Tokio Hotel has an estimated audience of 2M people in Germany.
The average Tokio Hotel fan in Germany is 40.5 years old, more female, and lives primarily in Nordrhein-Westfalen.
By number of fans, Tokio Hotel ranks #11 among the 4413 objects in Band in Germany — 2.4× the group median.
Women make up 63.7% of the fan base, 14.1 percentage points more than the group average.
Compared with the other 4412 objects in Band, Tokio Hotel fans stand out for their interest in Moony, Kaulitz & Kaulitz and Pretzel.
Most fans live in Nordrhein-Westfalen, Bayern, Baden-Württemberg.
Top affinities include Moony, Kaulitz & Kaulitz, Pretzel, with strongest over-indexing on Moony (55× the country average).
Demographically, the Tokio Hotel audience skews more female with an average age of 40.5, and over-indexes on personality traits such as Price Sensitivity, Sports Activity.
The typical Tokio Hotel fan in Germany is more female, around 40.5 years old, with strong Price Sensitivity tendencies and a notable affinity for Moony.
63.7% are female, 36.3% are male, average age 40.5.
| Metric | Value |
|---|---|
| Female | 63.7% |
| Male | 36.3% |
| Average age | 40.5 |
| Estimated audience size | 2M |
| Age bracket | Share | % |
|---|---|---|
| 16-24 | 18% | |
| 25-34 | 20% | |
| 35-44 | 18% | |
| 45-54 | 23% | |
| 55+ | 21% |
of the worldwide Tokio Hotel audience comes from Germany.
| Country | Share |
|---|---|
| Germany | 20.8% |
| United States | 10.5% |
| Brazil | 9.0% |
| # | Region | Reach | Affinity | × |
|---|---|---|---|---|
| 01 | Sachsen-Anhalt | ~60K | 1.22× | |
| 02 | Sachsen | ~100K | 1.07× | |
| 03 | Schleswig-Holstein | ~80K | 1.06× | |
| 04 | Niedersachsen | ~200K | 1.05× | |
| 05 | Hamburg | ~50K | 1.05× | |
| 06 | Nordrhein-Westfalen | ~500K | 1.04× | |
| 07 | Berlin | ~90K | 1.04× | |
| 08 | Brandenburg | ~70K | 1.04× | |
| 09 | Thüringen | ~50K | 1.04× | |
| 10 | Bayern | ~300K | 0.99× | |
| 11 | Mecklenburg-Vorpommern | ~40K | 0.97× | |
| 12 | Baden-Württemberg | ~300K | 0.94× | |
| 13 | Hessen | ~100K | 0.94× | |
| 14 | Rheinland-Pfalz | ~90K | 0.93× | |
| 15 | Bremen | ~10K | 0.86× | |
| 16 | Saarland | ~20K | 0.82× |
| # | · | Interest | Category | Affinity | × |
|---|---|---|---|---|---|
| 01 | Moony | Music & Radio | 55.00× | ||
| 02 | Kaulitz & Kaulitz | Movies & TV | 47.56× | ||
| 03 | Pretzel | Food & Beverages | 45.21× | ||
| 04 | Johnny Galecki | Movies & TV | 42.56× | ||
| 05 | BorgWarner | Cars & Mobility | 35.59× | ||
| 06 | Tom Kaulitz | Music & Radio | 25.03× | ||
| 07 | Kaulitz Hills | Movies & TV | 24.77× | ||
| 08 | hannah montana | Movies & TV | 20.63× | ||
| 09 | Rose McGowan | Movies & TV | 16.33× | ||
| 10 | High School Musical | Movies & TV | 14.27× | ||
| 11 | Hyundai Ioniq | Cars & Mobility | 12.16× | ||
| 12 | WALL-E | Movies & TV | 11.73× | ||
| 13 | Finding Nemo | Movies & TV | 7.60× | ||
| 14 | Ratatouille (film) | Movies & TV | 7.21× | ||
| 15 | Jennifer Lopez | Music & Radio | 6.42× | ||
| 16 | Olivia Rodrigo | Movies & TV | 5.38× | ||
| 17 | Angelina Jolie | Movies & TV | 4.95× | ||
| 18 | Checker Tobi | Movies & TV | 3.64× | ||
| 19 | Heidi Klum | Fashion & Accessoires | 2.51× | ||
| 20 | McDonald's | Food & Beverages | 1.52× |
| Trait | Cluster | Deviation | Score |
|---|---|---|---|
| Price Sensitivity | PREMIUM | 1.24× | |
| Sports Activity | POWER | 1.10× | |
| Healthy Lifestyle | BALANCE | 0.92× |
| Trait | Cluster | Deviation | Score |
|---|---|---|---|
| Career Orientation | POWER | 0.43× | |
| Individualism | JOY | 0.53× | |
| Quality Awareness | PREMIUM | 0.55× |
Cite as: “Rascasse Solution, Q3/2026, rascasse.com/explore/de/tokio-hotel-16200” · Methodology