PAW Business Expert Round 2: AI for Marketing & E-Commerce


Thursday, June 17, 2021


10:20 am


  1. Lessons Learned: Building a Keyword Extraction Service for Bibliographic Metadata (Daniel Wrigley)

    The right keywords drive revenue: They ensure better visibility, optimised findability and higher rankings of publications. But curating metadata is a tedious process and outsourcing is expensive. This was the motivation to build a service to automatically extract keywords from metadata. Finding the right toolset in order to find the right keywords was a huge challenge. I want to share what we learned in the areas of NLP (e.g. lemmatization, ML on unstructured data) and ETL.

  2. Data-driven Personas – Understand Your Customers’ Behavior (Alwin Haensel & Paul Kleinschmidt)

    Marketing is all about understanding customer behavior and anticipation of their responses and engagement. Classical marketing relies on general knowledge and a lot of gut feeling. But data can tell us who our customers are and how they react to campaigns and interact with offers over time. We propose an approach for customer segmentation based on temporal behavior clusters. This provides a customer interaction understanding, which enables marketeers to optimal target & time marketing campaigns.

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