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Einstein Discovery Writeback
Get real-time predictions with your transactional data
- Business Need
- Admin & Developer Tools
READ BEFORE INSTALLING. Einstein Discovery is best used out of the box. We encourage you to use native, no code write-back functionality. Use this managed package only if the native write-back functionality does not meet your business needs.
Compatibility
- Salesforce Editions
- EnterpriseUnlimitedDeveloper
App Details
- Version
- Einstein Discovery Prediction/Summer '20 1.20.0
- Listed On
- 09/21/2018
- Latest Release
- 01/09/2023
- Supported FeaturesNative AppBuilt exclusively on the Salesforce Platform, ensuring reliability and performance.No LimitsThis product's apps, tabs, and objects don't count against your Salesforce org limits. Learn More in HelpLightning ReadyOptimized for Salesforce orgs that use Lightning Ready.Managed PackageThis product is installed in your Salesforce org as a managed package and receives automatic upgrades.
- Native AppNo LimitsLightning ReadyManaged Package
- Package ContentsIf this app is a managed package, the custom apps, tabs, and objects that it contains don't count against your Salesforce allocations. If this app is not a managed package, allocations apply. Learn More in Help
- Custom Objects: 4Custom Tabs: 0Custom Apps: 0
- Lightning Components
- Global: 1App Builder: 1Community Builder: 0
- Languages
- English
Security
Additional Details
READ BEFORE INSTALLING. Einstein Discovery is best used out of the box. We encourage you to use native, no code write-back functionality. Use this managed package only if the native write-back functionality does not meet your business needs. A story includes what happened, why it happened, predictions and recommendations for a given outcome variable. A model is the portion of a story that includes: explanations (why it happened) predictions (what could happen) recommendations (what to do to improve a predicted outcome) Every story includes a desired goal to maximize or minimize the outcome. For example, if you want to predict time to close on an opportunity, you can have separate models for small and large opportunities. You can use this approach if the behavior of your opportunities changes depending on their size. You could create a model on your large opportunities dataset and deploy that to Salesforce. Then you could create a model on your small opportunities dataset and append your small model to the same prediction and recommendation settings. In this context, the model is the segment.
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