PSG

       Determining the Value of Brandwatch’s Football Sponsorship Analysis      

 
   
     
       
         
            
            
         
       
      
       
         
            
            
         
       
      
       
         
            
            
         
       
      
       
         
            
            
         
       
     
   
      In a post titled “Which Football Sponsors Get The Best ROI?,”  Brandwatch  examined the value created by kit (or jersey) partners over the past year on Twitter and Instagram. Not only did it look at the number of images produced, Brandwatch also created an ROI index that looked at the cost per image for soccer teams for Nike, Adidas, Puma, and Under Armour. More specifically, this analysis “divided the total images each sponsor received by the amount paid for their sponsorship.”  The analysis had two findings that may be surprising to most soccer fans. First, Leicester and Paris Saint Germain (PSG) returned the highest value on a cost per image basis. In  addition , “Puma performs incredibly in this analysis.” Puma’s £13.62 per image is far lower than Nike’s £43.53 per image. Given that Adidas pays only £8.45 per image, “Nike struggles to generate the same ROI as its rivals.”  Unfortunately for Leicester, PSG and Puma, there are several reasons why Manchester United and Nike are likely not too worried about this analysis. To start with, the cost per image metric needs further examination because of the way in which Brandwatch calculates cost. In particular, it is not clear why Brandwatch examines the entire cost of the partnership while only looking at one channel for its ROI analysis (social media focused solely on Twitter and Instagram). There is an argument to be made that companies should be focused on social media for activation of jersey deals. However, many deals now are focused on television viewable signage in video and not static images in social media. Maximizing time on screen for broadcast video is typically the goal of partners with these deals.  In addition, the analysis seems to lack standard image metrics when considering value. In particular, it omits prevalence (how much of the screen does an image take up), centricity (how close the image is to the center of the screen), and confidence (how clear is the image on screen). If an image is small or not in the center of the screen, then it is less likely that a person will be able to identify the logo.  The cost per image has another methodological flaw – it is only looking at the quantity of the images posted rather than the quality of posts with those images. Nike, Adidas, Under Armour, and Puma (the brands featured in this analysis) each have different goals for their sponsorships. For example, having a static image of a company’s logo can be a good way to increase brand awareness. The more images there are, the higher the likelihood that someone will see the brand. Nike arguably has near universal brand awareness while Puma is not at Nike’s level. While Puma is generating value from its jersey partnerships for this reason, Nike should not be looking at this metric in the same way given its business goals.   In addition, Adidas has taken market share from Nike, in large part, by becoming the “ coolest brand in sports ”. Does the quantity of images help Nike address this issue or is the context in which those images appear more important? Looking at the sentiment of posts would be a critical part of Nike’s analysis to determine if people are saying positive or negative things about the brand.  Finally, all of these brands would be looking at engagement metrics to determine whether people are interacting with these visual posts. More specifically, if no one is liking, sharing, retweeting, or commenting on posts then it is likely that the audience is not engaged with the content. The number of images is often less important than having engaging content consumed by a company’s targeted demographics.  The Block Six Analytics  Social Sentiment Analysis Platform (SAP ) conducts jersey analysis by looking at the quantity, quality, and engagement of social media content. Our technology can identify which posts have company logos and determine the engagement of those posts. We also examine the value of those posts by looking at the specific revenue and marketing goals of a company to determine how value is being created. We then use our Media Analysis Platform (MAP) to examine the ROI in live television, highlights, and digital channels to examine how video content featuring a company’s logo creates value.     

  

    
       
      
         
          
             
                  
             
          

          

         
      
       
    

  


     To its credit, Brandwatch did uncover valuable insights. In particular, Puma’s unique placement (as compared to other jersey partners) on the sleeve of a jersey (instead of on the chest) did enable the company to maximize the number of photos containing its logo. However, the other issues make Brandwatch's conclusions difficult to substantiate. B6A’s cross-channel, company-specific approach directly addresses the challenges with this Brandwatch analysis.  
BY ADAM GROSSMAN

Determining the Value of Brandwatch’s Football Sponsorship Analysis

In a post titled “Which Football Sponsors Get The Best ROI?,” Brandwatch examined the value created by kit (or jersey) partners over the past year on Twitter and Instagram. Its primary methodological flaw is that is only looking at the quantity of the images posted rather than the quality of posts with those images