Hoogeveen, M.J. Open data policy, connectivity and portfolio determine brand popularity in e-commerce channel. Zenodo2023, doi:10.5281/ZENODO.7956494.
Hoogeveen, M.J. Open data policy, connectivity and portfolio determine brand popularity in e-commerce channel. Zenodo 2023, doi:10.5281/ZENODO.7956494.
Hoogeveen, M.J. Open data policy, connectivity and portfolio determine brand popularity in e-commerce channel. Zenodo2023, doi:10.5281/ZENODO.7956494.
Hoogeveen, M.J. Open data policy, connectivity and portfolio determine brand popularity in e-commerce channel. Zenodo 2023, doi:10.5281/ZENODO.7956494.
Abstract
Background Content marketing is increasingly important for online branding. Brand popularity can be more easily determined online than sales-based measures but is not yet well-explained from a content marketing perspective. Promising predictors are open data syndication policies, connectivity to e-commerce platforms, product reviews, data health, and the depth and width of a brands product portfolio. A predictive content marketing model can help brand owners to understand their e-commerce potential. Methods We used brand popularity (Brand Popularity Rank) and catalog data in combination with product reviews from an independent content aggregator. For all datasets, we selected the overlapping dataset for brand popularity and brand reviews based on a period of 90 days from June 10, 2022, till September 24, 2022 (n = 333 brands). Backward stepwise multiple linear regression was used to develop a predictive content marketing model of the Brand Popularity Rank. Results Through stepwise backward multiple linear regression five highly significant (p < 0.01) predictive factors for brand rank are selected in our content marketing model: the brand’s data syndication policy, the number of connected e-commerce platforms, a brand’s number of products, its number of products per category, and the number of product categories in which it is active. Our model explains 78% of the variance of Brand Popularity Rank and has a good and highly significant fit: F (5, 327) = 233.5, p < 0.00001.Conclusions We conclude that a content marketing model can adequately predict a Brand Popularity Rank based on online popularity. In this model an open content syndication policy, more connected e-commerce platforms, and catalog size, i.e., presence in more categories and more products per category are each related to a better (lower) Brand Popularity Rank score.
Keywords
Brand rank; content marketing; predictive model; open data policy; e-commerce
Subject
Business, Economics and Management, Marketing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
