USING SUPERVISED MACHINE LEARNING FOR LEAD QUALIFICATION IN STARTUPS - A STUDY ON B2B SALES IN FINTECH - Work Project for Master’s Degree in Business Analytics

Aug 5, 2026

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Work project for a Master’s degree in Business Analytics at Nova School of Business and Economics, examining how supervised machine learning can improve lead qualification for startups operating in fintech. The study focuses on B2B sales processes, defines lead qualification challenges, and proposes a modeling pipeline from data acquisition and cleaning to feature selection and preprocessing. Multiple models are tested with hyperparameter tuning, performance evaluation, and interpretation, followed by results discussion including comparisons to literature, managerial implications, limitations, and directions for future research.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages48

Reading Time2 h 1 min

AccessFree to download

1. Introduction

2. Background

2.1 B2B sales processes

2.2 Lead qualification and its challenges

2.3 Machine learning in lead generation and qualification

3. Methodology

3.1 Research context

3.2 Data acquisition

3.3 Data cleaning and preprocessing

3.4 Model building

4. Results

4.1 Classification model

4.2 Proof of concept

4.3 Model interpretation

5. Discussion

5.1 Comparison to existing literature

5.2 Managerial implications

5.3 Limitations and future research

6. Conclusion

BIBLIOGRAPHY

APPENDIX

A Work Project, presented as part of the requirements for the Award of a Master's degree in Business Analytics from the Nova School of Business and Economics. “USING SUPERVISED MACHINE LEARNING FOR LEAD QUALIFICATION IN STARTUPS: A STUDY ON B2B SALES IN FINTECH” SEBASTIAN SIMMEL Work project carried out under the supervision of: Prof. Leid Zejnilovic TABLE OF CONTENTS 1. Introduction ...................................................................................................................... 2 2. Background....................................................................................................................... 3 2.1 B2B sales processes ......................................................................................................... 3 2.2 Lead qualification and its challenges ............................................................................... 5 2.3 Machine learning in lead generation and qualification .................................................... 7 3. Methodology ..................................................................................................................... 8 3.1 Research context .............................................................................................................. 8 3.2 Data acquisition ................................................................................................................ 9 3.3 Data cleaning and preprocessing .................................................................................... 10 3.3.1 Relevant feature selection ....................................................................................... 10 3.3.2 Handling of missing values ..................................................................................... 11 3.3.3 Keyword extraction ................................................................................................. 12 3.3.4 Data preprocessing .................................................................................................. 12 3.3.5 Dealing with an imbalanced dataset ........................................................................ 13 3.4 Model building ............................................................................................................... 13 3.4.1 Models tested........................................................................................................... 13 3.4.2 Feature selection...................................................................................................... 14 3.4.3 Hyperparameter tuning ............................................................................................ 15 3.4.4 Model testing and performance evaluation ............................................................. 15 4. Results ............................................................................................................................. 16 4.1 Classification model ....................................................................................................... 16 4.2 Proof of concept ............................................................................................................. 17 4.3 Model interpretation ....................................................................................................... 19 5. Discussion........................................................................................................................ 20 5.1 Comparison to existing literature ................................................................................... 21 5.2 Managerial implications ................................................................................................. 22 5.3 Limitations and future research ...................................................................................... 23 6. Conclusion................................................................................

FAQs

What problem does the study address in B2B fintech startups?

The study targets lead qualification challenges within B2B sales, aiming to improve how leads are assessed and prioritized for qualification using supervised machine learning.

How is the dataset prepared before modeling?

Methodology includes data acquisition, data cleaning and preprocessing, relevant feature selection, handling missing values, keyword extraction, and dealing with an imbalanced dataset.

What modeling and evaluation steps are used to obtain results?

The approach builds classification models, tests multiple model types, performs feature selection and hyperparameter tuning, and evaluates model performance. Results also include proof of concept and model interpretation.

Aug 5, 2026

Upload by Aria