Insight: Open data, platform connectivity, and portfolio determine a brand’s online popularity

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Our new research shows that an open data policy, platform connectivity, and portfolio size determine a brand’s online popularity. The study is available on MDPI’s preprint server.

Background

Content marketing is increasingly important for online branding, particularly brand popularity. Brand popularity can be more easily determined online than through sales-based measures but is not yet well-explained from a content marketing perspective. Promising predictors of online brand popularity are open data syndication policies, connectivity to e-commerce platforms, product reviews, data health, and the depth and width of a brand’s 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 Icecat. We selected the overlapping dataset for brand popularity and reviews for all datasets. These datasets cover a period of 90 days from June 10, 2022, till September 24, 2022 (n = 333 manufacturing brands). We use backward stepwise multiple linear regression to determine the Brand Popularity Rank’s predictive content marketing model.

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. As a result, 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

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 or online success for a manufacturing brand.

Read the complete paper on MDPI’s preprint server.


Please contribute to our research and take the brand rank survey.


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