4.5 Demographic Variables

While demographics did play a role in reactions to the pitch videos, they did so across both the organic and synthetic categories.
That is to say, the data suggests that demographic categories observed for, including age, household income, and technology adoption style did yield significantly different results across effectiveness and brand impression categories. Different age groups, for example, perceive the effectiveness of the videos differently. Notably, older age groups, particularly those in the 45 to 60 range, tend to give higher effectiveness and brand impression ratings. Similarly, household income significantly affects the overall effectiveness ratings, with a strikingly low p-value of 8.15e-09. Higher income groups tend to rate the videos more favorably in both effectiveness and brand impression categories, possibly due to differences in educational background, exposure to similar content, or even increasing opportunities to consider brand investment potentials as their own income growth has opened more of those opportunities.
The analysis of the impact of technology adoption levels on overall effectiveness ratings reveals a statistically significant difference, as indicated by a p-value of 3.55e-05. This finding suggests that individuals’ attitudes and behaviors towards technology adoption are closely linked to how they perceive and rate the effectiveness of the videos. Those who identify as ”Innovators” or ”Early Adopters” tend to rate the videos more favorably, reflecting a potential correlation between a propensity for early technology adoption and a positive reception to the content of the videos. There was not a statistical significance across adoption categories relative to brand impression, however. This suggests that the medium of video had little, if nothing, to do with this correlation. Instead, it is conceivable that this reflects a broader correlation amongst the attitudes needed to adopt a new piece of technology before its fully vetted by the public and the attitudes needed to adopt a new business proposal before it has proven fully viable.
In contrast, gender does not show a statistically significant impact on the overall effectiveness ratings, with a p-value of 0.117, but there is a marginal difference in brand impression with a p-value of 0.0460. Male respondents, on average, rated the brand’s competence, trustworthiness, and likeability slightly higher than female respondents.
However, while these findings are informative and may prove useful for future study, the data collected in this study indicates that while these demographic factors play a role in the favorability of the video’s pitch, they do so uniformly across organic and synthetic videos. The same impact by age, income, and technology adoption persists regardless of which spokesperson was seen. While income level increase was correlated with an increased rating, for example, that increase happened for both organic and synthetic spokesperson pitches. This suggests that for synthetic avatars are not uniquely perceived differently based on the participant’s age, gender, income status, or tech adoption tendencies.
The gender of the spokesperson/avatar did not have a statistically significant impact on any of the composite averages or individual questions asked (see Table 6). This was true for the all respondents, for just those viewing synthetic videos, and for just those viewing organic videos. This suggests that future studies may achieve equivalent results with a 1x1 method instead of a 2x2 method.