Over the past 10 years, fandoms have become the dominant currency in many industries, certainly in Film & TV, but also in Gaming, Sports, Fashion, Tech and now Finance. Their impact will continue to expand to more categories as the key trends that have propelled them to their position today continue to accelerate. In TV, audience communities organized around their interests are proven to be more effective at driving tune-in than any demographic-based group. So why is so much of our marketing still focussed on demographics rather than fandoms? Short answer: demographics are easy, fandoms are difficult, there's no playbook for it. In partnership with Twitter and Samba TV, our Research across 30 TV shows and 6 genres showed that Interest-based communities tune-in at a rate 4x higher than demographic-based communities, and fandom communities tune in at a rate 5x higher. In this talk we’ll discuss the results of the study, analyze how fandom communities drive tune-in and explore the levers at your disposal to optimize your marketing strategy for fandoms, not demographics.

1. Francesco D’Orazio, Founder & CEO, Pulsar
MARKET TO FANDOMS, NOT DEMOGRAPHICS

4. WE HELP GREG READ THE WHOLE INTERNET

5. Web analytics
Social Search
Media
catalyst
upstream
mainstream footprint
“The Attention Trail”
Ad Exposure
Purchase
Viewership
CONVERSIONS

6. OMNI-CHANNEL
LISTENING
AUDIENCE
SEGMENTATION
+

7. AN ORGANISED SUBCULTURE COMPOSED OF
FANS CHARACTERIZED BY A FEELING OF
EMPATHY AND CAMARADERIE WITH OTHERS
WHO SHARE A COMMON INTEREST

8. IDENTIFICATION
They express themselves through the subject
of their fandom

9. MASTERY
They know everything there is to know about the
brand and the product and they take pride in that

10. PRODUCTION
They like to have a say in the building of the
brand and the product and create their own
version of it

11. PARTICIPATION
They like to be part of the brand narrative

12. APPROPRIATION
As they create their own version of the
brand, they start to co-own it with the rest of
the community

18. PLATFORM
RANGE
FREQUENCY
CREATIVITY
DISTRIBUTION
OWNERSHIP
IP
Physical world
Local
Occasional
MakeshiF tools
Limited
No
Threat
FANDOM 1.0
Social Networks
Global
Always on
Repurposed tools
Social Distribution (viral)
No
At war
FANDOM 2.0
Interest Networks
Global
Always on
Purpose-built tools
Interest distribution (tribal)
Yes
Embedded in the IP
FANDOM 3.0

19. THE STUDY
MEASURING THE IMPACT OF FANDOMS

20. 20
30 TV shows across 6 genres
Action Sci-Fi/Fantasy Reality/Competition Drama Comedy AA
The Walking Dead
(Hero show)
The Flash
(Comparison show)
Jack Ryan
Hanna
Mayans M.C.
Westworld
(Hero show)
Carnival Row
(Comparison show)
The Mandalorian
Handmaid’s Tale
Watchmen
The Bachelorette
(Hero show)
Love Island
(Comparison show)
Real Housewives of OC
Survivor
Love is Blind
This is Us
(Hero show)
13 Reasons Why
(Comparison show)
Homeland
Succession
Ozark
The Good Place
(Hero show)
Space Force
(Comparison show)
Brooklyn Nine Nine
It’s Always Sunny in Phila.
Young Sheldon
Black-ish
(Hero show)
High Fidelity
(Comparison show)
Insecure
The Last OG
Power

21. 21
Sample set: audiences mapped for 6 Genres & 12 Hero/Comparison shows
Ac7on Sci-Fi/Fantasy Reality/Competition Drama Comedy AA
The Walking Dead
The Flash
Westworld
Carnival Row
The Bachelorette
Love Island
This is Us
13 Reasons Why
The Good Place
Space Force
Black-ish
High Fidelity
Genres
Hero
Shows
Comparison
Shows

22. 22
Audience shape
Segmentation
Number of communities
Distribution of communities (relative
share of audience)
Personas
Types of communiLes
Male vs. female parLcipaLon
Affinity similarity
Graph analysis
Degree of cohesion vs. fragmentation
(based on metrics such as network
modularity & average path length)
Conversation patterns
Volume
Total volume
Conversation rate (avg. # of tweets
per unique user)
Trend line pattern
Mode of conversation
Share of RTs vs. original tweets
Share of organic conversation vs. tweets
prompted by a marketer
Viewer reaction vs. fan-to-fan engagement
vs. cast engagement, etc.
Substance
Net sentiment
Media in tweet (share of text-only vs.
images, etc.)
Conversion Behaviour
Viewership / Samba TV Panel
Households who watched the program
for at least 5 cumulative minutes within
the L+7 window.
Advertising Exposure / Twitter
Exposure to Twi[er ads

