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Audience Development
Brooklyn Nets
Presenters:
Jane Boon, Haoxi Huang
Hongyuan Lin, Zhenyang Wang
Brooklyn Nets Audience: On TV and Online
Local Television Deals:
Brooklyn Nets – $20M/yr
NY Knicks - $100M/yr, 2016
LA Lakers –$200M/yr (20 years)
On Twitter:
@BrooklynNets – 599K Followers
@NYKnicks – 1.29M Followers
@Lakers - 4.55M Followers
Source: Google Trends, November 2015
Developing a Local Audience via Social Media
Basketball and Social Media
• NBA fans are younger, more diverse, and more attuned to social media than any
other sports fans
• 5 of the 10 most Tweeted sporting events in 2013 were NBA games (Nielsen)
• Twitter is the social media platform of choice for basketball fans
The challenge: Brooklyn Nets and Twitter
• How do the Nets fans feel about their team, and are they open to cultivation?
• Are there Twitter assets and influencers the Nets can leverage better?
• Are there geographic trends that can be exploited by the Nets for revenues?
• Are there pockets of interest that can be pursued to develop new fans for the team?
• How can the Nets engage and delight their audience, consistently and effectively?
Twitter Crawling with Expanded Python Code
Capturing - Text, Twitter Handle, Retweets, Likes
Fan - Identification and Demographics
Goal: Capture information about Twitter users
- Python Twitter crawling code was expanded for our needs
- Identify number of followers, Location
Measuring Tweet Relevance
Twitter user from prior slide - we are tracking his tweets for retweets and likes
#Nets is the keyword used
Twitter Influence and Engagement
Followers - we count as a measure of influence
Retweets - we capture the originator of the tweet
The Nets - Who are the Nets followers/fans?
Team fans/followers were analyzed
Demographics of Nets Followers on Twitter
Demographic Profile #Nets #Lakers
Gender (% Male) 84.7% 74.9%
Median Age 24.0 23.8
Median Income $35,100 $26,100
Race - White/Caucasian
•African American
•Hispanic
63.3%
24.3%
10.8%
43.8%
36.4%
18.5%
Occupations - Students
•Journalists
•Authors/Writers
•Musicians
•Senior Managers
•Other (notable differences)
20.7%
14.4%
10.4%
7.7%
6.3%
Entrepreneurs (4.5%)
18.9%
10.4%
7.8%
8.1%
7.5%
Artists (4.2%), Actors (3.9%)
Source: Demographics Pro, November 13, 2015
Geographic Profile of #Nets Fans
Geographic Information Nets
(Twitter Study)
#Nets
(Demographics Pro)
#Lakers
(Demographics Pro)
Location by State New York State - 46.4%
New Jersey - 11.2%
Texas - 1.5%
Pennsylvania - 1.2%
New York State - 35.7%
New Jersey - 17.5%
Texas - 10.6%
Pennsylvania - 5.1%
California - 47.3%
Florida - 8.2%
New York State - 4.3%
Location by City New York City (including
Brooklyn) - 46.4%
Brooklyn - 20.0%
SF/Oakland - 2.0%
New York - 35.7%
Houston - 8.0%
Philadelphia - 4.3%
Los Angeles - 23.7%
New York - 3.2%
Orlando - 3.1%
Source: Twitter analysis, December 2015, Demographics Pro, November 13, 2015
Twitter and the Players
Sentiment Analysis
• AlchemyAPI has developed several APIs which deploy machine learning
to do natural language processing.
• The average sentiment score assigned by AlchemyAPI was a neutral
0.00795 in November, decreasing to -0.050 in December.
• Sentiment is a quixotic and elusive thing to measure
Tone Analysis
Percentile Score of Nets Tweets
● Evaluates Emotional, Social and Writing Tone based on the percentile of words per tone
and tone trait
Word Count Score
● Measured % of words per tone and number of words per tone trait
Conclusions
• Current Nets Social Media/Twitter strategy is unfocused and ineffective
• Nets fans are young, on Twitter and ready to engage
• #Nets demographics align with team needs and interests
• Most #Nets users are local
• Twitter sentiment and tone indicates openness to cultivation
• Content of Tweets provides real time insight into fan passions and curiosity
• Twitter influencers can be identified, categorized and cultivated
• Social media is an underutilized asset, and properly used, the Nets should
sell more tickets and generate higher local TV ratings.
Recommendations
• Content Analysis
• Tweet content should guide media and marketing efforts of team
• Influence
• Nets players and executives can be trained to exploit Twitter
• Twitter influencers should be categorized and engaged by type
• Sentiment/Tone
• Should be assessed on an ongoing basis for changes in fan mood
• Cultivate fan passion
• Twitter should be used to convey the thrill of Nets games
• Highlight excitement in the stands (celebrity visitors) and on the courts
(shots, conflict, victories)
• Contests for seats, conversation with players, surprises
• The team must engage fans in alignment with fan passions.

