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How Social Media drove the 2016 US Presidential Election: a longitudinal topic and platform analysis

with Raoul V. Kübler and Kai S. Manke, July, 2020

Abstract:

To what extent did external events and news versus the candidates’ own actions drive the 2016 election outcome? And were candidates misled if they focused on traditional market research versus the newer probabilistics polls? Based on the dynamic political will formation framework, the authors address these questions with a national daily dataset combining polling, donations, and TV advertising data with social media interactions to all candidates’ posts of the two candidates on Twitter, Facebook, and Instagram. Persistence modeling reveals that donations followed rather than drove the candidates’ polls. The probabilistic polls show a different impact of candidate ads and statements, news coverage, and fake news than do the traditional polls. TV ads on the economy or gun control, and on terror threats were most effective for respectively Hillary Clinton and Donald Trump. Topics matter, as fake news about a candidate hurts her chances on one topic, but benefits her on another topic. Moreover, platforms matter: Clinton’s chances benefitted from promoting women issues on Instagram, but declined from doing so on Twitter. Her moral language on Fairness Vice and social media users’ on Authority Virtue made voters less likely to vote for her, but more likely to share fake news about her and to talk positively about Trump. While news coverage had minimal impact, fake news on Clinton’s emails, shared on her Facebook page, greatly damaged her election chances. This fake news impact was most pronounced for seniors, Hispanics and high earners – demographics who moved towards Trump in the last weeks before the election. The authors draw lessons from the past election to advise where, when and how to drive the political conversation.

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O2O lifts profits, even offline sales

Blog

Introduction:

Online-to-offline (O2O) channels offer innovative ways to order daily products and services online (via apps) and have them delivered fast offline. Enjoying rising popularity among consumers, the global pandemic saw their growth accelerating. Delivery Hero, the world’s largest food delivery app, saw orders double, while Instacart added 300,000 workers in eight weeks. In BrandZ’ 2020 global brand rankings, Meituan is a top ten raiser, increasing its brand value by 27% to $24B, having evolved into ‘a one-stop O2O super app that people use to navigate everyday life tasks’.  The rise of delivery services like Meituan and Alibaba’s Ele.me (‘Are you hungry?’, shown below with video at https://www.alizila.com/video/what-is-ele-me/) also drove the boom in O2O retail, expected to grow 57 % in China during 2020, according to Kantar.  https://www.kantar.com/campaigns/brandz/global/

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When and why attitude surveys still matter in the consumer decision journey: Enduring attitudes and contextual interest

with Bernadette van Ewijk, Journal of Interactive Marketing

Full Article

Abstract:
Consumers leave traces of key interest to managers on their journey to purchase. Next to traditional survey-based attitudes, readily available online metrics now show aggregate consumer actions. But how do survey response metrics and online action metrics relate to each other? To what extent do they explain and predict brand sales across consumer categories? This article shows that surveys and online behavior provide complementary information for brand managers. Times series data for 32 brands in 14 categories reveal low correlations but substantial dual causality between survey metrics and online actions. Combining both types of metrics greatly increases the model’s power to explain and predict brand sales in low-involvement categories. By contrast, high-involvement categories do not gain much from adding survey-based attitudes to a model including online behavior metrics. The authors synthesize these generalizations in a new framework relating enduring attitudes to the contextual interest expressed by online actions. This new framework helps managers assess both types of metrics to drive brand performance depending on whether their goal is short-term sales or long-term brand health.

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Social media’s impact on the consumer mindset: When to use which sentiment extraction tool?

Journal of Interactive Marketing, with Raoul Kubler and Anatoli Colicev, 2020

Full Article

Abstract:
User-generated content provides many opportunities for managers and researchers, but insights are hindered by a lack of consensus on how to extract brand-relevant valence and volume. Marketing studies use different sentiment extraction tools (SETs) based on social media volume, top-down language dictionaries and bottom-up machine learning approaches. This paper compares the explanatory and forecasting power of these methods over several years for daily customer mindset metrics obtained from survey data. For 48 brands in diverse industries, vector autoregressive models show that volume metrics explain the most for brand awareness and purchase intent, while bottom-up SETs excel at explaining brand impression, satisfaction and recommendation. Systematic differences yield contingent advice: the most nuanced version of bottom-up SETs (SVM with Neutral) performs best for the search goods for all consumer mind-set metrics but Purchase Intent for which Volume metrics work best. For experienced goods, Volume outperforms SVM with neutral. As processing time and costs increase when moving from volume to top-down to bottom-up sentiment extraction tools, these conditional findings can help managers decide when more detailed analytics are worth the investment.

