Department of Telecommunications BACHELOR’S THESIS Nr BACHELOR’S THESIS Nr ANALYSIS OF SOCIAL MEDIA MARKETING KEY PERFORMANCE INDICATORS Marko Sršan Zagreb, July 2014

Department of Telecommunications Contents  Introduction  Key Performance Indicators (KPI) definition  Data gathering  English Premier League (EPL) model  Analysis  Hypothesis  Statistical Analysis  Correlation Analysis  Regression Analysis  Conclusion Zagreb, July of 15

Department of Telecommunications Introduction  Brands switch from traditional marketing to social media marketing (SMM)  SMM is still young, therefore it is needed to find ways to improve its KPIs  Analysis will be conducted on the leading English Premier League football brands  Motivation – find out how much real life events contribute to the SMM KPIs Zagreb, July of 15

Department of Telecommunications Key Performance Indicators definition  Key Performance Indicators  Social Media Marketing – Facebook  Brand’s reach (daily and weekly)  Brand’s growth rate (daily and weekly)  Brand’s fan engagement (daily and weekly)  Brand’s popularity (daily and weekly)  Search Marketing – Google Search Index  Internet presence (weekly)  Internet trend (weekly)  KPIs are set from Sunday to Sunday Zagreb, July of 15

Department of Telecommunications Data gathering  Time period – July 1st 2012 to July 1st 2013  EPL brands – Manchester United, Chelsea, Liverpool, Arsenal, Manchester City  Social media marketing  Facebook fan pages – Socialnumbers.com (link)link  Search marketing  Google Search Index – Google Trends (link)link Zagreb, July of 15

Department of Telecommunications English Premier League model  EPL model  Significant events (games, transfers, news, etc.) for each EPL brand shown over time  Significant events attached to data for further analysis  Eventually, events are translated into dummy variables Zagreb, July of 15

Department of Telecommunications English Premier League model  Manchester United model  On the March 5th, Manchester United lost a home game in the UEFA Champions League competition Zagreb, July of 15

Department of Telecommunications Analysis - Hypothesis  S hypothesis:  “Leading brands in sports industry have different weekly/daily KPI.”  C hypothesis:  “Weekly/Daily KPI of a leading sports industry brand is correlated with its other weekly/daily KPI.”  R hypothesis:  “Event1 of the leading sports industry brand contributes to their weekly/daily KPI more than the other event2 does.” Zagreb, July of 15

Department of Telecommunications Statistical Analysis - Example  S1a: Leading brands in sports industry have different weekly SMM reach. Zagreb, July of 15

Department of Telecommunications  Friedman’s ANOVA non-parametric test concluded that: Zagreb, July of 15 Statistical Analysis - Result Leading brands in sports industry have different levels of... Result S1a) Weekly SMM reach Yes S2a) Weekly SMM growth rate Yes S2b) Daily SMM growth rate Yes S3a) Weekly SMM fan engagement Yes S3b) Daily SMM fan engagement Yes S4a) Weekly SMM popularity No S4b) Daily SMM popularity No S5a) Weekly Internet presence Yes S5b) Weekly Internet trend No

Department of Telecommunications Statistical Analysis - Outliers  Outliers are identified, but they exist as a result of certain internal and external factors that influenced the KPIs Zagreb, July of 15

Department of Telecommunications Correlation Analysis  Cn: VAR1 of a leading brand in sports industry is correlated with its VAR2 on a W/D basis. Zagreb, July of 15

Department of Telecommunications Regression Analysis  General estimation model for all EPL brands with dummy variables  Most dummy variables (D ni and B ni ) and even some constants (c) are insignificant  Only 9.5% of the dummy variables was significant  They were supposed to estimate the impact a certain type of event has on the EPL brands’ SMM and search marketing KPIs Zagreb, July of 15

Department of Telecommunications Regression Analysis - Result  Contribution of EPL derbies (B 10 ) to Manchester United’s and Manchester City’s Internet trend  reason for high percent of insignificant variables can be the small sample due to such a high number of regressors Zagreb, July of 15

Department of Telecommunications Conclusion  Statistical analysis showed that there exists significant difference between EPL brand’s KPIs  Correlation analysis showed that  Internet presence is highly correlated with Internet trend KPI  SMM fan engagement is correlated with SMM growth rate and SMM popularity on a weekly level  Regression analysis showed that most of the regressors were insignificant  One year data sample is too small  Further analysis needed Zagreb, July of 15