NFL audience

Role

Innovation Strategy

Agency

AAF MSU

Highlights

Innovate quantitative and qualitative analysis through synthetic persona infrastructure.

Tools

Qualtrics. Claude. Python. Streamlit. Figma. NotebookLM

Date

2026

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NFL Audience Design · Part 1

The Brief Challenge

Who is a
casual fan?

The NFL brief named the target as casual fans. The research turned that label into three behavioral profiles a creative team could write to.

Survey responsescleaned & analyzed

In-depth interviewsqual & quant coded

Synthetic personasbuilt to be talked to

casual
fan

/ˈkaʒ(u)əl fæn/

n. as received

"Fans with lower engagement levels and potential for increased fandom. Individuals who have some connection to the NFL but are not yet deeply invested in the league or its programs."

Research output · encoded

k-means · n=934

Revised Entry

Three distinct behavioral groups inside this term.

Disengaged Fan

Football isn't on their radar, so the way in is the social world already built up around it, not the game itself.

Engaged Skeptic Fan

High fan level, low institutional trust, so proof moves them more than any announcement about how much the NFL cares.

True Believer Fan

Already sold and ready to act, so the only job left is making the next step take thirty seconds.

Survey DesignOLS RegressionK-Means ClusteringDecision TreeQualtricsNotebookLMStreamlitClaude APIMachine LearningFigmaSynthetic PersonasFan SegmentationSurvey DesignOLS RegressionK-Means ClusteringDecision TreeQualtricsNotebookLMStreamlitClaude APIMachine LearningFigmaSynthetic PersonasFan Segmentation

How We Asked

Questions

Variables captured

Dimensions

935

Clean observations

Platform

Qualtrics professional survey

Timeline

Sep–Nov 2025

Target

Michigan State University community

Initial responses

1,437 · 935 after quality control

Target Variable

interest_level (1–10 scale)

NFL Perception & Values

7 Likert scales

Community care, player credibility, social issues, health support, values alignment

Content Consumption

2 ordinal scales

Weekly frequency, likelihood to watch next game

Personal Connection

3 binary

Favorite team, favorite player, neither

Program Awareness

7 binary

Play 60, NFL Flag, Inspire Change, and related initiatives

Engagement Drivers

9 binary

Content preferences: inspirational, youth, community, highlights, etc.

Demographics

11 variables

Age, gender, race, geography, parental status

In-Depth Interviews · 51

"You can just tell when a brand is genuine. Right off the rip. You can tell they don't really know the audience they're trying to reach."

Maya, 22

"I don't pay attention to their messages. You watch the game and you get over it. I don't know what they stand for."

Jordan, 21

"I would be more involved if it appealed more to females. But it really doesn't. I feel like it's not geared towards females."

Marie, 54

NotebookLMFigmaQual Coding

Focus Groups · 7

Focus groups surfaced something individual interviews cannot: how people perform their relationship with football when others are in the room. Social dynamics shift the answers in ways that make the findings richer and more honest.

Gen Alpha · Methodological Note

Under-13 respondents required parental consent and supervised conditions. Supplemented with secondary data from Mintel and MRI-Simmons to validate Gen Alpha media consumption and youth sports engagement patterns.

Mintel MRI-Simmons Supervised IDIs

What the Data Said

The gap isn't
in their heads.

Women don't distrust the NFL more than men. They just see it less.

Distribution by Generation

Gen Z

434

Millennial

219

Gen X

109

Boomer+

Distribution by Gender

Male

389

Female

529

Young, female-skewed, and racially homogeneous.

Gen Z, Millennial, and female signal is solid, but the sample skews white, so conclusions about Black and Hispanic fan experiences need more validation.

→ Reliable signal for Gen Z and female targeting

Correlation Matrix · Key Variables

Age

Fan Level

NFL Cares

Credibility

Content Freq

Age

1.00

0.09

0.03

0.06

−0.17

Fan Level

0.09

1.00

0.50

0.39

0.59

NFL Cares

0.03

0.50

1.00

0.54

0.29

Credibility

0.06

0.39

0.54

1.00

0.24

Content Freq

−0.17

0.59

0.29

0.24

1.00

Content frequency is the linchpin variable.

Content frequency is the strongest predictor of engagement at r=0.59, and trust metrics compound, so losing credibility in one area drags the others down with it.

→ More touchpoints = higher engagement

The gender gap is behavioral, not perceptual.

Women don't distrust the NFL more than men, they just see it less, which makes this a distribution problem, not a persuasion problem.

→ Meet them where they are

OLS Regression · Women's NFL Interest (n=454)

59.7%

R²: model explains 59.7% of variance

What drives women's interest in the NFL?

Watchability of content

39%

NFL community care belief

24%

Content frequency in feed

23%

Player credibility

14%

Decision Tree · High-Intent Fan Identification

Golden Cohort Criteria

Fan_Level > 9.5
Age ≤ 27.5
Content_Freq > 4.5

70.7%

High-intent probability · n=75

Low content frequency collapses high-intent probability to 32.1% regardless of fan level or age, so feed presence matters more than enthusiasm when allocating media budget.

→ Feed frequency predicts conversion

Impact Simulation · What drives casual fan growth?