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Web Analytics

  • 1. Audience Development Brooklyn Nets Presenters: Jane Boon, Haoxi Huang Hongyuan Lin, Zhenyang Wang
  • 2. Brooklyn Nets Audience: On TV and Online Local Television Deals: Brooklyn Nets – $20M/yr NY Knicks - $100M/yr, 2016 LA Lakers –$200M/yr (20 years) On Twitter: @BrooklynNets – 599K Followers @NYKnicks – 1.29M Followers @Lakers - 4.55M Followers Source: Google Trends, November 2015
  • 3. Developing a Local Audience via Social Media Basketball and Social Media • NBA fans are younger, more diverse, and more attuned to social media than any other sports fans • 5 of the 10 most Tweeted sporting events in 2013 were NBA games (Nielsen) • Twitter is the social media platform of choice for basketball fans The challenge: Brooklyn Nets and Twitter • How do the Nets fans feel about their team, and are they open to cultivation? • Are there Twitter assets and influencers the Nets can leverage better? • Are there geographic trends that can be exploited by the Nets for revenues? • Are there pockets of interest that can be pursued to develop new fans for the team? • How can the Nets engage and delight their audience, consistently and effectively?
  • 4. Twitter Crawling with Expanded Python Code Capturing - Text, Twitter Handle, Retweets, Likes
  • 5. Fan - Identification and Demographics Goal: Capture information about Twitter users - Python Twitter crawling code was expanded for our needs - Identify number of followers, Location
  • 6. Measuring Tweet Relevance Twitter user from prior slide - we are tracking his tweets for retweets and likes #Nets is the keyword used
  • 7. Twitter Influence and Engagement Followers - we count as a measure of influence Retweets - we capture the originator of the tweet
  • 8. The Nets - Who are the Nets followers/fans? Team fans/followers were analyzed
  • 9. Demographics of Nets Followers on Twitter Demographic Profile #Nets #Lakers Gender (% Male) 84.7% 74.9% Median Age 24.0 23.8 Median Income $35,100 $26,100 Race - White/Caucasian •African American •Hispanic 63.3% 24.3% 10.8% 43.8% 36.4% 18.5% Occupations - Students •Journalists •Authors/Writers •Musicians •Senior Managers •Other (notable differences) 20.7% 14.4% 10.4% 7.7% 6.3% Entrepreneurs (4.5%) 18.9% 10.4% 7.8% 8.1% 7.5% Artists (4.2%), Actors (3.9%) Source: Demographics Pro, November 13, 2015
  • 10. Geographic Profile of #Nets Fans Geographic Information Nets (Twitter Study) #Nets (Demographics Pro) #Lakers (Demographics Pro) Location by State New York State - 46.4% New Jersey - 11.2% Texas - 1.5% Pennsylvania - 1.2% New York State - 35.7% New Jersey - 17.5% Texas - 10.6% Pennsylvania - 5.1% California - 47.3% Florida - 8.2% New York State - 4.3% Location by City New York City (including Brooklyn) - 46.4% Brooklyn - 20.0% SF/Oakland - 2.0% New York - 35.7% Houston - 8.0% Philadelphia - 4.3% Los Angeles - 23.7% New York - 3.2% Orlando - 3.1% Source: Twitter analysis, December 2015, Demographics Pro, November 13, 2015
  • 11. Twitter and the Players
  • 12. Sentiment Analysis • AlchemyAPI has developed several APIs which deploy machine learning to do natural language processing. • The average sentiment score assigned by AlchemyAPI was a neutral 0.00795 in November, decreasing to -0.050 in December. • Sentiment is a quixotic and elusive thing to measure
  • 13. Tone Analysis Percentile Score of Nets Tweets ● Evaluates Emotional, Social and Writing Tone based on the percentile of words per tone and tone trait Word Count Score ● Measured % of words per tone and number of words per tone trait
  • 14. Conclusions • Current Nets Social Media/Twitter strategy is unfocused and ineffective • Nets fans are young, on Twitter and ready to engage • #Nets demographics align with team needs and interests • Most #Nets users are local • Twitter sentiment and tone indicates openness to cultivation • Content of Tweets provides real time insight into fan passions and curiosity • Twitter influencers can be identified, categorized and cultivated • Social media is an underutilized asset, and properly used, the Nets should sell more tickets and generate higher local TV ratings.
  • 15. Recommendations • Content Analysis • Tweet content should guide media and marketing efforts of team • Influence • Nets players and executives can be trained to exploit Twitter • Twitter influencers should be categorized and engaged by type • Sentiment/Tone • Should be assessed on an ongoing basis for changes in fan mood • Cultivate fan passion • Twitter should be used to convey the thrill of Nets games • Highlight excitement in the stands (celebrity visitors) and on the courts (shots, conflict, victories) • Contests for seats, conversation with players, surprises • The team must engage fans in alignment with fan passions.