Data science
Intelligence workbench module allows you create ready-to-use data science models to gain insights from the unified customer data and make informed decisions.
The following data science models are available within Intelligence Workbench.
| Algo/ use case family | Algorithm Name | Model Description | Links | 
|---|---|---|---|
| Audience selection models | 
 | Identifies similar audience for a given seed segment by analyzing profile and behavioral attributes | 
 | 
| Lead/ Account scoring | 
 | Scores Leads/ Accounts (B2B) based on their likelihood to convert based on engagement patterns | |
| Propensity models | 
 | Predicts the likelihood of purchasing/ re-purchasing a product(s) OR customer churning over OR engagement based on transactional, engagement or other patterns. | |
| Campaign/ Channel/ STO recommendations | 
 | Identifies the most effective campaign and/or channel based on past interactions | |
| Next best recommendationmodels | 
 | Identifies the next best Action/ Promotion/ Offer to present to customers based on past interactions. | 
 | 
| CLTV | 
 | Estimates the Customer’s value over a period of time based on profile and transaction patterns. | 
 | 
| RFM/ Fatigue | 
 | RFM models identify personas based on the recency, frequency or monetary value of transactions Fatigue – classifies customers into different levels of fatigue based on profile & engagement | 
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| Attribution | 
 | Measures effectiveness of campaign by measuring touchpoints that drive revenue and conversion | 
 | 
Accessing data science models
To access data science models:
- 
                                                            Click the Oracle icon  in the bottom-right corner to open the navigation menu. in the bottom-right corner to open the navigation menu.
- 
                                                            Select Intelligence workbench. 
The page will display the list of existing models.
Next steps
Get more information about each model and learn how to create and use them.