by: Chasson Gracie
I created the conceptual model to understand the independent variables that help predict music consumption, along with predicting how much change in those independent variables can impact oneâ€™s consumption of music in a way that leads to revenue for an artist, an artistsâ€™ label et al.
In our music consumption battery, there were five statements and a respondent rated each from strongly agree to strongly disagree. The scoring was summed up scoring for all 490 respondents and obtained a mean score, being above the mean is classified as having high music consumption; being below the mean is classified as having low music consumption.
Here are the six key findings from the model:
1. Cognitive use of music is the biggest predictor of music consumption.
Cognitive Users are defined as people who listens to music in a very rational/analytical manner. 36% of core music consumers are cognitive users of music, and while they are not a majority, they do explain the biggest portion of music consumption within the model. Cognitive users are more likely than emotional users of music to consume music, while background users as a whole were not statistically significant, hence not included in the model as a holistic battery.
2. Create a musical ecosystem – the more you share the musical taste of your friends, the more likely you are to consume music â€“ up to 5X more likely than the general population.Â
While radio DJs, blog writers et al have some sway in the fate of an artist, when it comes to actual music consumption, the more oneâ€™s friends have the same taste, the more likely they are to have high consumption of music. It seems that having friends with the same taste of music forms an ecosystem that encourages all involved to consume even more than if they all lived on separate musical islands.
3. Males are 1.5X more likely to have high music consumption than females.Â
When one thinks of the audiences of a Justin Bieber or One Direction, one has images of screaming girls who purchase lots of products of their favorite artists, whether it be albums and concert tickets, or memorabilia and endorsed products. However, there seems to be a point in time when males become more vociferous with their music consumption appetite and girls less, and this change seems to happen around 18 years-old.
4. Music fandom corresponds strongly with respect for all individuals, which differs greatly to sports fandom in which in-group loyalty is the driver.
The way you cultivate a sports audience differs from the way you cultivate a music audience. In the world of sports, loyalty, which correlates with belief in listening to authority, is a main driver, while in the world of music, the main psychological moral driver is a belief in the reduction of harm to individuals and the increasing care for them, not just those within oneâ€™s own group. This discovery helps to explain the successful fan-artist relationship people such as Lady Gaga possess.Â
5. Ethnicity has no impact on music consumption.
While in the political arena there might not be the post-racial/ethnic world people had hoped for in 2008, in the world of music consumption it has come already! Oneâ€™s race/ethnicity neither increases nor decreases oneâ€™s consumption of music.Â
6. Employment Matters.
As we have seen the cost of concerts increase, the cost of artist memorabilia increase, along with the ways of making these purchases more reliant on access to credit cards, it seems that past notions of music fans being at their consumption peak have moved from the student phases of life (high school/college) to the work phases of life. Being employed full-time (or even part-time) makes you much more likely to have high music consumption.
Major Insights and Implication for Marketing Strategy
While the audience for each artist is different, and we suggest adjusting the model to take that into account, these are the high-level macro-level findings of which all artists and labels should be cognizant:
1. Increasing the share of cognitive users of music in your audience will increase the share of people consuming your music, thus increasing your potential revenue.
2. People who have musical ecosystems among like-minded people are more likely to have heavy music consumption. Rather than simply instituting generic campaigns that just focus on the release of a product (e.g. new album), artists and labels should focus on platforms and programs that foster these ecosystems, which will help lead to long-term success.
3. For artists whose core audience is most likely to be above 18 years-old, it behooves them to have a marketing plan that heavily takes into account males as they are more likely to be heavy consumers of your music. Not only should messaging take into account this gender skew, but media placement and integration should also be in media properties that are popular with males.
4. Supporting a sports team appeals more to oneâ€™s traditional side but supporting a music group or an artist does not anywhere to the same degree. With a sports team, the morality of loyalty plays more of a role in oneâ€™s fandom, but in the case of supporting an artist, the notion of common good has a higher impact. Artists and labels who can appeal to peopleâ€™s better angels are more likely to move their followers from having passive music consumption to active music consumption.
5. When messaging to an audience, while there are some demographics that are still important, race/ethnicity is not one of them. A better marketing plan is one that involves finding the white space that cuts across all people regardless of their racial/ethnic origins. Â
6. Consider the lifestage of your core audience when making marketing plans more than actual age. If you are looking to appeal within the core music buyer group, you should keep in mind that the most fervent fans are possibly more likely to have already moved from their student lifestage and be in their post-college/first job lifestage. Programs and platforms that enhance the experience of that lifestage are more likely to be successful.
Our model was created to understand the independent variables that help predict music consumption, along with predicting how much % change in those independent variables can impact oneâ€™s consumption of music in a way that leads to revenue for an artist, an artistsâ€™ label et al.
In our music consumption battery (see Statistical Procedures 1. Dependent Variable: Music Consumption), there were five statements and a respondent rated each from strongly agree to strongly disagree. We summed up scoring for all 490 respondents and obtained a mean score, being above the mean is classified as having high music consumption; being below the mean is classified as having low music consumption.