Assessing the Multichannel Impact of Brand Store Entry by a Digital-Native Grocery Brand
Bibliographic record
Abstract
For digital-native fast-moving consumer goods (FMCG) manufacturers that sell through their own online channel and have made headway into supermarkets, brand stores can represent the next step in a multichannel distribution strategy. In this research, the authors investigate the impact of introducing a brand store on a digital-native FMCG brand's sales in its existing company-owned online channel and in independent supermarkets, as well as on the brand's supermarket distribution. By incorporating brand store sales and operational costs, this research also specifies the entry effects on the brand's top-line total brand sales and bottom-line operating profit. Based on before-and-after-with-control-group analyses of the entry of ten brand stores by a digital-native FMCG brand, the authors show that brand store entry boosts supermarket sales, partially driven by a brand store's positive effect on the number of supermarkets listing the brand. Although they cannibalize company-owned online sales, brand store entries generate an influx of own brand store sales that offset online channel losses. Still, accounting for brand stores’ operational costs reveals that top-line growth is not always enough to preserve the bottom line.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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".