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Lambert, Marina (2018) Sales Forecasting: Machine Learning Solution to B2B Sales Opportunity Win-Propensity Computation. Masters thesis, Dublin, National College of Ireland.
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Abstract
This research is focused on finding an optimal machine learning solution for computation of a sales win-propensity score for B2B software sales. Currently sales propensity scoring at opportunity level is a manual, time-consuming and subjective task carried out by a salesperson. Customised model stack involving Random Forests, GLM, boosting, trees, and neural networks is a proposed solution in this research. Unlike reviewed related works, research focused on developing an approach using open-source tools and commonly met sales variables, hence proposed solution can be lifted and re-purposed cross-industry. Integration of provided solution into CRM will allow for accuracy improvement in sales forecasting, result in better planning, more effective resource management, saving time and costs.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Caoimhe Ní Mhaicín |
| Date Deposited: | 06 Nov 2018 11:01 |
| Last Modified: | 06 Nov 2018 11:01 |
| URI: | https://norma.ncirl.ie/id/eprint/3437 |
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