23. THE KEY LEARNINGS

24. LEARNING #1:
THERE ARE 4 TYPES OF TV CONVERSATION PATTERNS,
DRIVEN BY GENRE AND DISTRIBUTION STRATEGY

25. 25
EXTENDED SPIKE
WEEKLY VOLATILITY
ALWAYS-ON
SINGLE SPIKE
Single Spike
A substan)al peak in conversa)on with a very short
lifespan
Extended Spike
A substan)al peak with con)nued momentum of
conversa)on
Always-On
A consistently high baseline volume of conversa)on
Weekly Vola=lity
Volumes spike when on-air and decline when off-air

26. LEARNING #2:
A SHOW AUDIENCE IS NEVER A MONOLITH
BUT ALWAYS A SYSTEM OF COMMUNITIES

27. 27
Size of the segments = proportional to the # of
members in the segment
Size of each circle (nodes) = the # of
interconnections the user has
Lines (edges) = interconnections between
different members
WHO’S DRIVING TV CONVERSATIONS?

28. 28
We ran a custom segmentation on the conversation audience of each show
and genre, identifying a broad range of communities (Hero shows pictured)
Walking Dead Superfans
Comics, Superhero, &
Wrestling Fans
M&E Mainstreamers
Sports Fan Parents
BTS Stans
Trump Supporters
Black Culturists
#Resistance
Progressives
Gamers &
Streamers
Westworld Superfans TV & Movie Buffs
Techies & Software
Engineers
Sweepstakers
Gamers
Black Culturists
Sports Dudes #Resistance
Progressives
Horror & Zombie Fans
Horror & Zombie Fans
TV & Movie Buffs
Sports Dudes
Progressive
News Junkies
The Good Place &
Comedy Superfans
POC & LGBTQ+ Geeks
Anime & Art Gamers
Bookworms
Black Culture Moms
Black Collegiates
M&E Mainstreamers
Entrepreneurs & Creatives
Gay Cullturists
The Good Place Black-ish
Westworld
M&E Mainstreamer Moms
Sports Dudes
Social Celebrity Stans
Tyler Cameron &
Hannah Brown Stans
Bachelor & Bachelorette
Superfans
Southern Moms &
Collegiates
The Bachelorette
The Walking Dead
Progressive Moms
Black Collegiates
Supernatural & YA Girls
TV & Movie Buffs
Jennifer
Morrison Stans
One Direction Stans
Conservative Moms
This is Us
This is Us
Superfan Moms

29. 29
Across the 30 audiences we mapped, we found 90+ discrete
communities; to reduce complexity, we can roll up these communities
into 12 archetypes
Archetype Avg. Share of
Show Audiences
Avg. Share of
Genre
Audiences
Show Superfans 19% 21%
M&E Mainstreamers 13% 20%
Black Culturists 13% 8% ↓
Politicos & News Junkies 10% 14%
Subculturists 10% 8% ↓
Supernatural & Fantasy Fans 9% 14%
Artist & Celeb Superfans 7% 6%
Gamers 8% 14% ↑
TV & Movie Buffs 6% 10%
Sports Fans 3% 9% ↑
LGBTQ+ Culturists 3% 1%
Socialites 1% 4%
Gamers & Comics & Superhero Fans
M&E Mainstreamers
The Walking Dead Superfans
Black Culturist WWE Superfans
#Resistance Progressives
Horror & Zombie Fans
Trump Supporters
Wynonna Earp Superfans
Comics & Supernatural Gamers
TV & Movie Buffs & Creatives
Progressive News Junkies
Bachelorette Superfans & Celeb Stans
Sports Fans & Gamers
Superhero Fans & Gamers
Politicos
Streetwear Fashionistas
Comedy Geeks
Musicophiles
Candice Patton Fans & Stans
Streamer & Youtubers
Podcasters
Supernatural Superfans
TV & Gossip Buffs
Socialite & Streamer Moms
POC & LGBTQ Geeks
Anime & Art Gamers
Bookworms
Black Culture Moms
WWE & Wrestling Fans
Techies & Software Engineers
Sports Fans
Supernatural TV & Movie Buffs
Sample of the 90+ segments identified

