How to Catch Consumers' Attention

Results

According to the descriptive statistics of brand social media content strategies, the number of posts for information strategy was 397 (26.1% of the total number of posts), the number of posts for community strategy was 524 (34.5% of the total number of posts) and the number of posts for action content strategy was 598 (39.4% of the total number of posts). The majority of posts were categorized as action content, which reflects the active motivation of brands to reach consumers through social media in order to effectively motivate customers to consume. The estimation results are presented in Tables 1, 2 summarizes the findings. The impact of potential independent variables on the different levels and overall level of digital customer engagement differ significantly.

TABLE 1

Table 1. Model results table.

TABLE 2

Table 2. Summary of results.

Impact of Brand Social Media Content Strategies and Response Strategies

As shown in Table 1, we conducted a hierarchical regression analysis. The three models are generally significant and reasonably explain the variance of the dependent variable. We found significant differences in the impact of brand social media content strategies on different levels of digital customer engagement. The main positive impact of action strategy (vs. information) was significant (β = 0.177, p < 0.05; β = 0.470, p < 0.01; β = 0.203, p < 0.05), while the information strategy can generate more likes and shares compared to the community strategy (β = –0.215, p < 0.05; β = –0.604, p < 0.01), but the effectiveness of the community strategy in comments did not differ from the information strategy (β = –0.107, p = 0.355). We think that due to the high commercial intent of Weibo, for example, the content presentation of the reward involved in the action strategy is directly related to consumer interests and may be more likely to generate "likes" among users and motivate them to share in an organic way. Information strategy, while favoring traditional "informing" communication, have additional brand preferences based on behavioral motivations for brand equity, and consumers are willing to accept information with high perceived brand expertise. Among the response strategies, interactive response had a non-significant main effect on likes and shares (β = 0.119, p = 0.136; β = 0.086, p = 0.327), but a positive and significant effect on comments (β = 0.226, p < 0.01), and affective response was significantly different from interactive response, which instead had a significant increase in the main effect on likes and comments, but not having a significant effect on shares. As suggested in H5, cohesive response does significantly predict the different levels of digital customer engagement.

The Direct Impact of Brand Image and Discretionary Purchases

As shown in Table 1, we found differences in the impact that discretionary purchases has on different levels of digital customer engagement. At the level of positive filtering, experiential brands could generate more likes compared to material brands (β = 0.648, p < 0.01); while at the level of cognitive and affective processing, there was no significant difference between the two purchases types (β = –0.108, p = 0.514); however, at the level of advocacy, material brands had a more positive impact than experiential brands (β = –1.834, p < 0.01), which is an important finding that differs from previous studies. Second, in the area of brand image research, consistent with predictions, the "warmth" image was more attractive compared to the "competence" image and had a significantly higher impact on the three levels of digital customer engagement.

Moderating Effect of Brand Image and Discretionary Purchases

After controlling variables such as media richness and weekdays, consistent with our hypothesis, the mean difference between high and low response strategies was greater for the "competence" brand image. The moderating effect of "competence" brand image on digital customer engagement is more significant than that of "warmth" brand image, implying that brands with a more prominent "competence" image have a significantly higher digital customer engagement by increasing their response strategies (see Table 1). This implies that brands that highlight the "competence" image have a significant increase in digital customer engagement by advancing their response strategies. As shown in Figure 1, overall, "warmth" image has a higher level of digital customer engagement than the "competence" image, with a small increase in impact. However, when the brand image highlights the organizational competence, the more positive response strategy has a more significant impact on the digital customer engagement.

FIGURE 1

Figure 1. Moderating effect of brand image on the relationship between brand social media response strategy and digital customer engagement.

Next, as shown in Figure 2, in the comparison between experiential purchases and material purchases, there is a considerable increase in the slope of the fitted line for material purchases as the response strategy increases, thus showing that the higher the brand social media response strategy based on material purchases, the higher the digital customer engagement level. However, it is worth noting that brands with predominantly experiential purchases have little difference in the impact of high and low response strategies on digital customer engagement.

FIGURE 2

Figure 2. Moderating effect of discretionary purchases on the relationship between brand social media response strategy and digital customer engagement.