Rascasse Audience Intelligence

CNN Audience Demographics in United States

CNN has an estimated audience of 99.6M people in United States.

#1among News in United States
#1among TV channels in United States#1in News

The average CNN fan in United States is 44.1 years old, balanced, and lives primarily in California.

By number of fans, CNN ranks #1 among the 776 objects in News in United States — 61.1× the group median.

Its fans are 1.5 years older than the group average of 42.6.

Women make up 50.4% of the fan base, 5.8 percentage points fewer than the group average.

Compared with the other 775 objects in News, CNN fans stand out for their interest in Hakeem Jeffries, Democratic Underground and CNN Newsroom.

Most fans live in California, New York, Florida.

Top affinities include Hakeem Jeffries, Democratic Underground, Google News, with strongest over-indexing on Hakeem Jeffries (3.7× the country average).

Demographically, the CNN audience skews balanced with an average age of 44.1, and over-indexes on personality traits such as Need for Security, Patriotism.

The typical CNN fan in United States is balanced, around 44.1 years old, with strong Need for Security tendencies and a notable affinity for Hakeem Jeffries.

Category: News · Type: TV Channel · Subtype: News

Data status: Q3/2026 · Source & method

Section 01

At a glance

Audience size
99.6M
in United States
Gender
50.4%♀
49.6% male
Age
44.1
average years
Country rank
#77
among all objects in United States
Fig. 01

Search interest · 12-month trend

-29%
vs. last year
JanMarMayJulSepNov
Monthly searches · Source: Rascasse Solution
Section 02

Audience demographics of CNN

50.4% are female, 49.6% are male, average age 44.1.

Fig. 02

Gender split

50.4%
Female
49.6%
Male
Demographic split for CNN audience in United States
MetricValue
Female50.4%
Male49.6%
Average age44.1
Estimated audience size99.6M
Fig. 03

Age distribution

Ø 44.1
average years
Age distribution of the CNN audience in United States
Age bracketShare%
16-2413%
25-3415%
35-4419%
45-5424%
55+30%
Fig. 04

Worldwide distribution

51.8%

of the worldwide CNN audience comes from United States.

Worldwide audience distribution share by country for CNN
CountryShare
United States51.8%
Canada7.9%
China3.2%
Section 03
Affinity (×) = how much more likely a member of this audience is to live in a region than the United States average. Example: 2.0× means twice as concentrated as the national baseline.

Geography

Fig. 05

Top regions by affinity

CNN fans by region: top regions in United States
#RegionReachAffinity×
01Vermont~300K1.80×
02Maine~600K1.60×
03New Hampshire~600K1.46×
04Minnesota~2.5M1.38×
05Massachusetts~3M1.35×
06Connecticut~1.5M1.32×
07Virginia~3.5M1.30×
08Oregon~1.5M1.30×
09Washington, District of Columbia~300K1.27×
10Maryland~2.5M1.26×
11Rhode Island~400K1.24×
12Washington~2.5M1.20×
13Wisconsin~2M1.19×
14Colorado~2M1.18×
15Delaware~300K1.15×
16Pennsylvania~4.5M1.14×
17Iowa~1M1.09×
18New Mexico~700K1.09×
19Montana~300K1.08×
20North Carolina~3.5M1.04×
21Alaska~200K1.02×
22Hawaii~400K1.01×
23New Jersey~3M1.00×
24Michigan~3M0.98×
25Nebraska~600K0.96×
26Illinois~3.5M0.94×
27Ohio~3.5M0.94×
28New York~5.5M0.92×
29Missouri~1.5M0.92×
30Arizona~2M0.91×
31South Dakota~200K0.91×
32Idaho~500K0.90×
33Kansas~800K0.88×
34West Virginia~500K0.87×
35Florida~5.5M0.85×
36South Carolina~1.5M0.85×
37California~10M0.84×
38Georgia~3M0.84×
39Tennessee~2M0.82×
40Indiana~1.5M0.79×
41Kentucky~1M0.79×
42Nevada~800K0.78×
43North Dakota~200K0.76×
44Utah~700K0.72×
45Texas~4.5M0.65×
46Oklahoma~700K0.64×
47Alabama~900K0.63×
48Arkansas~600K0.62×
49Louisiana~800K0.57×
50Mississippi~400K0.50×
Fig. 06

Affinity by region

Affinity by region — CNN, United States
0.50×1.00×1.80×
Section 04
Brands and objects ranked by affinity with this audience. Values above 1.0× mean over-representation compared with the country average.

Audience interests & affinities

Fig. 07

Top cross-interests, ranked by affinity

Affinities of the CNN audience vs. the country average
#·InterestCategoryAffinity×
01Hakeem JeffriesPolitics & Society3.70×
02Democratic UndergroundPolitics & Society3.68×
03Google NewsNews3.38×
04CNN NewsroomMovies & TV3.06×
05Lindsey GrahamPolitics & Society2.79×
06Joe BidenPolitics & Society2.62×
07LabCorpHealth2.62×
08Dick CheneyPolitics & Society2.57×
09The Washington PostNews2.49×
10Nancy PelosiPolitics & Society2.43×
11United States SenatePolitics & Society2.28×
12CBS NewsNews2.26×
13MontanaTravel & Leisure2.18×
14Thomas MassiePolitics & Society1.96×
15Melania TrumpPolitics & Society1.91×
16Ivanka TrumpPolitics & Society1.78×
17Native american culture in the united statesPolitics & Society1.73×
18Barack ObamaPolitics & Society1.63×
19Quest DiagnosticsHealth1.61×
20Google DriveTechnology & Electronics1.52×
Section 05
Strongest and weakest personality traits of this audience (1.0 = country average).

Personality of the CNN audience

Fig. 08

Deviation from the national baseline

↑ What stands out
The strongest tendencies
Personality traits of the CNN audience vs. the country average · What stands out
TraitClusterDeviationScore
Need for SecurityCONSERVATISM1.33×
PatriotismCONSERVATISM1.27×
Career OrientationPOWER1.08×
0×1.00× baseline2×
↓ Rather not
The weakest tendencies
Personality traits of the CNN audience vs. the country average · Rather not
TraitClusterDeviationScore
ExtroversionTHRILL0.62×
Design AffinityPREMIUM0.69×
SustainabilityBALANCE0.70×
0×1.00× baseline2×
Appendix

Explore more audiences

More News audiences in United States

Source & method

Source
Rascasse Solution, own modelling
What “fans” means here
Estimated number of people in United States with measurable interest in CNN over the last 12 months. Modelled, not counted; people interested in several tv channels count for each of them.
Data basis
Anonymised behavioural signals: search demand, social media signals, sponsorship and event data. Not a survey.
Period
10/2025 – 09/2026 · updated quarterly · data status Q3/2026
Confidence
high gender and age data available and an audience of at least 100,000 people

Cite as: “Rascasse Solution, Q3/2026, rascasse.com/explore/us/cnn-14809” · Methodology