> For the complete documentation index, see [llms.txt](https://developer.kizen.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.kizen.com/docs/concepts/objects/custom-fields/numerical-field-types.md).
# Numerical Field Types
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**Audience**: Administrators, Developers, Solution Architects
**Purpose**: Explain how to use numerical field types to accurately capture quantitative data and select the correct field type when designing space.vars.object schemas.
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## Overview
Numerical field types are structured fields used to capture measurable values such as quantities, financial amounts, percentages, and projections.
These fields power:
* Accurate reporting and aggregation
* Mathematical operations and calculated values
* Forecasting and weighted projections
* space.vars.automation triggers and conditional logic
* API-based integrations and data pipelines
Selecting the correct numerical field type is a foundational schema decision that directly impacts data precision, validation behavior, formatting and display, reporting accuracy, and the reliability of downstream analytics and integrations.
Whenever numeric data will be aggregated, used in calculations, or evaluated by space.vars.automation, selecting the correct field type becomes critical.
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**Warning**: Using the wrong numerical field type can introduce rounding issues, reporting inconsistencies, or unexpected space.vars.automation behavior.
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The sections below explain each numerical field type and when to use it.
***
## Number (Decimal)
The `decimal` field type supports fractional values and is designed for data that requires precision beyond whole numbers.
### Common Use Cases
Use this field when values require fractional precision, such as:
* Percentages (for example, 12.5%)
* Rates (for example, 4.25% interest rate)
* Measurements (for example, 2.75 hours, 10.5 miles)
* Ratios and calculated outputs
* Financial values that are not currency-specific
### Behavior Considerations
Decimal fields support fractional input and are optimized for calculations, aggregations, and threshold-based space.vars.automation. A decimal field:
* Accepts numeric input with decimal points, including negative numbers
* Supports mathematical operations in reporting and space.vars.automations
* Supports fractional values for reporting, calculations, and space.vars.automation logic
* Supports up to 15 total digits, with up to 4 digits displayed after the decimal point
Choose decimal fields if rounding errors may materially affect reporting accuracy, forecasts, or space.vars.automation logic.
If your data requires fractional accuracy, use `decimal` instead of `integer` to prevent truncation or rounding errors.
***
## Number (Integer / Whole)
The `integer` field type captures discrete numeric values that do not require fractional precision. Integer fields require whole-number values when inputted into the UI and API calls.
### Common Use Cases
Use this field when values must remain whole numbers, such as:
* Item counts
* Units in inventory
* Event attendance
* Number of employees
### Behavior Considerations
Integer fields enforce whole-number input, supporting accurate counting, aggregation, and threshold-based space.vars.automation**.** An integer field:
* Restricts values to whole numbers
* Allows negative values
* Supports values from `-2,147,483,647` to `2,147,483,647`. Values are displayed with comma separation
* Prevents fractional input
* Ensures consistent reporting and aggregation
* Supports clear quantitative comparisons
Use integer fields when fractional values would introduce ambiguity or distort reporting. By restricting precision, the `integer` field enforces data consistency and avoids unintended decimal usage.
***
## Money / Currency / Price
The `money` field captures monetary values and provide currency-aware handling to support financial reporting, forecasting, and operational workflows.
### Common Use Cases
Use this field for monetary values such as:
* Revenue tracking
* Deal values
* Pricing
* Budgeting
* Cost analysis
* Commerce-related workflows
### Behavior Considerations
Money fields are currency-aware and formatted according to the business’s configured currency settings. Depending on configuration:
* Values may use a single default currency
* Each Money field instance stores one monetary value in one currency
Currency configuration directly impacts reporting accuracy, forecasting, and financial integrations.
When designing financial schemas, confirm:
* Whether your organization operates in multiple currencies
* How currency conversion should be handled in reporting
* Whether downstream systems expect currency codes
Your currency strategy should be established before implementing financial fields.
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**Note**: Money fields store currency values but do not perform currency conversion.
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### Why Not Use Decimal for Money?
Decimal fields store numeric values without currency context.
Money fields store numeric values with associated currency formatting and display the appropriate currency symbol based on business configuration.
Use Money fields when values represent financial amounts and should be displayed with currency formatting in the application.
***
## % Chance to Close
The **% Chance to Close** field represents the probability that a pipeline space.vars.entity will reach a successful outcome. It is a system field used in weighted pipeline forecasting calculations.
This field is available on pipeline-enabled space.vars.objects and interacts with stage-level probability settings defined in the space.vars.object’s pipeline configuration. The value may be influenced by stage changes or, if enabled, AI-driven predictions.
### **Common Use Cases**
Use this field when managing probability-driven pipeline space.vars.entities, such as:
* Tracking sales opportunities
* Forecasting projected revenue
* Weighting deal values based on probability
The % Chance to Close field is part of the space.vars.object’s workflow and forecasting logic. It should be used only within lifecycle-driven pipeline space.vars.objects where probability impacts forecasting.
***
## Additional Information
Schema Design Best Practices
Before implementing numerical fields:
* Confirm required precision
* Identify reporting and aggregation needs
* Evaluate space.vars.automation triggers using numeric comparisons
* Consider API integrations and downstream systems
* Avoid retroactive schema changes that may affect calculations
Changing numerical field types after implementation can disrupt reporting and integrations. Design intentionally.
***
## What’s Next
Review field-specific documentation before making schema changes to ensure consistent data behavior across space.vars.objects, space.vars.workflows, and integrations. To continue designing your schema, review our related topics.
Related Topics
* [Date Field Types ](/docs/concepts/objects/custom-fields/date-field-types.md)
* [Selection Field Types](/docs/concepts/objects/custom-fields/selection-field-types.md)
* [Text Field Types](/docs/concepts/objects/custom-fields/text-field-types.md)
* [Communication Field Types](/docs/concepts/objects/custom-fields/communication-field-types.md)
* [Special Field Types](/docs/concepts/objects/custom-fields/special-field-types.md)
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