Beyond the First Touchpoint: How Initial Engagement, Marketing Communication, and Store Proximity Shape Multichannel Purchasing
Bibliographic record
Abstract
In the evolving retail landscape, companies embrace multichannel retailing to address consumer needs. Central to this discussion is the initial purchasing channel’s impact on multichannel engagements, which is complexified by the influential role of marketing communication methods (i.e., mail and email) and store proximity. This study focuses on a multinational consumer packaged goods company operating online and physical stores in Quebec, Canada. It explores two research questions: (1) how does a consumer's initial offline engagement impact total purchases in different channels? (2) how do communication methods and store proximity impact the relationship between the initial offline engagement and total purchases in different channels? The study focuses on the total quantity of products purchased for a specific category in online and offline channels. First, the findings suggest how consumers who first engage offline tend to make 92.88% fewer online purchases and 948.56% more offline purchases than consumers who first engage online. Second, for consumers who first engage offline, being on the direct mailing list may mitigate the decline in online purchases while potentially mitigating the increase in offline purchases. Third, for consumers who first engage offline, being on the email list may mitigate the decline in online purchases while potentially mitigating the increase in offline purchases. Fourth, for consumers who first engage offline, store proximity may amplify the decline in online purchases while potentially amplifying the increase in offline purchases. This study contributes to the existing knowledge of multichannel purchasing behavior, offering insights for retailers navigating the world of multichannel retailing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".