A data profile of the people who buy, follow and care about Business intelligence tools in United States — modelled from more than twelve digital signal sources. Business intelligence tools has an estimated audience of 262,624 people in United States.
The average Business intelligence tools fan in United States is 36.3 years old, more male, and lives primarily in California.
The audience is concentrated in California, Texas, New York.
Top brand affinities include Kaggle, TensorFlow, Web server, with strongest over-indexing on Kaggle (83.35× the country average).
Demographically, the Business intelligence tools audience skews more male with an average age of 36.3, and over-indexes on personality traits such as Need for Security, Family Orientation.
Compared to the country baseline, this audience shows distinctive patterns across 20 brand affinities and 50 regions tracked by Rascasse.
The typical Business intelligence tools fan in United States is more male, around 36.3 years old, with strong Need for Security tendencies and a notable affinity for Kaggle.
The key figures that characterise the Business intelligence tools profile in United States.
44.3% are female, 55.7% are male, average age 36.3.
| Metric | Value |
|---|---|
| Female | 44.3% |
| Male | 55.7% |
| Average age | 36.3 |
| Estimated audience size | 262,624 |
| Age bracket | Share | % |
|---|---|---|
| 16-19 | 18% | |
| 20-29 | 30% | |
| 30-39 | 24% | |
| 40-49 | 16% | |
| 50+ | 12% |
Where the Business intelligence tools audience in United States is strongest.
| # | Region | Reach | Affinity | × |
|---|---|---|---|---|
| 01 | Washington, District of Columbia | ~2K | 2.15× | |
| 02 | New York | ~20K | 1.58× | |
| 03 | Colorado | ~6K | 1.51× | |
| 04 | Virginia | ~10K | 1.49× | |
| 05 | Illinois | ~10K | 1.46× | |
| 06 | Massachusetts | ~7K | 1.38× | |
| 07 | New Jersey | ~9K | 1.30× | |
| 08 | Georgia | ~10K | 1.27× | |
| 09 | California | ~40K | 1.24× | |
| 10 | Maryland | ~5K | 1.21× | |
| 11 | Washington | ~6K | 1.19× | |
| 12 | Texas | ~30K | 1.17× | |
| 13 | Utah | ~3K | 1.17× | |
| 14 | North Carolina | ~9K | 1.16× | |
| 15 | Connecticut | ~3K | 1.04× | |
| 16 | Oregon | ~3K | 1.03× | |
| 17 | Pennsylvania | ~9K | 1.01× | |
| 18 | Tennessee | ~5K | 1.01× | |
| 19 | Kansas | ~2K | 1.01× | |
| 20 | Minnesota | ~4K | 1.00× | |
| 21 | Missouri | ~4K | 0.99× | |
| 22 | Ohio | ~8K | 0.97× | |
| 23 | Arkansas | ~2K | 0.96× | |
| 24 | Nebraska | ~1K | 0.96× | |
| 25 | New Hampshire | <1K | 0.96× | |
| 26 | Vermont | <1K | 0.96× | |
| 27 | Florida | ~20K | 0.95× | |
| 28 | Rhode Island | <1K | 0.95× | |
| 29 | Delaware | <1K | 0.95× | |
| 30 | Alaska | <1K | 0.94× | |
| 31 | Michigan | ~6K | 0.93× | |
| 32 | Indiana | ~4K | 0.93× | |
| 33 | Idaho | ~1K | 0.93× | |
| 34 | North Dakota | <1K | 0.93× | |
| 35 | Arizona | ~5K | 0.92× | |
| 36 | Kentucky | ~3K | 0.92× | |
| 37 | South Dakota | <1K | 0.92× | |
| 38 | Iowa | ~2K | 0.90× | |
| 39 | Montana | <1K | 0.90× | |
| 40 | Wisconsin | ~4K | 0.89× | |
| 41 | Maine | <1K | 0.89× | |
| 42 | Hawaii | <1K | 0.88× | |
| 43 | South Carolina | ~3K | 0.87× | |
| 44 | Oklahoma | ~3K | 0.87× | |
| 45 | West Virginia | ~1K | 0.85× | |
| 46 | Alabama | ~3K | 0.84× | |
| 47 | New Mexico | ~1K | 0.84× | |
| 48 | Nevada | ~2K | 0.83× | |
| 49 | Mississippi | ~2K | 0.83× | |
| 50 | Louisiana | ~3K | 0.80× |
The strongest cross-interests of the Business intelligence tools audience — brands, topics and people combined.
