Welcome to Oracle AI Apps for Sales

Oracle AI Apps combines decision science and machine learning to help your salespeople increase and accelerate sales. When salespeople work on leads, they see AI Apps 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 Oracle AI Apps for Sales to:

Predict lead scores
Predict opportunity win probability
Recommend actions for opportunities

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

Predictive Lead Score

The AI Apps models predict scores for leads based on your organization’s lead history, activities, and relevant data. Your salespeople can view the AI Apps 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 AI Apps 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.