Letting Logos Speak: Leveraging Multiview Representation Learning for Data-Driven Logo Design

55 Pages Posted: 28 Jun 2019 Last revised: 27 Nov 2019

See all articles by Ryan Dew

Ryan Dew

University of Pennsylvania - Marketing Department

Asim Ansari

Columbia Business School - Marketing

Olivier Toubia

Columbia Business School - Marketing

Date Written: November 25, 2019

Abstract

Logos serve a fundamental role as the visual figureheads of brands. Yet, due to the difficulty of using unstructured image data, prior research on logo design has largely been limited to non-quantitative studies. In this work, we explore logo design from a data-driven perspective. We develop both a novel logo feature extraction algorithm that uses modern image processing tools to decompose pixel-level image data into meaningful features, and a multiview representation learning framework that links these visual features to textual descriptions of firms, industry tags, and consumer ratings of brand personality. We apply this framework to a unique dataset of hundreds of brands. Our model is able to predict which brands use which logo features, and how consumers evaluate these brands' personalities. Moreover, we show that manipulating the model's learned representations through what we term "brand arithmetic" yields new brand identities, and can help with ideation. Finally, through an application to fast food branding, we show how our model can be used as a decision support tool for suggesting typical logo features for a brand, and for predicting consumers' reactions to new brands or rebranding efforts.

Keywords: logos, branding, machine learning, multiview learning, deep generative modeling, image processing

Suggested Citation

Dew, Ryan and Ansari, Asim and Toubia, Olivier, Letting Logos Speak: Leveraging Multiview Representation Learning for Data-Driven Logo Design (November 25, 2019). Available at SSRN: https://ssrn.com/abstract=3406857 or http://dx.doi.org/10.2139/ssrn.3406857

Ryan Dew (Contact Author)

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

Asim Ansari

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

Olivier Toubia

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

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