Title

Session 8: Financial - Using Attribution Modeling to Find Profitable Lending Customers

Presenter Information/ Coauthors Information

Nirav Bhagat, Metafunding

Presentation Type

Event

Abstract

A career in marketing data science will entail answering questions about how best to allocate spend within a marketing portfolio. As marketing budgets continue to shift towards online channels and away from print, the availability and quantity of campaign data make the data scientist’s job more challenging than ever. Within financial services (and credit card issuers), a strategy that optimizes the mix of paid direct mail, paid online, organic search and on-site optimization has historically led to more efficient marketing costs. That strategy can been derived through attribution modeling, a close cousin to marketing mix models. In this presentation, Nirav will present examples of the conversion path of customers over paid, earned and owned marketing channels. He’ll introduce the data engineering and analytics tools used to give credit to each channel for conversions. And, he’ll introduce a few areas where science and tools are nascent.

Start Date

12-2-2018 2:00 PM

End Date

12-2-2018 3:00 PM

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Feb 12th, 2:00 PM Feb 12th, 3:00 PM

Session 8: Financial - Using Attribution Modeling to Find Profitable Lending Customers

University Student Union: Pasque Room 255

A career in marketing data science will entail answering questions about how best to allocate spend within a marketing portfolio. As marketing budgets continue to shift towards online channels and away from print, the availability and quantity of campaign data make the data scientist’s job more challenging than ever. Within financial services (and credit card issuers), a strategy that optimizes the mix of paid direct mail, paid online, organic search and on-site optimization has historically led to more efficient marketing costs. That strategy can been derived through attribution modeling, a close cousin to marketing mix models. In this presentation, Nirav will present examples of the conversion path of customers over paid, earned and owned marketing channels. He’ll introduce the data engineering and analytics tools used to give credit to each channel for conversions. And, he’ll introduce a few areas where science and tools are nascent.