---
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title: Numerical Use Cases
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/analytics/264-0-0/bi_edd_about_use_case_numeric.md
canonical_url: https://help.salesforce.com/s/articleView?id=analytics.bi_edd_about_use_case_numeric.htm&release=264.0.0&type=5
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content_type: documentation
content_hash: 6be76d5cee7d4cb88710f8bd272ae83d2c2e1282798fe7f306df47bce78abd47
description: Numerical solutions target numeric outcomes represented as quantitative data (measures), such as currency, counts, or percentages.
products:
  - CRM Analytics
  - Cross Cloud
release: "264"
---
# Numerical Use Cases

Numerical solutions target numeric outcomes represented as quantitative data (measures), such as currency, counts, or percentages.

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_note.png)

Note Einstein Discovery stories are now models. We wish we could snap our fingers to update the name everywhere, but you can expect to see the previous name in a few places until we replace it.

## Example Numerical Solutions

Here are just a few examples of how Einstein Discovery can help you improve numerical outcomes in your organization:

- Predicted Amount of an opportunity
- Predicted Time-to-Close of an opportunity
- Predicted Customer Lifetime Value of an account
- Predicted Customer Satisfaction of a case

## Model Templates

- [Maximize Customer Revenue Model Template](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_template_maximize_customer_revenue.htm&release=264.0.0&type=5 "Analyze which types of accounts are leading to higher sales based on the last 365 days. Use a linear regression model to predict which accounts could bring additional revenue.")
- [Minimize Time to Close Model Template](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_template_minimize_time_to_close.htm&release=264.0.0&type=5 "Understand the key factors that drive shorter deal cycles without having to worry about where to begin.")

## Supported Algorithms for Numerical Solutions

- Generalized Linear Model (GLM) - Linear Regression
- XGBoost
- Gradient Boost Machine (GBM)
- Random Forest

## Model Quality Metrics

[Metrics for Numeric Use Cases](https://help.salesforce.com/s/articleView?id=analytics.bi_edd_model_metrics_measure.htm&release=264.0.0&type=5 "The numeric use case is based on outcomes that are numeric variables. Model Performance shows quality statistics associated with linear regression models.")

#### See Also

- [_Trailhead_: Einstein Discovery Analysis and Insights](https://trailhead.salesforce.com/en/content/learn/modules/einstein-discovery-analysis-and-insights)