Ron Berman

Ron Berman
  • Assistant Professor of Marketing

Contact Information

  • office Address:

    746 Jon M. Huntsman Hall
    730 Walnut Street
    University of Pennsylvania
    Philadelphia, PA 19104

Research Interests: advertising attribution, entrepreneurship, game theory, industrial organization, marketing analytics, online marketing, search engine marketing, startups

Links: Personal Website, @marketsensei

Overview

Ron Berman is an assistant professor of marketing at the Wharton School. He focuses his research on online marketing, marketing analytics and the marketing actions of startup firms. His recent research looks at how advertisers incorrectly attribute sales to online advertising which results in suboptimal campaigns, and how search engine optimization (SEO) may improve search engine results contrary to common belief.
Ron’s previous experience includes working on Internet and Media investments as a venture capitalist at Carmel Ventures, and developing software for the IDF. Currently Ron mentors startups at the UpWest Labs accelerator and spends time meeting and advising young entrepreneurs.
Ron holds a PhD and MSc in Business Administration (Marketing) from the University of California, Berkeley, an MBA and MSc in Computer Science from Tel-Aviv University, and a BSc in Computer Science, Physics and Mathematics from the Hebrew University in Jerusalem.
More information is available at Ron’s personal page: www.ron-berman.com
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Research

  • Ron Berman and Zsolt Katona (Under Review), The Impact of Curation Algorithms on Social Network Content Quality and Structure.

    Abstract: Curation algorithms are selection and ranking algorithms that social media platforms use to improve user experience. This paper analyzes the impact of curation algorithms on the number of friends consumers connect to and the quality of content created by producers. The model takes into account both vertical and horizontal differentiation and analyzes three different types of algorithms. The results show that without algorithmic curation, the number of friends an individual has and the quality of content on the platform are strategic complements. Introducing algorithmic curation makes consumers less selective in their follower lists when content quality is low. In equilibrium, producers of content receive lower payoffs because they enter into a contest leading to a prisoner’s dilemma. The quality of content on the platform may increase if the marginal cost of producing this quality is high enough. Both of these effects may result theoretically in more diverse content consumption, but in equilibrium we find that a perfect filtering algorithm may reduce the horizontal distance of matched content resulting in a filter bubble. We identify an algorithm that focuses on filtering low quality items that results in higher quality of content as well as higher diversity under specific conditions.

  • Ron Berman, Colman Humphrey, Shiri Melumad, Robert Meyer (Under Review), Make America Tweet Again: A Dynamic Analysis of Micro-blogging During the 2016 U.S. Republican Primary Debates.

    Abstract: The 2016 presidential election illustrated the growing role that micro-blogging sites such as Twitter play in electoral politics. In this paper we report an analysis of a unique dataset that characterizes how the substantive and affective content of Tweets evolved during the course of three pivotal Republican Primary debates leading up to the 2016 Presidential election. We find that as the debates progressed Tweets provided an increasingly backward-looking account of the debates, as original content gradually gave way to retweets of the most popular earlier posts. Moreover, whereas during the debate Tweets focused on a mix of substantive topics, the Tweets that had the longest staying power after the debates were those that focused on the more sensationalist news events, often through pictures and videos. As such, a user coming to Twitter after the debate was over would have encountered a different topical and emotional landscape than one who had been following the site in real-time, one more closely resembling a tabloid than a substantive discussion forum. We explore the potential implications of the findings for the role that micro-blogging sites may have on shaping voter opinion in elections.

  • Ron Berman Case Study: United by Blue.

    Description: United by Blue, an outdoor apparel brand, located in Philadelphia focused on ocean and waterway conservation. The company ran two crowdfunding campaigns; one in 2012 and the second in 2014 which surpassed its funding goal tenfold. The case describes the sequence of strategic choices the company must make in order to launch its third crowdfunding campaign for a highly innovative winter jacket. Through detailing the structure of crowdfunding platforms, campaign creations, and decisions needed to be taken by entrepreneurs, the case illustrates tradeoffs facing entrepreneurs and how crowdfunding can operate as both a marketing channel as well as a financing channel for firms.   To request permission to use the case for teaching purposes, please contact the Wharton Course Materials Initiative

  • Ron Berman, Alexander Saldanha, Keshore Vunmaro Advertising Conversion Attribution (US Patent 8775248 B1).

    Description: An advertising attribution system determines an attribution value for a set of advertising modalities associated with a conversion event. The modalities each provided an advertisement to a user who performed the conversion event. A conversion value associated with each of a plurality of modality subsets is determined representing the value to the advertiser of providing advertisements by the modalities in each modality subset. Based on the conversion value of each modality subset, a marginal value for each modality is determined for the set of modalities associated with the conversion event.

  • Ron Berman (Under Review), Beyond the Last Touch: Attribution in Online Advertising.

    Abstract: Online advertisers often utilize multiple publishers and bid in multiple auctions concurrently to deliver ads, a process which may result in externalities between publishers that impact advertising effectiveness. In conjunction with these externalities, uncertainty about consumer visit patterns may limit the advertiser's ability to optimize its campaigns. We define the attribution problem as the attempt to measure such uncertainties and correct for the externalities, and determine the characteristics of a good attribution process. Using an analytical model of an online campaign we show that publisher externalities will lead an advertiser to shift from truthful bidding in equilibrium, and that combined with uncertainty about consumer visits, its profits will be lowered. Our analysis of a common attribution method known as last-touch shows that it reduces advertiser profits compared to not using attribution at all, and that stronger advertisers suffer from a misallocation of consumer impressions due to overbidding for ads resulting from the attribution process. Our analysis of an attribution scheme based on the Shapley value shows that it will improve the profits of advertisers when conversion rates in the market are not too high.