30. 30
Archetype | Show Superfans
Top Affinities
(based on % of archetype who follow and uniqueness vs. other archetypes)
Brands &
media
People
Top Bio Keywords
Fan
IG
Music
TV
BLM
Walking Dead
Fan Account
Enthusiast
Recent Hashtags
#Dune
#SweaterWeather
#The100
#SuperGirl
#NamjoonDay
#EnolaHolmes
#TVTime
#Cancelled
Gender
Age
M F
> 45
< 18
Top Locations
Los Angeles, Chicago, New York
• Their defining characteris/c is that their top Twi3er affinity is a par/cular TV
show
• First and foremost, they self-iden/fy as a fan of a par/cular show(s)
16%
40%
7% 8%
14%
10%
24%
19%
33%
0% 0% 0%
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Presence by Show (% of show audience that are Show Superfans)
Presence by Genre (genres with the largest share of Show Superfans)
Reality/Comp., 44%
Comedy, 50% Action, 32%
Anna Kendrick Chrissy Teigen Jimmy Fallon Lin Manuel
Miranda
Brie Larson
Brooklyn 99
NeRlix Marvel NASA Game of Thrones

31. LEARNING #3:
THE SHAPE OF AN AUDIENCE PREDICTS THE PATTERN
OF THE SHOW CONVERSATION

32. Audience Shape falls on a spectrum

33. 33
Fragmented
Audience
Cohesive
Audience
High Conversation
Performance
Low Conversation
Performance
Reality/Comp.
Drama
Sci-Fi/Fantasy
AA
Action
Comedy
- Spread
- Conversation Rate
Conversation Performance
- Modularity
- Avg Path Length
Audience Fragmentation

34. 34
Audience cohesion affects the spread of conversation and content
There is a directional relationship
between audience
cohesion/fragmentation and
conversation performance
(volume/lifespan)
Genres with less fragmented, more
cohesive audiences generate more
conversation volume, particularly
AA & Action.
Genres with more fragmented
audiences see less tweets per user
(Comedy & Drama).
X-axis fragmenta>on value = Modularity x Avg. Path Length

35. LEARNING #4:
THE SHAPE OF AN AUDIENCE SHIFTS OVER TIME

36. 36
For each show audience studied, we analyzed the change in audience
composition from season to season (Hero shows pictured)
Politicos & News Junkies are colored green when representing a progressive group, and red when representing Trump supporters.
Gamers -18%
M&E Mainstreamers -13%
Show Superfans -6%
Supernatural Fans +14%
Subculturists +10%
M&E Mainstreamers -18%
Gamers -17%
Black Culturists +10%
TV & Movie Buffs +8%
Show Superfans +7%
Show Superfans -30%
M&E Mainstreamers -18%
Politicos & News -9%
Celeb Superfans +48%
Sports Fans +5%
Gamers -11%
Politicos & News -5%
TV & Movie Buffs +5%
LGBTQ+ Culturists +4%
Sports Fans +3%
TV & Movie Buffs -22%
Politicos & News -20%
M&E Mainstreamers +14%
Black Culturists +10%
LGBTQ+ Culturists +5%
M&E Mainstreamers -17%
Sports Fans -8%
Show Superfans -7%
TV & Movie Buffs +10%
Politicos & News +9%
The Walking Dead
Season 9 vs. 10
Westworld
Season 2 vs. 3
The Bachelorette
Season 14 vs. 15
This is Us
Season 3 vs. 4
The Good Place
Season 3 vs. 4
Black-ish
Season 5 vs. 6
Most significant community shifts for each show (% = percentage point changes)

37. 37
Number in parentheses (#) denotes the most recent season of the show we’ve studied
Westworld (3)
Black-ish (6)
The Flash (6)
13 Reasons Why (4-Final)
The Walking Dead (10)
Bachelorette (15)
High Fidelity (1-Final)
This is Us (4)
The Good Place (4)
Space Force (1)
Carnival Row (1)
Love Island USA (1)
Change
in
M&E
Mainstreamer
/
Show
Superfan
/
TV
&
Movie
Buff
share
of
audience
+
-
Show Lifespan
Presence of key M&E audience archetypes indicates the position on the
audience lifecycle of the show
👀 A show that’s still finding its audience
🌊 A show that’s cres4ng in popularity
🏄 A show that’s focused on hardcore fans

