" — but Ambivo's lead statuses are "open", "attempted", "contacted", "additional contact", and "disqualified". Without value mapping, rows that have an unrecognized status would be rejected.

• The wizard pulls canonical values for the object you are importing
• For each distinct source value, the wizard auto-matches obvious ones (case-insensitive, near-matches)
• For everything else, pick the right canonical value from the dropdown
• Keep original — send the value unchanged (use only when the source value is already canonical)
• Skip these rows — drop every row that has this value
• Click Next when every source value has a destination

Right before submitting, the wizard rewrites each cell in the status/stage column using your mapping — Ambivo only ever sees canonical values. Your original CSV file is not changed.

Step 5: Review and Start

1. 1

   Review mapping

   Review the mapping summary — it shows each CSV column and its mapped Ambivo field. Check the total row count.

2. 2

   Start import

   Click Start Import.

What Happens Next

The import runs in the background. For small files (under a few hundred records), it completes in seconds. Larger files with thousands of records are processed in batches and may take several minutes. You can continue using Ambivo while the import runs.

Review Import Results

1. 1

   Open import log

   Go to Settings > Import Log and find your import in the list.

2. 2

   Review details

   Click on it to see Total Records, Imported Successfully, Failed (with reasons), and Duplicates.

Understanding Failed Records

Re-importing Failed Records

• Download or note the failed rows from the import log
• Fix the issues in your CSV
• Create a new CSV with only the corrected rows
• Run a new import with this file

Export Data

1. 1

   Navigate and filter

   Navigate to the object list you want to export (e.g., Contacts, Leads, Accounts). Optionally, apply filters to narrow down the records.

2. 2

   Download

   Click the Export button in the toolbar, choose the export format (typically CSV), and click Download.

What Gets Exported

• All visible fields for the selected records are included
• If filters are applied, only the filtered records are exported
• Hidden columns are not included — make sure the columns you need are visible in your list view before exporting

Common Export Scenarios

Import for Different Object Types

Importing Leads

Importing Contacts

Importing Accounts

• Account Name (required)
• Industry, Website, Phone (optional but recommended)

Importing Products

• Product Name (required)
• Price (required)
• Description, SKU, Category (optional)

Importing Opportunities, Orders, and Invoices with Multiple Line Items

A single opportunity (deal), order, or invoice often has more than one product on it — these are called line items. How you import them depends on how your CSV file is laid out.

Two Ways Your File Can Be Laid Out

• Layout A — one row per deal. Each row is a complete deal. Import it normally — one row becomes one opportunity.
• Layout B — one row per line item. Each product sits on its own row, and the deal's information is repeated on every row. Turn on line-item grouping during import to merge rows into one multi-line deal.

Turning On Line-Item Grouping

When importing Opportunities, Orders, or Invoices, the import wizard offers a line-item grouping option. When you enable it, you also pick a grouping column — the column whose value is the same for every row that belongs to the same deal. Use a stable ID column whenever possible (for example, HubSpot's Record ID).

Example CSV (one row per line item): Deal ID, Deal Name, Customer, Company, Deal Amount, Product, Line Price — with rows for Acme Rollout (3 products) and Globex Upgrade (2 products). With line-item grouping on and Deal ID as the grouping column, a 5-row file imports as 2 opportunities.

Mapping the Columns

• Deal-level columns are read from the first row of each group
• Line-level columns are read from every row — one product line per row
• Map the deal's total to Value of Sale so the imported deal carries a dollar amount
• The Product column can hold a product name or SKU — the product must exist and be active
• Customer and Company can be names — Ambivo looks up the matching contact and account

Migrating Deals From HubSpot

• Just the deals? Export the Deals object (one row per deal) and import it normally — no grouping needed. Add a contact column so deals link to people.
• Deals with itemized products? Export the Line Items object with the associated-deal columns added. Import with line-item grouping turned on, grouped by the deal's Record ID.

Things to Keep in Mind

• A blank grouping value — that row becomes its own single-line deal
• One product per row — a deal with five products needs five rows
• Single-row deals still work — one row imports as a normal one-product deal
• Test first — try a small file (one or two deals) before importing a large batch
• Rows for one deal do not need to be next to each other in the file

Common Questions

Tips and Best Practices

• Always test with a small batch (10-20 records) before running a full import — this catches mapping errors early
• Use consistent date formats across your entire CSV (YYYY-MM-DD is safest)
• Map the Owner field if you want imported records to be assigned to specific team members automatically
• Check the Import Log after every import — even if most records succeed, a few failures can go unnoticed
• Spot-check imported records — open 5-10 random records to verify the data looks correct in the UI
• Export your data periodically as a backup or for offline analysis in a spreadsheet
• Clean your CSV data before import — it is much easier to fix issues in a spreadsheet than to correct hundreds of records inside Ambivo
• Save your CSV mapping — if you import the same type of data regularly, keep a template CSV with the correct column headers
• Don't rename status values in your spreadsheet — use the Map values step in the import wizard instead

Related Guides

• CRM-001 — Leads Management
• CRM-002 — Contacts Management
• CRM-019 — Custom Objects and Settings
• CRM-003 — Accounts Management
• CRM-009 — Products and Commissions
• CRM-004 — Opportunities and Pipeline
• CRM-008 — Orders and Invoices