Maximilian Matthe

Maximilian Matthe

Doctoral Candidate in Marketing

Goethe University Frankfurt

Hi there!

I am a doctoral candidate in Marketing at Goethe University Frankfurt supervised by Bernd Skiera. In Fall 2018 and Spring 2019 I was a visiting doctoral scholar at the Univerity of North Carolina (UNC) at Chapel Hill, USA, invited by my co-supervisor Daniel M. Ringel.

My research studies contemporary marketing problems via the lens of modern data science. In particular, I investigate the relationships among market actors, such as competing firms, consumers with similar behavior, or consumer-brand interactions. I believe that understanding these relationships can provide novel solutions to practical marketing challenges, such as competitive analysis, branding, positioning, or targeting.

A centerpiece of my work is dynamic mapping which I use to investigate positioning dynamics among firms, political parties or media outlets.

I am on the Summer/Fall 2022 academic job market.

  • Competition and Market Structure
  • Strategic Market Analysis
  • Unstructured Data Analysis
  • Mapping
  • Machine Learning
  • Dr. Marketing, 2023 (expected)

    Goethe University Frankfurt (Germany)

  • M.Sc. Money & Finance (Financial Economics), 2017

    Goethe University Frankfurt (Germany)

  • B.Sc. Mathematics and Economics, 2015

    University of Wuerzburg (Germany)


Mapping Market Structure Evolution

Forthcoming in Marketing Science

  • Finalist, 2022 ASA Statistics in Marketing Doctoral Research Award
  • Finalist, 2019 EMAC Best Paper Award based on Doctoral Work
[Show abstract …]

Mapping Market Structure Evolution

Working Papers

Politics in Flux: Dynamic Party Positioning and Voter Support

New version available soon

[Show abstract ...]

Identifying Consumers’ Information Needs in Online Search

Job Market Paper

[Show abstract …] [Request copy]

Open-Source Software

developed to disseminate my work

Upcoming Talks

Show all


Courses in which I was co-instructor or teaching assistant


Empirical Customer Data Analysis

Role: Co-instructor with Martin Schmidberger (Winter 2021).

Bachelor Seminar covering advanced marketing analytics techniques (e.g., prediction, logfile analysis, or text mining) and their practical application to real-world customer data.

Evaluation: 5.6/6

Marketing Analytics

Role: Teaching assistant for Bernd Skiera (Fall 2017 - Summer 2021).

Bachelor Course covering common marketing analytics techniques (e.g., regression, conjoint, clustering, perceptual mapping), applications to real-world data and a R/RStudio-based final exam.

Predictive Modeling in Marketing

Role: Co-instructor with Martin Schmidberger (Summer 2022).

Master Seminar focused on predictive modeling in Marketing. Covers the application of modern machine learning algorithms for predicting customers' purchase behavior and optimizing the efficiency of marketing campaigns.

Evaluation: 5.7/6