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Introduction
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Oracle inbound demand generation process
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The goal of the project
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The challenge
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The implementation
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Operational challenges
7
Machine learning score
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Capacity pilot
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Results
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Roles responsibilities
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Customer journey
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Customer journey model output
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Account level insights
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Questions
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Early adopter program
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How long does it take
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Timeline
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Customer Journey Model
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Time constraint
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Lead scoring efficacy
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Stack rank
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Tools
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Live model
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How to develop your own model
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Questions from the audience
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Human rules
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Automated quota
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Account scoring
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Machine learning takes a lot of the heavy lifting
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Two more questions
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Have we considered the install base of competitive products
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Prepackaged basic rules based on industry
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Contact information
Description:
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

Oracle
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