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Deriving Value from Conversations about your Brand

MIT Sloan Management Review, with Brad Fay, Ed Keller and Rick Larkin, Winter 2019

Short Article

Introduction:
Research shows that both online and off-line customer conversations drive
purchase decisions — but they require separate marketing strategies.
Nordstrom, the Seattle-based retailer, had a memorable 2017. In early February, Donald Trump, then the newly elected U.S. president, took to Twitter to berate Nordstrom for dropping the Ivanka Trump clothing line, complaining that the company had treated his daughter “so unfairly … terrible!” The tweet set off a powerful reaction in social media. Our research showed the number of weekly mentions of the Nordstrom brand on Twitter and other sites surged by 1,700%, while the tone of those conversations (as measured using natural language processing, which interprets meaning from adjacent words and context) swung sharply from positive to negative.1 However, in off-line conversations (measured via surveys), the sentiment stayed positive. Amidst these mixed signals, Nordstrom rolled through the 2017 holiday season with a 2.5% sales increase over the prior year.

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A broader view on brands’ growth and decline

International Journal of Market Research, with Lia Zarantonello and Marcello Formisano

Full Article

Abstract:
What does it take to grow a brand? How to avoid its decline? Some popular answers to these questions can be found in the research by Byron Sharp and others from the Ehrenberg-Bass (EB) Institute on “how brands grow.” In this article, we propose that such an approach, despite its strengths, lends itself to some limitations when taken too literally. We maintain that a broader notion and role of branding—encompassing brand equity, brand portfolio, and circular relationship of attitudes and behaviors—should be adopted by marketeers to derive better managerial implications for sustainable brand growth. We, therefore, invite marketers to not oversimplify Dirichlet evidences by thinking of availability as the only (costly) response to all marketing challenges

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Big and lean is beautiful: A conceptual framework for data-based learning in marketing management

Soyer, E., Pauwels, K., & Seggie, S. H. (2019). Marketing in a Digital World (Review of Marketing Research, 16, 63-83.

Short Article

Abstract:
While Big Data offer marketing managers’ information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

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The Impact of Adding Online-to-Offline Channels on Firm’s Offline and Total Revenues

with Sha Zhang and Chenming Peng,  Journal of Interactive Marketing, 47, 115-128, 2019.

Full Article

Abstract:
Online-to-offline service platform (O2OSP) channels offer innovative means for customers to order local, daily services online (via apps) and have them delivered almost instantly offline. By comparing the business models underlying O2OSP, traditional online and offline, and platform-based e-commerce channels, this article aims to identify the short- and long-term impacts of adding an O2OSP channel on firms’ offline and total sales and profits. The analysis focuses primarily on a recent set of daily data gathered from a Chinese fast-food restaurant chain with 35 physical stores that also participates in four food delivery O2OSP channels. The panel data regressions with fixed effects reveal that adding O2OSP channels hurts offline and total profits in the short run but improves offline and total sales and profits in the long run. Specifically, offline and total sales increase by 23.28% and 33.94%, respectively. Thus, the O2OSP channel can serve as a complement to, rather than a substitute for, the offline channel. These results challenge previous research on the sales effects of adding (pure) online or offline channels and highlight the attractiveness of O2OSP channels for improving sales and profits. However, negative interaction effects among different O2OSP channels also signal that adding more O2OSP channels does not necessarily lead to profitable growth

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App popularity: Where in the world are consumers sensitive to price, ratings and product characteristics

with Raoul Kubler, Thomas Fandrich and Gokhan Yildirim, Journal of Marketing, 82(5), 2018, 20-44.

Full Article

Abstract:
Many companies compete globally in a world in which user ratings and price are important drivers of performance but whose importance may differ by country. This study builds on the cultural, economic, and structural differences across countries to examine how app popularity reacts to price and ratings, controlling for product characteristics. Estimated across 60 countries, a dynamic panel model with product-specific effects reveals that price sensitivity is higher in countries with higher masculinity and uncertainty avoidance. Ratings valence sensitivity is higher in countries with higher individualism and uncertainty avoidance, while ratings volume sensitivity is higher in countries with higher power distance and uncertainty avoidance and those that are richer and have more income equality. For managers, the authors visualize country groups and calculate how much price should decrease to compensate for a negative review or lack of reviews. For researchers, they highlight the moderators of the volume and valence effects of online ratings, which are becoming ubiquitous in this connected world.

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Social Media and Customer-Based Brand Equity: An Empirical Investigation in the Retail Industry

with Anatoli Colicev and Ashwin Malshe, Administrative Sciences, 8 (55), 2018.

