How to choose the right field type

Summary

Choosing the right field type in Kombiner ensures your data stays consistent and easy to manage. The correct type helps prevent errors and improves how data is used across the platform. In this article, we explain how to select the right type for your needs.

What does choosing the right type mean?

Each field type is designed for a specific purpose. Choosing the correct one ensures:

• Better data quality
• Easier filtering and usage
• More predictable behavior

Choosing the wrong type can lead to inconsistent or hard-to-use data.

When should I think about field types?

You should consider field types when:

• Creating a new Custom Field
• Importing data from external systems
• Structuring product or company data
• Standardizing data across your organization
• Planning how the data will be used later

How to choose the right field type

The typical decision process:

1. Identify what kind of data you need to store
2. Decide if the data should be structured or flexible
3. Choose the closest matching field type
4. Test the field before using it widely

The goal is to match the field type to the data, not the other way around.

Key guidelines

Use text only when flexibility is needed

Text fields are useful but can lead to inconsistent data.

Use when:

• Values vary widely
• No strict format is required

Use numbers for measurable data

Always use numeric types for values that can be calculated or compared.

Use when:

• You need quantities
• You need measurements

Use single select for standardization

Predefined options keep data consistent.

Use when:

• You want limited choices
• You need consistent reporting

Use boolean for simple states

Best for yes/no logic.

Use when:

• A value is either true or false

Use date for time-based data

Avoid storing dates as text.

Use when:

• You need scheduling or tracking

Use file/image for assets

Best for documents and visuals.

Use when:

• You need attachments
• You want visual references

Best practices for choosing field types

• Think about how the data will be used later
• Avoid mixing different types of data in one field
• Keep fields simple and focused
• Use predefined options when possible
• Test with real data before scaling

Important notes

• Changing field types later is difficult
• Poor type selection can reduce data quality
• Some integrations may rely on specific types
• Different teams should agree on standards
• Data consistency depends on correct type usage

Common questions

What is the most common mistake?

Using text fields for structured data like numbers or dates.

Should I always use single select?

Only when you need controlled and consistent values.

Can I fix a wrong field type later?

Often this requires creating a new field and migrating data.

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