Baseline

5.76

+ Trust Boost

5.86

+ NFL Cares

6.02

+ Content Freq

6.32

+ Attention ↑

7.15

Predicted fan level · Scale 1–10

Attention is the multiplier.

Attention is the highest-return variable, a one-point increase predicts fan level 7.15 versus 5.86 for trust-first approaches, so earn attention before anything else.

→ Lead with entertainment. Embed purpose.

Barrier ROI Analysis

▲ +0.003 Hard to Watch (access)
▲ +0.003 Rules Confusing (education)
▼ −0.004 Cost (price sensitivity)
▼ −0.005 No Time (scheduling)

Invest in accessibility and education. Price sensitivity is a stated rather than actual barrier for most respondents.

NFL Audience Design · Part 2

Team Exploration · ML Quiz

Can machine learning
classify a fan?

During the exploratory phase, before strategy had crystallized, I built a quiz as a shared reference point that aligned how the whole team thought about the audience.

Central Question

Can machine learning help classify fan engagement levels to enable personalized program messaging?

ML Pipeline

Data Collection

→

Data Cleaning

→

Schema Validation

↓

Feature Engineering

←

Train-Test Split

←

Normalization

↓

Model Evaluation

←

Model Building

←

Feature Selection RFE

↓

FastAPI

→

Streamlit

→

Final Web App UI

Live Demo · nflfantype.streamlit.app

Try the live quiz

Audience Persona

↑ True Believers cluster

Couch Coordinator · 40 yrs · Gen X

Lions season ticket holder since '08. Two kids in NFL FLAG. Wants programs to work, not to be sold.

Proud DadSunday FanPragmatist

He'd do it. He's not resistant, he's just busy. Make the path short enough to complete from his couch during the Lions game and he's in.

↑ Engaged Skeptics cluster

GDG

Game Day Girly · 22 yrs · Gen Z

Came to football through tailgate culture. Hosts game day every Sunday. Has very specific opinions about the halftime show.

Tailgate PlannerAuthenticatorValues-Driven

She's got a sixth sense for when something's been approved by a committee. NFL messaging that reads like marketing copy gets scrolled past in under a second.

↑ Disengaged cluster

Tiny Teammate · 12 yrs · Gen Alpha

Didn't care about football. Joined NFL FLAG to hang with friends. Loves it now because of the team, not the game.

Social TeammateFootball CuriousMom Decides

Sports content just isn't written for her. The door in is the friendships, not the game.

Audience Design as Infrastructure

Personas you can
talk to.

Most agencies put personas on a slide and leave them there. These are AI-powered and grounded in all three layers of triangulated research. Drop in a tagline, upload a concept, describe an activation and they respond the way the actual audience would.

Focus Group Recording

NFL Synthetic Focus Group

🧒🏽 Tiny Teammate

👩🏾 Game Day Girly

👨🏻 Couch Coordinator

What do you think of this poster? Kids playing flag football under stadium lights.

🧒🏽

TINY TEAMMATEooh the lights are sooo cool
but like why is everyone so serious
my team is always laughing and being silly
if they were actually having fun i would show Ava this fr 😭

What if we added a trending sound?

🧒🏽

TINY TEAMMATEWAIT YES
if it had that sound everyone is using rn
idk what its called but u know the one
my mom would still have to approve it tho lol

Does this tagline work? "Everyone belongs in the huddle."

👩🏾

GAME DAY GIRLYok wait
this is actually giving something
"huddle" is specific enough to feel real but open enough to not require football knowledge
ngl if this had the right casting behind it i would screenshot it

Who would you want to see in it?

👩🏾

GAME DAY GIRLYreal people not models 💀
the girl doing tailgate videos, the dad at his kid's first game
shoot it on an iphone in natural light and it's a whole different thing
the produced look is what makes it feel fake fr

Here's the Play 60 program overview: two kids running drills. Would you sign your kid up?

👨🏻

COUCH COORDINATOROk this is clean. I get what it's saying. But where do I actually go? That's the piece that's missing. A dad sees this during halftime, thinks "huh, maybe." Then forgets by the third quarter if there's no next step.

What would make you actually click or call?

👨🏻

COUCH COORDINATORShow me a real coach. Not an actor. Also: is it on Saturdays? I already got soccer. If it fits the schedule I'd actually talk to my wife about it. That's how it works.

Sample exchanges · AI-powered with web search · Grounded in 934 survey responses + 51 interviews

NFL audience

Who is acasual fan?

The gap isn'tin their heads.

What drives women's interest in the NFL?

Can machine learningclassify a fan?

Personas you cantalk to.

the insights

THE IDEA

STATIC

experientials

Commercial

AD TESTING

THE AAF MSU CREW

the insights

THE IDEA

STATIC

experientials

Commercial

AD TESTING

THE AAF MSU CREW

the insights

THE IDEA

BRAND DESIGN

STATICS

BRANDING MERCH

OUT-OF-HOME

SOCIAL

EXPERIENTIAL

the insights

STATICS

ACTIVATIONS

Branding

inspiration

TYPOGRAPHY

Color palette

Logo Process

MOBILE APP

KEY VISUALS

BOOKMARK ORIGAMI

AR EXPERIENCE

print ad

BREWING IDEAS...

Who is a
casual fan?

The gap isn't
in their heads.

Can machine learning
classify a fan?

Personas you can
talk to.