Full Article

Abstract:
As customer-brand engagement progressively shifts to digital domains, understanding social media effects in branding has become a vital issue. Social media effectiveness is especially important for the US retail sector due to intense competition among retailers for consumer attention and engagement on digital channels. Yet, the research on the effectiveness of social media in the retail industry remains sparse. Thus, the purpose of this paper is to investigate how social media affects US retailers’ customer-based brand equity (CBBE) which is an important indicator of brand success. Using a dataset of 15,717 retailer-day observations, the authors empirically test the dynamics between owned and earned social media and CBBE using panel vector autoregression (PVAR). The authors find strong impacts of owned and earned social media on CBBE across the board. However, they find that owned social media harms CBBE of retailers dealing in hedonic and high involvement products. Whereas owned social media helps general retailers in building CBBE, it reduces CBBE of specialty retailers.

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Battle of the Brand Fans: Impact of brand Attack and Defense on social media

with Behice Ece Ilhan and Raoul Kubler, Journal of Interactive Marketing, 43 (August), 2018, 33-51.

Full Article

Abstract:
Fans of a brand attack fans of rival brands on social media. Given the nature of such rival brand fan attacks, managers are unsure about how much control they should exercise on brand-negative comments on their owned social media touchpoints, and what brand actions drive these Attack, Defense and Across (ADA) posts. Multimethod analysis identifies ADA’s impact across industries of technology, fast food, toothpaste, beverages, and sports apparel. Sentiment analysis identifies that fans posting in both communities stimulate both brand-negative and brand-positive comments. Despite their relatively low prevalence (1–6% of all posts), ADA posts induce broader social-media brand engagement as they substantially increase and prolong the effects of managerial control variables such as communication campaigns and new product introductions. Brand managers, thus, have specific levers to stimulate the positive consequences of rival brand fan posting on their owned media.

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Pricing Best Sellers and Traffic Generators: The Role of Asymmetric Cross-selling

with Cenk  Kocas, and Jonathan D. Bohlmann. ” Journal of Interactive Marketing 41, 2018, 28-43.

Full Article

Abstract:
Among the many items online retailers sell, some stand out as best sellers and are often sold at considerable discounts. Bestseller discounting 10 can encourage customer traffic and the purchase of a basket of other products in the same transaction. Although most studies treat retailers as 11 symmetric, the cross-selling potential is generally asymmetric across retailers, since some online retailers have more products to sell. In addition, 12 the cross selling effect works both ways — customers intending to buy a best-seller may buy other items in their shopping basket, while other 13 customers intending to buy a basket may buy a best-seller while visiting the retailer. The authors model the pricing implications of this rich variety 14 of asymmetric cross-selling, with both best sellers and typical baskets acting as traffic generators and cross-sold products. The common wisdom 15 that loss leader pricing leads to neither a significant increase in-store traffic nor an increase in profits does not apply in an asymmetric case where 16 one retailer has more products to cross-sell. The cross-selling potential of products even far down the bestseller list is demonstrated. Empirical 17 analyses provide support for key findings of the theoretical model using book pricing and sales rank data from multiple online retailers.

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Improving Consumer Mind-Set Metrics and Shareholder Value through Social Media: The Different Roles of Owned and Earned

with A. Colicev, A. A. Malshe, P. O’Connor, Journal of Marketing, 82(1), 2018, 37-56.

Full Article

Abstract:
Although research has examined the social media–shareholder value link, the role of consumer mindset metrics in this relationship remains unexplored. To this end, drawing on the elaboration likelihood model and accessibility/ diagnosticity perspective, the authors hypothesize varying effects of owned and earned social media (OSM and ESM) on brand awareness, purchase intent, and customer satisfaction and link these consumer mindset metrics to shareholder value (abnormal returns and idiosyncratic risk). Analyzing daily data for 45 brands in 21 sectors using vector autoregression models, they find that brand fan following improves all three mindset metrics. ESM engagement volume affects brand awareness and purchase intent but not customer satisfaction, while ESM positive and negative valence have the largest effects on customer satisfaction. OSM increases brand awareness and customer satisfaction but not purchase intent, highlighting a nonlinear effect of OSM. Interestingly, OSM is more likely to increase purchase intent for high involvement utilitarian brands and for brands with higher reputation, implying that running a socially responsible business lends more credibility to OSM. Finally, purchase intent and customer satisfaction positively affect shareholder value.

