1Overview

Welcome to Adaptive Intelligence for Sales

Adaptive intelligence combines decision science and machine learning to help your salespeople increase and accelerate sales. When salespeople work on leads, they see adaptive intelligence predictive lead score that helps them prioritize their leads better. When they view their opportunities, they get recommendations to increase their win rates. Salespeople can use these features to improve their productivity and close deals faster.

This image illustrates the high-level flow of data feeding into adaptive intelligence to:
  • Predict lead scores

  • Predict opportunity win probability

  • Recommend actions for opportunities

A high-level flow chart showing the different aspects of Adaptive Intelligent Sales. Sales data feeds into Adaptive Intelligence for Sales and the models predict lead score, win probability, and recommended actions.

Predictive Lead Score

The adaptive intelligence models predict scores for leads based on your organization’s lead history, activities, and relevant data. Your salespeople can view the adaptive intelligence predictive lead scores and focus on leads that are most likely to convert to opportunities. Let’s look at an example. A salesperson has about 50 marketing qualified leads in her territory. She doesn’t have the time to follow up on each of these leads individually. She sees that about 10 of these leads have predictive lead scores of 80 or more. She immediately knows that these 10 leads are most likely to convert to opportunities and decides to pursue them.

Opportunity Recommended Actions

The adaptive intelligence models estimate win probability for opportunities. If there’s a mismatch between the models’ estimate and the salesperson’s estimate, it alerts the salesperson. The models also estimate opportunity win probabilities for all recommended actions so that salespeople see only those with higher win probability estimates. Your salespeople can use the recommended actions to improve their chances of winning opportunities.

Let’s look at an example. Suppose the role marked as the primary contact on an opportunity correlates with a low win rate in the past. The reason might be that this contact isn't the decision maker in the organization. And so the models recommend that the salesperson checks that the primary contact is the decision maker.

Version Compatibility

Use the application on devices with a width of 768 pixels or higher. For detailed information on Oracle's browser support policy, see System Requirements for Oracle Applications Cloud.

This table lists version compatibility for the supported integrations.

Integrated Application Version Requirement
Oracle CX Sales

Oracle CX Sales Release 13 (update 18B) or later (for opportunity win probability and recommended actions)

Oracle CX Sales Release 20D or later (for predictive lead scores)

Accessibility

You can use assistive technology products, such as screen readers, while you work in the application. You can also use the keyboard instead of the mouse. This table lists the supported accessibility features for Oracle Adaptive Intelligence for Sales.

Feature Description

Zoom

You can use your browser's zoom feature to resize text up to two hundred percent without loss of content or functionality.

Contrast

Large-scale text and images of large-scale text have a contrast ratio of at least 3:1. Other text and images of text have a contrast ratio of at least 4.5:1.

Screen Reader

You can use screen readers. No special mode is required to enable them.

Timing Adjustable

If you experience being timed out of the application, your Oracle Identity Cloud Service administrator can extend the session expiry period.

Roles and User Administration

Roles and privileges control the access that users have to different features of the application. You can manage users in Oracle Identity Cloud Service and assign them to roles, which determine which tasks they can perform.

This table describes the roles that you can assign and the privileges associated with the role.

Role Privileges Description
Oracle Adaptive Intelligent CX User
  • View Home page

  • Review Insights

  • Manage Supervisory Controls

Coordinates and supervises all sales user activities related to Oracle Adaptive Intelligence for Sales. Reviews the insights page to monitor data flow to and from Oracle CX Sales. Sets the opportunity recommended actions threshold using supervisory controls.
Oracle Adaptive Intelligent CX Operations Manager
  • View Home page

  • Manage Connections

  • Review Insights

  • Manage Supervisory Controls

Coordinates and supervises all activities related to the operation of Oracle Adaptive Intelligence for Sales, such as managing data source connections. This role inherits privileges of the User role for sales activities.

You can manage users in Oracle Identity Cloud Service (IDCS) and assign them to specific roles, which determine which tasks they can perform. If you have the appropriate privileges, select the User Administration shortcut on the user menu to go to IDCS, where you can map users to roles.

See Manage Oracle Identity Cloud Service Users for information about user administration.

Privacy Regulations and Data Protection

This topic introduces important aspects related to privacy and data protection.

Some jurisdictions, such as the European Union with its General Data Protection Regulation (GDPR), require special control to maintain privacy of personal information. Oracle Adaptive Intelligence for Sales has capabilities to help you comply with these rules.

For details on privacy and security for Oracle CX Sales, see Privacy and Security Feature Guidance for all Oracle Services (Doc ID 114.2) on My Oracle Support. Navigate to Customer Experience > Engagement – Sales & Service, and open the PDF Oracle Fusion Engagement Cloud (Sales, Service, Customer Data Management, & Loyalty).

Consumer Consent

Adaptive intelligence models use consumer data within Oracle CX Sales to enhance salespeople’s likelihood of closing opportunities. The models use consumers’ profile attributes and their purchase history to make recommendations. For example, the models may recommend that the salesperson provides unique product feature information to a certain consumer before quoting a price.

Ensure that the data you store in Oracle CX Sales and use in machine learning is restricted to consumers who have given explicit consent.

Consumers’ Right to be Forgotten

If consumers remove consent, you must delete their data from Oracle CX Sales. The consumer data is subsequently deleted in Oracle Adaptive Intelligence for Sales during the next ingestion process.