Split text into different properties

Use Edit > Split Property to turn one text column into several properties. For example, split name@company.com at @ into name and company.com. You can split selected items, a filtered view, or the full collection. Preview the destination properties before running the split.

This is useful when cleaning scraped data or preparing columns for an enrichment.

Splitting text into properties is perfect to:

• Split full names into First Name and Last Name
• Split email addresses into name and domain
• Split multi values property into single-value properties

Step 1: Open the Split Property tool

Open the "Split Property" tool in the "Edit" menu.

The tool selects the items to process in this order:

• If you have selected items in your collection, it will process them
• If you have a filter or a full-text search term, it will process the filtered items
• Otherwise, it will process all your collection items

And select the property you want to split. Only text-based properties are available. Checkbox, Datetime, etc. properties are not available.

Step 2: Split Property options

Delimiters

Then, select one or more delimiters to use. Common delimiters are available:

• @ (at)
• Comma
• Semicolon
• Dot
• Tab
• Space

You can also enter a custom delimiter. Add multiple delimiters when the same column mixes separators, such as commas and semicolons. Each custom delimiter is treated as a complete string, not as separate characters.

Notes
💡 Example: Add both , and ; to split Finance, Technology; Retail in one run. Leave Trim spaces enabled to remove spaces around the resulting terms.

One term per property

By clicking on the "More settings" link, you get an option to group splitted terms in distinct properties.

With this option, Datablist analyses all the distinct terms that need to be generated from the split process. Then, for each item, split terms are moved to their matching new property.

For example, with this initial data:

#id         #industries
0001        finance, technology
0002        technology, construction
0003        construction, education

And a split process using the "," delimiter. With the "One term per property" option enabled, the result will be:

#id         #finance     #technology    #construction      #education
0001        finance      technology
0002                     technology     construction
0003                                    construction       education

Step 3: Data Analysis

After configuring the settings, Datablist analyzes your data to know how many properties need to be created.

Warning
⚠️ The analysis inspects up to the first 4,000 items in the selected scope. If later items contain more terms than the sample, the generated properties may not cover every term. Check the analysis and preview, or split a more representative subset first.

Step 4: Preview and run

Like many cleaning and editing tools in Datablist, a preview step is shown before running the algorithm.

The preview screen shows a sample of the splitting algorithm on your first items.

For each result, map it to an existing property or create a new property. Check whether the source values need to remain available, then click Split Property to process the selected scope.

Examples

Split Full Names into First Name and Last Name

Some CRMs use Full Name, while others split it into First Name and Last Name. The result is a headache to consolidate your lead lists.

With Datablist Split Text, you can split Full Name on a space and map the two results to First Name and Last Name. Inspect names with middle names or compound surnames in the preview: a simple space delimiter cannot reliably identify name parts.

Split email addresses into name and domain

You can learn a lot on your leads with their email addresses. The email domain is a good example. Does it belong to a corporate website, an email provider, or a disposable email service? To clean your email list, getting the domain address is the first step.

Run the Split Text algorithm on your Email property with the @ delimiter.

Split multi values property into single-value properties

The Datablist tool to merge duplicate items merges conflicting data by combining texts into a single property.

Datablist Split Property algorithm is complementary to Datablist Duplicates Finder. To force a single value in a property (for email addresses, website URLs, etc.), run the algorithm with the same delimiter.

Split text into distinct properties

Use the "One term per property" to create a property for each distinct split value. This feature is useful for segmentation and data cleaning or data matching.