Luca Massaro Founder of We Play

The Wonders of Data and Measuring for Social Media Success in Sport

Matthew Falla Partner at Signal Noise

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Sales and Marketing Analysis

Fan Segmentation

Social Media Strategy

Product Manager

Lets go back in time…

TargetMCG Media  and  Communica-ons  Group  

Partners:

We Know Sports Fans

Fan Segmentation

Trends Analysis Territories Analysis

1   2   3  

Influencer and Advocacy Mapping

Competitor Benchmarking

Strategic Recommendations

When Social meets Real World

Predicting the Next President Using Twitter

•  Analysed Tweets in the ‘swing States’ •  Used Sentiment analysis to see positive vs negative Tweets to create a Positivity Score •  Attributed the Positivity Score to the Swing States and number of votes available

Our Predictions

Modest prediction: Barack Obama to win

Bold Prediction:

Obama will win with over 300 electoral votes but no higher than 310

Exact Prediction:

Obama to win with 304 electoral votes

Electoral Vote: Obama 332 (303 Before Florida)

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Signal Noise is an information design agency combining the disciplines of information and UX design to create content, tools and installations.

Data Insight Content Product

LISTENING & ENGAGING STIMULATING SOCIAL ENGAGEMENT

Leaderboards Real time monitoring and fan engagement

Empower any community with a real time engagement and monitoring dashboard

Leaderboards

Tweet to Win an iPad Fans Tweeting

Trigger Action Reward

Data Brand awareness

Happy fans

How do our leaderboards work?

Leaderboards How do our leaderboards work?

Fans and Followers

Connect to Social Network Track Followers and retain data

Publish League Table

Supercharge your target audience, get them to compete against each other to retain customer data

Monitor Performance

Twitter Betting League  

Leaderboards Leaderboard examples

Leaderboards Profiling the Betting Community

700k Followers

The Betting Community

We can profile fans and give you the insight needed… to turn them into Customers

Run Scripts

Accounts following

Usage

Keywords

Territories

Segmented and Profiled potential customer

But how can this process be attributed to sports… and specifically; to players?

We believe this data is really valuable for…

Clubs

Player representatives

Brands, sponsors, agencies

So we set ourselves a challenge…

The problem…

Multiple software packages

Expensive licenses

Resources and training

But imagine…

So where would you begin? Listening tools

Data from all the social platforms in one place

Explaining the score

The scoring is a formula that takes the data from each social platform in relation to the messages sent on that platform in the time period selected. That score is then relatively weighted based on all data from all players and modified into a single percentage out of 100.

But what part does perfromance play?

How can you use this data to determine value?

The factors that matter to your business…

Merchandising sales

Media spend

Image rights

How do you start to turn this into actionable insight?