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

54 Pages Posted: 28 Jun 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: June 19, 2019

Abstract

Logos serve a fundamental role in branding as the visual figurehead of the brand. Yet, due to the difficulty of using unstructured image data, prior research on logo design has been largely limited to non-quantitative studies. In this work, we explore logo design from a data-driven perspective. In particular, we aim to answer several key questions: first, to what degree can logos represent a brand's personality? Second, what are the key visual elements in logos that elicit brand and firm relevant associations, such as brand personality traits? Finally, given text describing a firm's brand or function, can we suggest features of a logo that elicit the firm's desired image? To answer these questions, we develop a novel logo feature extraction algorithm, that uses modern image processing tools to decompose unstructured pixel-level image data into meaningful visual features. We then analyze the links between firm identity and the features of logos through a deep, multiview generative model, which links visual features of logos with textual descriptions of firms and consumer ratings of brand personality by learning representations of brand identity. We apply our modeling framework on a dataset of hundreds of logos, textual descriptions from firms’ websites, third party descriptions of firms, and consumer evaluations of brand personality to explore these questions.

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 (June 19, 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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