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Combining big data and lean startup methods for business model evolution

with Steven Seggie, and Emre Soyer, AMS Review, December, 7 (3-4), 2017, 154-169

Full Article

Abstract:
The continued survival of firms depends on successful innovation. Yet, legacy firms are struggling to adapt their business models to successfully innovate in the face of greater competition from both local and global startups. The authors propose that firms should build on the lean startup methodology to help adapt their business models while at the same time leveraging the resource advantages that they have as legacy corporations. This paper provides an integrated process for corporate innovation learning through combining the lean startup methodology with big data. By themselves, the volume, variety and velocity of big data may trigger confirmation bias, communication problems and illusions of control. However, the lean startup methodology has the potential to alleviate these complications. Specifically, firms should evolve their business models through fast verification of managerial hypotheses, innovation accounting and the build-measure-learn loop cycle. Such advice is especially valid for environments with high levels of technological and demand uncertainty

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A marketing perspective on business models.

with Gatignon, Hubert, Xavier Lecocq, and Alina Sorescu. AMS Review, December, 7 (3-4), 2017, 85-89

Short Article

Abstract:
The Internet and the digital economy have prompted the creation of new business models (McKinsey and Company 2017). Technologies that can enable new business platforms and increased digital access to potential customers have significantly changed in the manner in which firms conduct business, from the creation of value (see, for instance, the literature on co-creation, e.g., Hoyer et al. 2010, or that on open innovation, e.g., Chesbrough et al. 2006), to the appropriation of value (see, for instance, research on freemium pricing, e.g., Pauwels and Weiss 2008, or on pay-per-use, e.g., Prasad et al. 2003). Competitive advantage from product innovation has become difficult to maintain for extended periods of time; as a result, incumbents are increasingly looking for ways to update and innovate their existing business models (Neus et al. 2017). For instance, Accenture reports that 80% of firms plan to grow via new business models over the next 5 years (Accenture 2014).
Changes in business practice have also led to a heightened focus on business models in the academic literature. Several recent reviews highlight the scope of this literature, which ranges from attempts to define and provide structure for the concept of business model, to examinations of specific types of business models (Coombes and Nicholson 2013; Foss and Saebi 2017; Massa et al. 2017; Zott et al. 2011). The majority of these articles, however, can be found in management journals. Attempts to study business models in marketing are scant, and typically focus on specific sectors of the economy (e.g., Wieland et al. 2017 on services, and Sorescu et al. 2011 on retailing) or on specific types of business models (e.g., Kind et al. 2009; Pauwels and Weiss 2008). Moreover, while value creation and appropriation have separately received attention in marketing, they have been rarely studied in combination, which is a prerequisite to understanding business models. This is a surprising gap, given that marketers are responsible for the design and implementation of several aspects of the value creation and value appropriation components of a business model. This special issue is a first step in stimulating more research on this topic in the marketing literature. Building on what we have learned from the management literature but bringing insights from the marketing literature’s expertise on building a viable value proposition, we can further enhance our understanding of how business models can be effectively designed in order to lead to sustainable firm performance.

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The Impact of Brand Familiarity on Online and Offline Media Synergy

with Ceren Demirci, Gokhan Yildirim and Shuba Srinivasan, International Journal of Research in Marketing, 33(4), 2016, 739-753.

Full Article

Abstract:
Rooted in the integrated marketing communication framework, this paper conceptualized how brand familiarity affects online and cross-channel synergies. The empirical analysis uses Bayesian vector autoregressive models to estimate long-term elasticities for four brands. The authors distinguish customer-initiated communication (typically online) from firm-initiated communication (typically offline). Their results indicate that within-online synergy is higher than online-offline synergy for both familiar brands but not for both unfamiliar brands. Managers of unfamiliar brands may obtain substantial synergy from offline marketing spending, even though its direct elasticity pales in comparison with that of online media while managers of familiar brands can generate more synergy by investing in different online media.

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Demonstrating the Value of Marketing

with Dominique M. Hanssens, Journal of Marketing, 80 (6), 2016,173-190.

Full article

Summary
Marketing departments are under increased pressure to demonstrate their economic value to the firm. This challenge is exacerbated by the fact that marketing uses attitudinal (e.g., brand awareness), behavioral (e.g., brand loyalty), and financial (e.g., sales revenue) performance metrics, which do not correlate highly with each other. Thus, one metric could view marketing initiatives as successful, whereas another could interpret them as a waste of resources. The resulting ambiguity has several consequences for marketing practice. Among these are that the scope and objectives of marketing differ widely across organizations. There is confusion about the difference between marketing effectiveness and efficiency. Hard and soft metrics and offline and online metrics are typically not integrated. The two dominant tools for
marketing impact assessment, response models, and experiments, are rarely combined. Risk in marketing planning and execution receives little consideration, and analytic insights are not communicated effectively to drive decisions. The authors first examine how these factors affect both research and practice. They then discuss how the use of marketing analytics can improve marketing decision making at different levels of the organization. The authors identify gaps in marketing’s knowledge base that set the stage for further research and enhanced practice in demonstrating marketing’s
value.

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