Use of predictive analytics in B2B sales lead generation
Lindberg, Anna-Maria (2018)
Lindberg, Anna-Maria
Haaga-Helia ammattikorkeakoulu
2018
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018112718575
https://urn.fi/URN:NBN:fi:amk-2018112718575
Tiivistelmä
The aim of this study is to investigate the possibilities of using predictive analytics as a part of the B2B lead generation in the case company Fonecta. The target is to examine how predictive analytics is used in the current lead process as well as identify areas of improvement and new possibilities of using predictive analytics.
The theoretical framework of this study describes the two main domains related to this study: B2B lead generation and predictive analytics. The theoretical framework covers in more detail the different areas of predictive analytics, including the related machine learning algorithms as well as specific applications of predictive analytics in marketing.
The current lead generation process and the use of predictive analytics in the process was examined based on documentation review and workshops with the stakeholders.
Pilot cases for testing new ways of using predictive analytics in the lead process were selected based on discussions in the workshops that were held for the stakeholders. The pilot cases were run for a two month period after which the results were analyzed and validation of the selected predictive model was carried out. No statistically significant results on the pilot cases were achieved during the pilot period.
Main suggestions for future includes extending the selected pilots cases for a longer period in order to gain significant results as well as the utilization of behavioural data as a part of the predictive model.
The theoretical framework of this study describes the two main domains related to this study: B2B lead generation and predictive analytics. The theoretical framework covers in more detail the different areas of predictive analytics, including the related machine learning algorithms as well as specific applications of predictive analytics in marketing.
The current lead generation process and the use of predictive analytics in the process was examined based on documentation review and workshops with the stakeholders.
Pilot cases for testing new ways of using predictive analytics in the lead process were selected based on discussions in the workshops that were held for the stakeholders. The pilot cases were run for a two month period after which the results were analyzed and validation of the selected predictive model was carried out. No statistically significant results on the pilot cases were achieved during the pilot period.
Main suggestions for future includes extending the selected pilots cases for a longer period in order to gain significant results as well as the utilization of behavioural data as a part of the predictive model.