9 research outputs found

    social media s impact on the consumer mindset when to use which sentiment extraction tool

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    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

    Faking or Convincing: Why Do Some Advertising Campaigns Win Creativity Awards?

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    Since the Sarbanes-Oxley Act was passed in 2002, it has become commonplace in the advertising industry to use creativity-award-show prizes instead of gross income figures to attract new customers. Therefore, achieving a top creativity ranking and winning creativity awards have become high priorities in the advertising industry. Agencies and marketers have always wondered what elements in the advertising creation process would lead to the winning of creativity awards. Although this debate has been dominated by pure speculation about the success of different routines, approaches and strategies in winning creativity awards, for the first time our study delivers an empirical insight into the key drivers of creativity award success. We investigate what strategies and which elements of an advertising campaign are truly likely to lead to winning the maximum number of creativity awards. Using a sample of 108 campaigns, we identify factors that influence campaign success at international advertising award shows. We identify innovativeness and the integration of multiple channels as the key drivers of creativity award success. In contrast to industry beliefs, meaningful or personally connecting approaches do not seem to generate a significant benefit in terms of winning creativity awards. Finally, our data suggest that the use of so-called “fake campaigns” to win more creativity awards does not prove to be effective

    The effect of review images on review helpfulness:A contingency approach

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    Online retailing is still dominated by information asymmetries, as it often remains difficult for consumers to fully judge the quality of a product online. Reviews written by customers help to reduce this asymmetry. Helpful reviews have thus become an important tool to drive online sales. Beside textual information, reviews nowadays also often include images that can further help consumers to better judge products or services. While online retailers need to invest substantial resources in hosting and incentivizing review images, it remains unclear under which conditions review images drive (or reduce) review helpfulness and how review image content affects review helpfulness. We rely on a set of more than 97,000 reviews from Amazon to investigate the contingencies under which review images increase review helpfulness. Furthermore, we rely on more than 6,000 images in our data set to explore how review image content (i.e., image focus and context fit) drives review helpfulness. Our results show that online retailers should especially motivate consumers to include images in a review when the overall rating is extremely positive, when the reviewer has a high reputation, and when the review addresses a hedonic or experience product. Our image content analysis further shows that images help to increase helpfulness when they show the product in application. This effect is especially strong in the case of longer reviews

    Machine Learning and Big Data

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    The role of the partner brand’s social media power in brand alliances

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    Due to copyright restrictions, the access to the full text of this article is only available via subscription.Managers frequently seek strategies to profit systematically from social media to increase product sales. By forming a brand alliance, they can acquire an installed social media base from a partner brand in an attempt to boost the sales of their composite products. Drawing from power theory, this article develops a conceptual model of the influence of the social media power of partner brands on brand alliance success. The proposed framework details the partner brand’s social media power potential (size and activity of the social media network), social media power exertion (different posting behaviors and comments), and their interaction. The authors test this framework with an extensive data set from the film industry, in which films function as composite products and actors represent partner brands. The data set features 442 movies, including 1,318 actor–movie combinations and weekly social media data (including 41,547 coded Facebook posts). The authors apply a linear mixed-effects model, in which they account for endogeneity concerns. The partner brand’s social media power potential, power exertion, and their interaction can all lead to higher composite product sales. By coding different types of product-related posts, this article provides estimates of their varying monetary value
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