Discover how Oracle transformed lead management using machine learning and automated lead routing in this 43-minute video. Learn about the inbound demand generation process, project goals, implementation challenges, and operational hurdles faced. Explore the machine learning score, capacity pilot, and resulting 2X improvement in lead opportunity conversion. Gain insights into roles, responsibilities, and the customer journey model. Understand account-level insights, timeline, and tools used in the process. Delve into the development of live models, automated quota systems, and account scoring techniques. Address common questions about human rules, competitive product considerations, and industry-specific prepackaged rules. Connect with Oracle's resources for cloud services, events, support, and community engagement.
Transforming Lead Management with Machine Learning at Oracle
Overview
Syllabus
Introduction
Oracle inbound demand generation process
The goal of the project
The challenge
The implementation
Operational challenges
Machine learning score
Capacity pilot
Results
Roles responsibilities
Customer journey
Customer journey model output
Account level insights
Questions
Early adopter program
How long does it take
Timeline
Customer Journey Model
Time constraint
Lead scoring efficacy
Stack rank
Tools
Live model
How to develop your own model
Questions from the audience
Human rules
Automated quota
Account scoring
Machine learning takes a lot of the heavy lifting
Two more questions
Have we considered the install base of competitive products
Prepackaged basic rules based on industry
Contact information
Taught by
Oracle
