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Discovering and Inducing Rules to Categorize Sales Personnel

Stenström, Lisa LU and Wahlgren, Olof LU (2016) In 1650-2884 EDA920 20152
Department of Computer Science
Abstract
In sales, it is presumed that the behavior of sales personnel differs depending on what part of sales they are in. However, to the best of our knowledge, there are no studies about conducting a segmentation of sales personnel based on behavioral data from Salesforce, the world’s largest Customer Relationship Management platform. Previous research describes how to segment different customers based on their behavioral data, but no one has yet attempted to segment sales personnel.

In this thesis, we extracted Salesforce behavioral data about sales staff and clustered them into previously unknown segments. Using a mixture of supervised and unsupervised learning we created six profiles that describe how different sales personnel work in... (More)
In sales, it is presumed that the behavior of sales personnel differs depending on what part of sales they are in. However, to the best of our knowledge, there are no studies about conducting a segmentation of sales personnel based on behavioral data from Salesforce, the world’s largest Customer Relationship Management platform. Previous research describes how to segment different customers based on their behavioral data, but no one has yet attempted to segment sales personnel.

In this thesis, we extracted Salesforce behavioral data about sales staff and clustered them into previously unknown segments. Using a mixture of supervised and unsupervised learning we created six profiles that describe how different sales personnel work in Salesforce. Our findings helped the company Brisk to improve their knowledge about sales personnel. (Less)
Popular Abstract (Swedish)
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Please use this url to cite or link to this publication:
author
Stenström, Lisa LU and Wahlgren, Olof LU
supervisor
organization
course
EDA920 20152
year
type
H3 - Professional qualifications (4 Years - )
subject
keywords
sales, categorization, machine learning, data mining, crm, segmentation
publication/series
1650-2884
report number
LU-CS-EX 2016-04
ISSN
1650-2884
language
English
id
8726563
date added to LUP
2016-02-19 08:46:36
date last changed
2016-02-19 08:46:36
@misc{8726563,
  abstract     = {In sales, it is presumed that the behavior of sales personnel differs depending on what part of sales they are in. However, to the best of our knowledge, there are no studies about conducting a segmentation of sales personnel based on behavioral data from Salesforce, the world’s largest Customer Relationship Management platform. Previous research describes how to segment different customers based on their behavioral data, but no one has yet attempted to segment sales personnel. 

In this thesis, we extracted Salesforce behavioral data about sales staff and clustered them into previously unknown segments. Using a mixture of supervised and unsupervised learning we created six profiles that describe how different sales personnel work in Salesforce. Our findings helped the company Brisk to improve their knowledge about sales personnel.},
  author       = {Stenström, Lisa and Wahlgren, Olof},
  issn         = {1650-2884},
  keyword      = {sales,categorization,machine learning,data mining,crm,segmentation},
  language     = {eng},
  note         = {Student Paper},
  series       = {1650-2884},
  title        = {Discovering and Inducing Rules to Categorize Sales Personnel},
  year         = {2016},
}