July 2024
What was measured
We analyzed the top 1000 Belgian TV, Online, and Print advertisements from July 2024 ranked by media investment. We extracted 1443 faces of talent from these ads and mapped the representation of age, gender, and ethnicity using an image analysis algorithm and human quality control. "Talents" refer to actors, models, and depicted persons in advertisements.
Channel | Number of assets | Number of talents |
---|---|---|
Television | 514 | 1068 |
Online Ads | 59 | 165 |
427 | 279 | |
Total | 1000 | 1443 |
Remark: Some talents will appear in ads on multiple channels, therefore the total of all channels is not the sum. The total of all channels is the number unique talents across all channels.
Age representation
In this chart we see the visual age distribution of talents featured in the Top 1000 ads, compared to the age of the Belgian population (green area),
The visual age distribution is centered around age group 25-34, good for 37% of talent. In the last 3 months we’ve seen the proportion of this group increase gradually. The next two age groups are 35-44 and 18-24, good for 20% and 16% of all talent respectively. Age group is 45-54 and -18 account for 10% and 9% of talent respectively.
Talents looking 45 and above account for only 18% of talents, while they represent 46% of the population and 53,5% of buying power.
Age distribution of casting in Top 1000 Ads compared to Belgian Population
Age by media
Online ads feature the youngest talent with over 44% of talent visually aged 24-34. As in previous months, Print ads shift towards older talent with all ages above 35 being represented more than in other channels. Talent looking 45 and above account for 30% in Print ads and only 10% on Online ads, which is lower than in previous months.
Online
Television
Gender representation
Gender isn't simply a binary attribute determined by visual appearance. Our model, however, uses facial features to determine whether a person looks male or female.
Across the Top 1000 ads, we find 49% male talents and 51% female talents.
Visual Gender distribution of talent in Top 1000 Ads
Gender by media
Unlike previous months where Online and TV Ads would portray more female talent than male talent, we have now virtually an equal proportion of female/male representation across all channels.
Online
Television
Gender x Age
Female talents are younger than male talents when we cross visual age and visual gender. Under the age of 25 we see more female talent, over the age of 45 we see less female talent in the Ads. We observe this trend month after month.
Age | Male | Female | Difference F-M/F+M |
---|---|---|---|
65+ | 1% | 1% | 0% |
55-64 | 5% | 1% | -67% |
45-54 | 6% | 4% | -20% |
35-44 | 10% | 9% | -5% |
25-34 | 18% | 19% | 3% |
18-24 | 5% | 11% | 38% |
-18 | 3% | 6% | 33% |
Visual Gender crossed with visual age of talent in Top 1000 Ads
Ethnic representation
According to the analysis, 83% of talents are perceived as White (57% White + 26% Mediterranean White/Middle Eastern) compared to 17% non-White. Black talent makes up 9% of depicted persons, while Asian talent makes up 5%. This is in line with previous months.
Based on facial features, the data model predicts the likelihood that a talent belongs to one of the ethnic/race groups. Due to the fact that there are no hard boundaries between ethnic/race groups, a talent can be perceived as having a dominant and a secondary ethnicity/race.
In addition to White (lighter) and Mediterranean White/Middle Eastern (darker), the model detects Black, Asian, South Asian (e.g. India, Pakistan) and Latine/Hispanic looking people.
Visual Ethnicity distribution of talent in Top 1000 Ads
Ethnicity by media
Overall, TV and Online ads display the most ethnic diversity, while print ads show the least.
Online
Television
Representation of Disability
Along with demographic representation, our image analysis algorithm detects visually detectable disabilities, including wheelchairs, mobility aids, canes, and prosthetic limbs.
This month, we identified six brands featuring people with disabilities, an increase from previous months, due to the upcoming Paralympics. AB InBev, Orange, and Samsung showcased athletes with disabilities, while Rexona and Carglass included people with disabilities without focusing on their disability. Additionally, Aviq (Agence wallonne pour une vie de qualité) ran an awareness campaign for service dogs.
Comparing sectors
Age representation per sector
The Media and Publishing, Tourism and Culture, and Health and Pharma sectors display the most age diversity, meaning they represent a broad range of age groups. As shown in the Media and Publishing chart below, the representation of all age groups—except those under 18 and over 65—is closely aligned with the general population.
As in previous months, the Beauty and Hygiene sector continues to emphasize the idea that youth is aspirational, even for older audiences. Automotive and Transportation, which previously ranked high for age diversity, has now dropped to the bottom of age-diverse advertising sectors. Similarly, Telco and Energy show limited age diversity, as seen in the chart. This is because, in July, many youth-focused telco brands were advertising to their target audience. This highlights that diverse representation isn't a rigid rule; brands should reflect diversity within their target audience rather than diversity for diversity's sake.
Sectors showing the most age diversity in their ads
Rank | Sector | Diversity score | % 45+ |
---|---|---|---|
1. | media and publishing | 76 | 33% |
2. | tourism and culture | 71 | 12% |
3. | health and pharma | 70 | 31% |
Sectors showing the least age diversity in their ads
Rank | Sector | Diversity score | % 45+ |
---|---|---|---|
8. | beauty and hygiene | 57 | 10% |
9. | automotive and transportation | 57 | 5% |
10. | finance and insurance, telco and energy | 55 | 7% |
Charts comparing age diversity in the most and least age diverse sector
Gender representation per sector
The Food and Drinks, Distribution and Retail, and Toys and Events sectors show a perfect balance between female and male representation. Last month, the Toys and Events sector had a noticeable male skew due to the European Football Championship, which featured many ads centered around football players. However, this month, with ads focusing on music events, movies, and theatre shows, the gender balance has returned to normal.
Sectors showing the most gender diversity in their ads
Rank | Sector | Diversity score | % Female |
---|---|---|---|
1. | food and drinks | 50 | 51% |
2. | distribution and retail | 50 | 52% |
3. | toys and events | 50 | 47% |
Sectors showing the least gender diversity in their ads
Rank | Sector | Diversity score | % Female |
---|---|---|---|
9. | health and pharma | 47 | 60% |
10. | tourism and culture | 42 | 67% |
11. | beauty and hygiene | 38 | 71% |
Charts comparing gender diversity in the most and least gender diverse sector
Ethnic representation per sector
As we've mentioned before, diverse representation is often one-dimensional. Case in point is the Beauty and Hygiene sector, which is the least diverse in terms of age and gender, but one of the most diverse in terms of ethnicity. Food and Drinks brands often use internationally produced ads, which tend to feature a broader range of ethnic diversity. Like in the previous month, Belgian Telco and Energy brands are also doing a good job representing ethnical diversity.
In line with previous months, Event ads, coming mainly from Media brands, are the least ethnically diverse.
Sectors showing the most ethnic diversity in their ads
Rank | Sector | Diversity score |
---|---|---|
1. 2. |
food and drinks, telco and energy |
63 |
3. | beauty and hygiene | 60 |
Sectors showing the least ethnic diversity in their ads
Rank | Sector | Diversity score |
---|---|---|
9. | cleaning products | 48 |
10. | health and pharma | 46 |
11. | toys and events | 28 |
Charts comparing ethnic diversity in the most and least ethnic diverse sector
Methodology
If you have questions about the methodology or the technology used to creat the Belgian Ad Diversity Barometer, check our methodology page.