38. LEARNING #5:
EACH GENRE AND EACH AUDIENCE COMMUNITY
SHOW A UNIQUE CONVERSATIONAL FOOTPRINT

39. 39
54%
30%
25% 28%
55%
31%
46%
70%
75% 72%
45%
69%
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A
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Marketer Mention/RT Organic
49% 47%
37%
42%
55%
47%
51% 53%
63%
58%
45%
53%
Action Sci-Fi/FantasyReality/Comp. Drama Comedy AA
Retweet Original Tweet
46%
53%
63% 64%
54% 50%
Action Sci-Fi/Fantasy Reality/Comp. Drama Comedy AA
Text-only Images Videos Links

40. LEARNING #6:
ACROSS GENRES, FANDOMS DRIVE HIGHER
CONVERSATION RATES THAN ANY OTHER COMMUNITY

41. 41
Across genres, there are three “fandom” archetypes that behave similarly
These archetypes are most prominent within the genres below:
Example: The Bachelorette
Artist & Celeb Superfans, 42%
Example: The Flash
Supernatural & Fantasy Fans, 19%
Example: The Good Place
Show Superfans, 33%
Supernatural & Fantasy Fans
Ac#on & Sci-Fi
Artist & Celeb Superfans
Reality/Competition
Show Superfans
Comedy

42. 42
Audiences featuring fandom communities
show Conversation Rates that are between
2xand 3x
higher than the audiences
where fandoms are absent

43. LEARNING #7:
ACROSS GENRES,
FANDOMS DRIVE HIGHER TUNE-IN BEHAVIOUR

48. SO HOW DO YOU MARKET
TO FANDOMS

49. #2 How fragmented is the audience?
#3 What are the top 10 communities?
#5 Which ones are fandoms?
#6 What is the conversation footprint
for each community?
#7 Where is the show on its audience life cycle?
#1 What is the conversation pattern?

50. The Difference Engine

52. CONCLUSIONS:
FORGET YOUR TARGET AUDIENCE,
GO ALL IN ON FANDOMS

53. Thank you
Francesco D’Orazio, Founder & CEO, Pulsar

54. 54
The critical role of the show or network’s official account
UNIFY CONVERSATION
COMMUNITIES
DIRECT TRAFFIC AMONGST
AUDIENCE
GETTING COMMUNITIES ON THE
SAME PAGE AND INTO A FLOW
ACT AS A CENTER OF GRAVITY
• Practical information: setting expectations about
availability, where to watch, when to watch, how to
get involved
• Signaling that it’s time to start a conversation: by
sharing exclusive content assets (behind the scenes);
or by creating a thread that invites the audience to
discover a second-layer of the narrative, character
backstories, or historical references
• Surfacing content/memes from one community and
introducing it to others (either via promoted or organic
activity)

55. M&E Mainstreamers
• Twitter users with a broad range of media and entertainment interests which are generally accepted as popular or mainstream, and who have a high affinity for major media
outlets.
Show Superfans
• Twitter users who self-identify as fans of a particular show(s) and/or whose defining characteristic is an affinity for a particular TV show.
TV & Movie Buffs:
• Twitter users with deep interests in television and movies, including writers, directors and cinema.
Supernatural & Fantasy Fans:
• Twitter users with interests in science fiction, horror, fantasy, magic realism and young adult content across TV, movies, books and games.
Politicos & News Junkies:
• Twitter users with heavy consumption of news and politics and who show high affinity for politicians.
Artist & Celeb Superfans:
• Twitter users that self-identify as superfans or followers of specific individuals, bands, celebrities or actors.
Gamers:
• Twitter users whose primary activity on the platform centers on Console and PC gaming and its community. The group is inclusive of both competitive and casual gamers.
Black Culturists:
• Twitter users with a high affinity for Black/African American celebrities across various domains such as music, entertainment, sports, beauty and business.
Subculturists:
• Twitter users who belong to an array of niche communities defined by small but thriving groups with discrete interests.
Sports Fans:
• Twitter users whose leading theme in their media diet centers on sports and sports content, and who often self-identify as fans of a particular team or sport.
55
Pulsar Archetype Definitions
55