| # | · | Interest | Category | Affinity | × |
|---|---|---|---|---|---|
| 01 | TensorFlow | Technology & Electronics | 123.52× | ||
| 02 | Kaggle | Technology & Electronics | 83.35× | ||
| 03 | MongoDB | Technology & Electronics | 47.95× | ||
| 04 | Amazon Web Services | Technology & Electronics | 20.00× | ||
| 05 | Business intelligence | Business & Career | 20.00× | ||
| 06 | Massive open online course | Business & Career | 20.00× | ||
| 07 | Data visualization | Technology & Electronics | 20.00× | ||
| 08 | Microsoft Azure | Technology & Electronics | 20.00× | ||
| 09 | Germany national football team | Sports | 20.00× | ||
| 10 | Faye Dunaway | Movies & TV | 20.00× | ||
| 11 | Data science | Business & Career | 19.28× | ||
| 12 | FIFA Club World Cup | Sports | 15.63× | ||
| 13 | Dustin Hoffman | Movies & TV | 14.69× | ||
| 14 | Web server | Technology & Electronics | 13.44× | ||
| 15 | Dropbox (service) | Technology & Electronics | 12.22× | ||
| 16 | Statistics | Business & Career | 8.68× | ||
| 17 | Robert Redford | Movies & TV | 6.72× | ||
| 18 | Internet & Social Media | 6.17× | |||
| 19 | Innovation | Business & Career | 5.65× | ||
| 20 | Planet Fitness | Sports | 2.90× |
Values above 1.00× are above the country average, values below 1.00× below it.
| Trait | Cluster | Deviation | Score |
|---|---|---|---|
| Need for Security | CONSERVATISM | 5.37× | |
| Family Orientation | CONSERVATISM | 2.32× | |
| Career Orientation | POWER | 2.12× |
| Trait | Cluster | Deviation | Score |
|---|---|---|---|
| Pet Ownership | JOY | 0.67× | |
| Extroversion | THRILL | 0.70× | |
| Creativity | OPEN | 0.77× |
Business intelligence tools has an estimated audience of 262,624 people in United States, concentrated in California and Texas.
44.3% of Business intelligence tools fans are female, 55.7% are male, with an average age of 36.3 years.
Business intelligence tools fans show strongest brand affinity for Kaggle (83.35×), TensorFlow (123.52×), and Web server (13.44×) over the country average.
Business intelligence tools fans in United States are most concentrated in California (reach ~40K), Texas (reach ~30K), and New York (reach ~20K). These three regions account for the largest share of the active audience.
Beyond Business intelligence tools itself, the audience over-indexes on TensorFlow (123.52×), Web server (13.44×), Data science (19.28×), and MongoDB (47.95×) compared to the United States average.
Related profiles, rankings and the same audience in other markets.
Audience size is the estimated number of people in United States who actively search for Business intelligence tools. Affinity is an over-index ratio: 2.0× means the audience is twice as likely to engage with that brand or trait as the country average. Reach is the estimated number of audience members in a region. Regional and brand-affinity tables are sorted from strongest signal to weakest.
This audience profile is generated by Rascasse from anonymized search-behavior signals across United States. For methodology see methodology. Affinity values are over-index ratios vs. the country average (1.0 = baseline). Audience sizes are estimated, not measured.
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