Mobile diaries – Benchmark against metered measurements: An empirical investigation

Lovett, Mitchell J.; Peres, Renana

doi:10.1016/j.ijresmar.2018.01.002

Cited by 13 publications

(14 citation statements)

References 57 publications

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“…The benefits of experience tracking as a data collection method enabled us to assess the effects of our metric on brand purchases overall, as well as in the digital and traditional channels, but there are also limitations of this method. We illustrated its robustness by comparing self-reported data with aggregated data obtained from media research companies (see also Lovett and Peres (2018)). However, because it relies on self-reporting, our data collection method cannot detect brand encounters below perceptual thresholds.…”

Section: Discussionmentioning

confidence: 99%

“…It also reduces the cognitive burden associated with recalling brand encounters and the memory decay that can arise with retrospective surveys (Danaher and Dagger, 2013). For an overview of this data collection method, see Baxendale et al (2015) or Lovett and Peres (2018). To report on their brand encounters, respondents answered three questions through a smartphone app: Which brand is encountered?…”

Section: Data Collectionmentioning

confidence: 99%

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Customer journey analyses in digital media: exploring the impact of cross-media exposure on customers' purchase decisions

Klein

Zhang

Falk

et al. 2020

JOSM

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PurposeIn the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.Design/methodology/approachBuilding on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.FindingsCross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.Practical implicationsThe proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.Originality/valueService managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.

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Section: Discussionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Customer journey analyses in digital media: exploring the impact of cross-media exposure on customers' purchase decisions

Klein

Zhang

Falk

et al. 2020

JOSM

View full text Add to dashboard Cite

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“…Mobile diaries are a trending tool to collect repeated self-reports about experiences. They have been used as a research tool in variety of domains including psychology, geography, health, medicine (e.g., Hektner et al 2007;Heinonen et al 2012;Hensel et al 2012;Hofmann and Patel 2015), marketing practice, and recently also by academic researchers (Lovett and Peres 2018). In mobile diary visual studies, respondents are usually asked to take photos of certain experiencesfor example, photograph what they see on the shelf, windows of stores they stop by, or the content of their refrigerator.…”

Section: Directly Elicited Imagesmentioning

confidence: 99%

Image Analytics in Marketing

Dzyabura

Kihal

Peres

2021

Handbook of Market Research

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Recent technical advances and the rise of digital platforms enhanced consumers' abilities to take and share images and led to a tremendous increase in the importance of visual communication. The abundance of visual data, together with the development of image processing tools and advanced modeling techniques, provides unique opportunities for marketing researchers, in both academia and practice, to study the relationship between consumers and firms in depth and to generate insights which can be generalized across a variety of people and contexts.However, with the opportunity come challenges. Specifically, researchers interested in using image analytics for marketing are faced with a triple challenge:(1) To which type of research questions can image analytics add insights that cannot be obtained otherwise? (2) Which visual data should be used to answer the research questions, and (3) which method is the right one?In this chapter, the authors provide a guidance on how to formulate a worthy research question, select the appropriate data source, and apply the right method of analysis. They first identify five relevant areas in marketing that would benefit greatly from image analytics. They then discuss different types of visual data and explain their merits and drawbacks. Finally, they describe methodological approaches to analyzing visual data and discuss issues such as feature extraction, model training, evaluation, and validation as well as application to a marketing problem.

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“…as discussed in the preceding section (measures and indicators of these states having been derived from stages 2 and 3). These temporal effects could be addressed through an app mediated 'diary' (see Lovett and Peres 2018) or app based record approach or (less reliably) through self-reporting/recall (possibly through depth methods) or again, through neuroscience applications. A form of observational experiment is a possibility, during which a smartphone is issued to participants tasked with choosing a given high involvement product (perhaps with the limit of one week).…”

Section: ] Transitional Temporal and Longitudinal Dynamicsmentioning

confidence: 99%

“…Neuroscience methods may also have a place in mapping the cognitive morphology during variant lab-based purchase tasks on different cohorts with differential use of smart technology (see Braeutigam et al, 2019 or Wilmer et al, 2019). Mobile diaries are another possibility; Lovett and Peres (2018) examine the efficacy of this form of data capture in a consumer research context.…”

Section: Theory Development Corroboration and Empirical Deploymentmentioning

confidence: 99%

Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making

et al. 2020

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We develop the concept of exogenous cognition (ExC) as a specific manifestation of an external cognitive system. ExC describes the technological and algorithmic extension of (and annexation of) cognition in a consumption context. ExC provides a framework to enhance the understanding of the impact of pervasive computing and smart technology on consumer decision-making and the behavioural impacts of consumer analytics. To this end, the article provides commentary and structures to outline the impact of ExC and to elaborate the definition and reach of ExC. The logic of ExC culminates in a theory of cognitive states comprising of three potential decision states: endogenous cognition, symbiotic cognition and surrogate cognition. These states are posited as transient (consumers might move between them during a purchase episode) and determined by individual propensities and situational antecedents. The article latterly provides various potential empirical avenues and issues for consideration and debate.

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Mobile diaries – Benchmark against metered measurements: An empirical investigation

Cited by 13 publications

References 57 publications

Customer journey analyses in digital media: exploring the impact of cross-media exposure on customers' purchase decisions

Customer journey analyses in digital media: exploring the impact of cross-media exposure on customers' purchase decisions

Image Analytics in Marketing

Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making

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