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The amount of digital text available for analysis by consumer researchers has risen dramatically. Consumer discussions on the internet, product reviews, and digital archives of news articles and press releases are just a few potential sources for insights about consumer attitudes, interaction, and culture. Drawing from linguistic theory and methods, this article presents an overview of automated text analysis, providing integration of linguistic theory with constructs commonly used in consumer research, guidance for choosing amongst methods, and advice for resolving sampling and statistical issues unique to text analysis. We argue that although automated text analysis cannot be used to study all phenomena, it is a useful tool for examining patterns in text that neither researchers nor consumers can detect unaided. Text analysis can be used to examine psychological and sociological constructs in consumer-produced digital text by enabling discovery or by providing ecological validity.

Mobile applications (apps) have become an important platform for brands to interact with customers, but few studies have tested their effects on app adopters’ subsequent brand purchase behavior. This paper investigates whether adopters’ spending levels will change after they use a brand's app. Using a unique dataset from a coalition loyalty program with implementations of propensity score matching and difference-in-difference-in-difference methods, we compare the spending levels of app adopters with those of non-adopters. Specifically, we examine whether the use of the app's two main interactive features—information lookups and check-ins—influences adopters’ spending levels. We find that app adoption and continued use of the branded app increase future spending. Furthermore, customers who adopt both features show the highest increase. However, we also observe “the recency effect” – when customers discontinue using the app, their spending levels decrease. Our findings suggest that sticky apps which attract continuing uses can be a persuasive marketing tool because they provide portable, convenient, and interactive engagement opportunities, allowing customers to interact with the brand on a habitual basis. We recommend that firms should prioritize launching a mobile app to communicate with their customers, but they should also keep in mind that a poorly designed app, which customers abandon after only a few uses, may in fact hurt their brand experience and company revenues.

As consumers move through their decision journey, they adopt different goals (e.g., transactional vs. informational). In this research, the authors propose that consumer goals can be detected through textual analysis of online search queries and that both marketers and consumers can benefit when paid search results and advertisements match consumer search–related goals. In bridging construal level theory and textual analysis, the authors show that consumers at different stages of the decision journey tend to assume different levels of mental construal, or mindsets (i.e., abstract vs. concrete). They find evidence of a fluency-driven matching effect in online search such that when consumer mindsets are more abstract (more concrete), consumers generate textual search queries that use more abstract (more concrete) language. Furthermore, they are more likely to click on search engine results and ad content that matches their mindset, thereby experiencing more search satisfaction and perceiving greater goal progress. Six empirical studies, including a pilot study, a survey, three lab experiments, and a field experiment involving over 128,000 ad impressions provide support for this construal matching effect in online search.

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