  • Ron Berman and Zsolt Katona (2013), The Role of Search Engine Optimization in Search Marketing, Marketing Science.

    Abstract: This paper examines the impact of search engine optimization (SEO) on the competition between advertisers for organic and sponsored search results. The results show that a positive level of search engine optimization may improve the search engine's ranking quality and thus the satisfaction of its visitors. In the absence of sponsored links, the organic ranking is improved by SEO if and only if the quality provided by a website is sufficiently positively correlated with its valuation for consumers. In the presence of sponsored links, the results are accentuated and hold regardless of the correlation. When sponsored links serve as a second chance to acquire clicks from the search engine, low-quality websites have a reduced incentive to invest in SEO, giving an advantage to their high-quality counterparts. As a result of the high expected quality on the organic side, consumers begin their search with an organic click. Although SEO can improve consumer welfare and the payoff of high-quality sites, we find that the search engine's revenues are typically lower when advertisers spend more on SEO and thus less on sponsored links. Modeling the impact of the minimum bid set by the search engine reveals an inverse U-shaped relationship between the minimum bid and search engine profits, suggesting an optimal minimum bid that is decreasing in the level of SEO activity.

Teaching

Current Courses

  • MKTG955 - Econ/or Models In Mktg B

    This is a continuation of MKTG 954. This doctoral seminar reviews analytical models relevant to improving various aspects of marketing decisions such as new product launch, product line design, pricing strategy, advertising decisions, sales force organization and compensation, distribution channel design and promotion decisions. The primary focus will be on analytical models. The seminar will introduce the students to various types of analytical models used in research in marketing, including game theory models for competitive analysis, agency theory models for improving organization design and incentives within organizations, and optimization methods to improve decision making and resource allocation. The course will enable students to become familiar with applications of these techniques in the marketing literature and prepare the students to apply these and other analytical approaches to research problems that are of interest to the students.

    MKTG955302

Past Courses

  • MKTG270 - DGTL SOCIAL & E-COM MKTG

    MKTG 270 explores the digital marketing environment from both a consumer and business perspective. The course provides an overview of various online business models and delves into digital advertising and social media marketing techniques and technologies. A mixture of case studies, guest speakers and assignments, including one that uses real advertising data, translates theory into practice. It is recommended that students enrolling in the course be comfortable using Excel and are knowledgeable in applying regression analysis techniques. Students who would prefer a less technical course may wish to take MKTG 227, Digital Marketing and Electronic Commerce, a half cu course offered by the department.

  • MKTG770 - DGTL SOCIAL & E-COM MKTG

    MKTG 770 explores the digital marketing environment from both a consumer and business perspective. The course provides an overview of various online business models and delves into digital advertising and social media marketing techniques and technologies. A mixture of case studies, guest speakers and assignments, including one that uses real advertising data, translates theory into practice. It is recommended that students enrolling in the course be comfortable using Excel and are knowledgeable in applying regression analysis techniques. Students who would prefer a less technical course may wish to take MKTG 727, Digital Marketing and Electronic Commerce, a half cu course offered by the department.

  • MKTG955 - ECON/OR MODELS IN MKTG B

    This is a continuation of MKTG 954. This doctoral seminar reviews analytical models relevant to improving various aspects of marketing decisions such as new product launch, product line design, pricing strategy, advertising decisions, sales force organization and compensation, distribution channel design and promotion decisions. The primary focus will be on analytical models. The seminar will introduce the students to various types of analytical models used in research in marketing, including game theory models for competitive analysis, agency theory models for improving organization design and incentives within organizations, and optimization methods to improve decision making and resource allocation. The course will enable students to become familiar with applications of these techniques in the marketing literature and prepare the students to apply these and other analytical approaches to research problems that are of interest to the students.

  • MKTG972 - ADV TOPICS MKTG PART B

    Taught collectively by the faculty members from the Marketing Department, this course investigates advanced topics in marketing. It is organized in a way that allows students to 1) gain depth in important areas of research identified by faculty; 2) gain exposure to various faculty in marketing and their research values and styles; and 3) develop and advance their own research interests.

  • MKTG973 - RESEARCH SEM MKTG PART A

    This course is taught collectively by the faculty members from the Marketing Department. It is designed to expose Doctoral students to the cutting-edge research in marketing models in order to help them to define and advance their research interests. This course will offer: in-depth discussions on some important topics in marketing by experts in respective areas; tools, and methodologies required for conducting research in those areas; broad exposure to our faculty members and their proven research styles.

Awards and Honors

  • Frank M. Bass Dissertation Paper Award, 2014
  • ISMS Doctoral Dissertation Proposal Competition, 2014

In the News

Knowledge @ Wharton

Activity

In the News

Why Amazon’s ‘1-Click’ Ordering Was a Game Changer

Amazon’s patent on “1-Click” ordering, which recently expired, helped jump-start the e-commerce giant’s growth from a virtual bookstore to a massive online marketplace.

Knowledge @ Wharton - 2017/09/14
All News

Awards and Honors

Frank M. Bass Dissertation Paper Award 2014
All Awards