Keep It Crisp: Starting Analytics Success through Constant Focus On the Why

Track: Data Science

Session Number: 2095
Date: Sat, Aug 3rd, 2019
Time: 8:00 AM - 9:00 AM
Room: Grand Sonoran G

Description:

Our two-member prospect development team is responsible for thousands of prospects: how does the team prioritize the crowd? This session looks at a descriptive analytics project using the Recency, Frequency, and Monetary Size score model as the basis for a prospect interaction score to spot the next group of leads to research and promote as identified prospects. Attendees will take away key steps, make-or-break challenges, helpful tools (R, RStudio, tiydverse), and crucial tips that made the project a success.
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 1: The Data Science Umbrella
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 4: Statistical Techniques and Competencies
Intended Audience Level: Level I
Recommended Prerequisites: Excel, Excel formulas, and minimal knowledge/use of the R programming language
Learning Objective #1: Attendees will learn the names and benefits of three specific low to no cost resources that can guide them to successfully complete an analytics project.
Learning Objective #2: Attendees will learn a few common impediments that can end an analytics project, and they will learn how to remove or navigate around those impediments to successfully complete an analytics project.
Shop Size: Small
Session Type: Breakout Session (60min)

Primary Competency: DA:Competency 1: The Data Science Umbrella
Secondary Competency: DA:Competency 3: Data Manipulation Skills
Tertiary Competency: DA:Competency 4: Statistical Techniques and Competencies
Intended Audience Level: Level I
Recommended Prerequisites: Excel, Excel formulas, and minimal knowledge/use of the R programming language
Learning Objective #1: Attendees will learn the names and benefits of three specific low to no cost resources that can guide them to successfully complete an analytics project.
Learning Objective #2: Attendees will learn a few common impediments that can end an analytics project, and they will learn how to remove or navigate around those impediments to successfully complete an analytics project.
Shop Size: Small