Publicação
Using supervised machine learning for lead qualification in start ups: a study on B2b sales in fintech
| Resumo: | Lead qualification is a fundamental process in every business-to-business sales organization, yet it is often manual, time-consuming, and heavily relies on the human intuition of sales representatives. Especially early-stage startups face difficulties finding new business opportunities due to a lack of resources, sales experience, and data. Model-based decision support systems make this process less subjective and quicker. I apply supervised machine learning techniques to analyze and learn from previously qualified leads. The results show that gradient-boosted decision trees perform best in this context and indicate that the application significantly cuts time spent on qualification while keeping the quality of leads consistent. |
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| Autores principais: | Simmel, Sebastian Jakob |
| Assunto: | Machine learning Sales analytics B2b sales Lead qualification |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Lead qualification is a fundamental process in every business-to-business sales organization, yet it is often manual, time-consuming, and heavily relies on the human intuition of sales representatives. Especially early-stage startups face difficulties finding new business opportunities due to a lack of resources, sales experience, and data. Model-based decision support systems make this process less subjective and quicker. I apply supervised machine learning techniques to analyze and learn from previously qualified leads. The results show that gradient-boosted decision trees perform best in this context and indicate that the application significantly cuts time spent on qualification while keeping the quality of leads consistent. |
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