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The Innovation Forge: Engagement Scoring and Predictive Modeling in the Slate CRM
Paperback
Series: The Innovation Forge, Book 1
Publisher: Independently Published
Published: Nov 13 2024
Pages: 276
Weight: 0.82
Height: 0.58 Width: 6.00 Depth: 9.00
Language: English
Institutions are increasingly turning to data-driven strategies to enhance recruitment, enrollment, and student success. The Innovation Forge is a comprehensive and practical guide that empowers admissions professionals, enrollment managers, and data enthusiasts to leverage Engagement Scoring, Predictive Modeling, and Adaptive Enrollment Management for decision-making and crafting artisanal student experiences.
Act I: Engagement Scoring
Our journey begins with engagement scoring. We lay the foundation explaining how CRM systems can be utilized to track and quantify student interactions. You'll learn about the development of scoring rubrics and the importance of selecting meaningful behaviors.
Balancing data analytics with staff expertise, we emphasize involving your team in developing and implementing engagement scoring systems. We also provide a Slate architecture for this collaboration and aligning institutional outcomes.
The act ends by including practical aspects of leveraging Excel for scoring and validation, incorporating bonuses. Through detailed instructions and examples, you'll learn how to import and prepare data, assign point values, aggregate scores, validate your models, and automate in Slate.
Act II: Predictive Modeling
The 2nd act shifts into the intricacies of predictive modeling. Through building predictive models, we cover key concepts such as model development, training data, and feature engineering.
Key to this act is the implementation and automation of predictive models in Slate, empowering you to keep updated results at your fingertips and integrated in your process.
We also cover Configurable Joins, Source Formats, and Reports extensively, including specific examples and how to build these tools in your instance of Slate. Even beyond scoring and modeling, these tools can push Slate in powerful ways for other projects.
Act III: Adaptive Enrollment Management
The final act introduces advanced strategies for Adaptive Enrollment Management. Between TARGET projections and CRAFTing your class, you can make informed, strategic decisions, meet institutional goals, and manage your funnel.
By using BEACON Data Mining, you develop an investigative data analytics framework that empowers your scoring and modeling as well as elevates your understanding of your students. This unlocks the ability to craft artisanal student experiences and elevate the relationship your students.
Moving from predictive modeling to prescriptive modeling, NUDGE dissects your model to understand how anticipated behaviors, strategic nudges, and financial aid optimization from the institution not only affects an individual student's likelihood to apply and enroll but how it affects the size of your incoming class, NTR, and remaining aid. With the model coded into Slate or Excel, these updates are live and only seconds away.
Paired with the GPS framework for resource allocation, you can now prioritize high-cost and high-touch recruitment strategies to optimize funnel conversion, reducing the need for more names entering your system.
To further improve recruitment, SCOUT practices, especially when implemented with Reports and Voyager offers practical advice on recruitment travel, feeder schools, and using a broad spectrum of data to inform recruitment strategies.
Taken in tandem with THRIVE programming, we highlight initiatives that support student success based on a foundation of data and student understanding. We close with a look ahead to future directions and innovations, especially at the rise of the EnrollMentor - the ability for analytics and generative AI to help guide you into the new era of higher education.
Note: eBook and Paperbook versions include AI-generated images unrelated to the content. These images are excluded from the Hardcover for a more streamlined experience.Also from
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