Looking backwards to move forwards: assessing the informativeness of mobile shoppable video
Bibliographic record
Abstract
For both marketing professionals and researchers, what is shiny and new continues to captivate. The latest ‘it’ thing that marketers are gravitating towards is shoppable video where brands and retailers emphasize, entertain and engage consumers with mobile content that is directly ‘shoppable.’ In this new temporal and spatial interactive context, this study dissects the informative content of shoppable videos to develop an initial and comprehensive understanding of mobile shoppable videos. A content analysis of 200 shoppable videos utilizing emotional soft-sell type appeals, utilitarian hard-sell type appeals and humor appeals indicates that utilitarian-focused hard-sell shoppable videos dominate this new landscape thus creating a mobile shopping experience that relies on a hard-sell approach. Under an evolutionary perspective, the content of mobile shoppable videos or ‘digital direct-response ads’ was then compared to the content of direct-response infomercials to account for the modernization bias of digital marketing and explore how the informativeness of shoppable videos evolves and adapts over time. Findings suggest that mobile-designed creative executions adapt the hard-sell standard and feature significantly fewer mentions of price, special offers and guarantees, new ideas, and company research as they contextually adapt. It shows in the future-obsessed digital arena, old and dreary formats can conceptually and practically inform ‘next generation’ ‘revolutionary’ formats, which provides a foundation for future research into mobile shoppable video and updates marketing best practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".