How Enhanced Data Availability Affects Multi-Channel Marketing Attribution
Individuals can engage with businesses via various marketing channels throughout the sales journey. At Boston Scientific, members of the sales and marketing teams use many applications to develop strategies for and analyze the results of these channels. However, data is not always entered in these a...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/146653 |
| _version_ | 1826202030476099584 |
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| author | Facen, Taylor |
| author2 | Daniel, Luca |
| author_facet | Daniel, Luca Facen, Taylor |
| author_sort | Facen, Taylor |
| collection | MIT |
| description | Individuals can engage with businesses via various marketing channels throughout the sales journey. At Boston Scientific, members of the sales and marketing teams use many applications to develop strategies for and analyze the results of these channels. However, data is not always entered in these applications as cleanly as possible and work to integrate the data from these tools is not always prioritized. In order to support prioritization efforts, management would need an example case study to prove how improvements to data availability could positively affect the type of analysis that could be created and used throughout the organization.
There is no shortage of literature that defines, designs, and advocates for effective data architecture. There are also studies that dive into detail about all of the various types of marketing analyses one can do with channel metrics. Here, this project sets out to combine components from both areas to demonstrate the effects of making data pipeline improvements on downstream projects. First, it describes how a new connector was built to sync Zoom webinar data to the organization’s data warehouse. Then it uses the newly produced dataset to compare and contrast insights created with and without the data. More specifically, this project used both heuristic and stochastic multi-channel marketing attribution models to showcase the types of in- sights that can be drawn with access to more channel activity data. The final result is a feedback loop where one can begin to understand how this type of analysis can help managers advocate for resources within their organization for data architecture improvements. |
| first_indexed | 2024-09-23T12:01:06Z |
| format | Thesis |
| id | mit-1721.1/146653 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T12:01:06Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1466532022-12-01T03:26:23Z How Enhanced Data Availability Affects Multi-Channel Marketing Attribution Facen, Taylor Daniel, Luca Levi, Retsef Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Sloan School of Management Individuals can engage with businesses via various marketing channels throughout the sales journey. At Boston Scientific, members of the sales and marketing teams use many applications to develop strategies for and analyze the results of these channels. However, data is not always entered in these applications as cleanly as possible and work to integrate the data from these tools is not always prioritized. In order to support prioritization efforts, management would need an example case study to prove how improvements to data availability could positively affect the type of analysis that could be created and used throughout the organization. There is no shortage of literature that defines, designs, and advocates for effective data architecture. There are also studies that dive into detail about all of the various types of marketing analyses one can do with channel metrics. Here, this project sets out to combine components from both areas to demonstrate the effects of making data pipeline improvements on downstream projects. First, it describes how a new connector was built to sync Zoom webinar data to the organization’s data warehouse. Then it uses the newly produced dataset to compare and contrast insights created with and without the data. More specifically, this project used both heuristic and stochastic multi-channel marketing attribution models to showcase the types of in- sights that can be drawn with access to more channel activity data. The final result is a feedback loop where one can begin to understand how this type of analysis can help managers advocate for resources within their organization for data architecture improvements. S.M. M.B.A. 2022-11-30T19:39:13Z 2022-11-30T19:39:13Z 2022-05 2022-08-25T19:15:22.989Z Thesis https://hdl.handle.net/1721.1/146653 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Facen, Taylor How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title | How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title_full | How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title_fullStr | How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title_full_unstemmed | How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title_short | How Enhanced Data Availability Affects Multi-Channel Marketing Attribution |
| title_sort | how enhanced data availability affects multi channel marketing attribution |
| url | https://hdl.handle.net/1721.1/146653 |
| work_keys_str_mv | AT facentaylor howenhanceddataavailabilityaffectsmultichannelmarketingattribution |