Semantically-Enabled Optimization of Digital Marketing Campaigns

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11779)


Digital marketing is a domain where data analytics are a key factor to gaining competitive advantage and return of investment for companies running and monetizing digital marketing campaigns on, e.g., search engines and social media. In this paper, we propose an end-to-end approach to enrich marketing campaigns performance data with third-party event data (e.g., weather events data) and to analyze the enriched data in order to predict the effect of such events on campaigns’ performance, with the final goal of enabling advanced optimization of the impact of digital marketing campaigns. The use of semantic technologies is central to the proposed approach: event data are made available in a format more amenable to enrichment and analytics, and the actual data enrichment technique is based on semantic data reconciliation. The enriched data are represented as Linked Data and managed in a NoSQL database to enable processing of large amounts of data. We report on the development of a pilot to build a weather-aware digital marketing campaign scheduler for JOT Internet Media—a world leading company in the digital marketing domain that has amassed a huge amount of data on campaigns performance over the years—which predicts the best date and region to launch a marketing campaign within a seven-day timespan. Additionally, we discuss benefits and limitations of applying semantic technologies to deliver better optimization strategies and competitive advantage.


Semantic enrichment Big data analytics Digital marketing Data linking Data reconciliation 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of Milan-BicoccaMilanoItaly
  2. 2.JSILjubljanaSlovenia
  3. 3.SINTEF ASOsloNorway
  4. 4.JOT Internet MediaMadridSpain

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