Profiling consumers’ online shopping and following social media influencers behaviors

Abstract

In order to develop effective digital marketing strategies, this study explores how demographic factors may affect consumers’ online shopping and following social media influencers behaviors. Market segmentation theory and consumer demographics theory provide the theoretical foundation for this study. By analyzing survey data collected from 6,034 U.S. adults with decision tree analysis, there are a number of significant findings. First, educational level, income, and age category are the important predictors for consumers’ buying things online using a desktop or laptop computer behavior. Second, age category, geographic location (urban, suburban, rural) are the predictors for consumers’ buying things online using a smartphone behavior. Third, educational level, age, and geographic location are the predictors for consumers’ preferring online shopping over in-store shopping behavior. Fourth, age category and race-ethnicity are the predictors for following social media influencers behavior. Fifth, gender and age category are the predictors for purchasing something after seeing an influencer’s posts behavior. Finally, age category and gender are the predictors for purchase decisions getting impacted by influencers. The results provide valuable insights about consumer behaviors online, market segmentation, and influencer marketing strategies.

Keywords

• consumer profiling
• consumer demographics
• market segmentation
• social media influencer
• decision tree