Nielsen Social released its Twitter ratings for the past Champions League match-day today. It will come as no surprise that the Barcelona/Arsenal match carried the day, but Bayern/Juventus were not nearly as far behind as it seems at first glance. Here are the overall Twitter ratings, with Bayern/Juve placing fourth on the top five:
source: Nielsen Social
The number that leaps off the page is obviously the number of "impressions" for Barcelona/Arsenal: 15,079,000 impressions, which is 4.3 times as many as Bayern/Juventus, with only 3,528,000. This dominance, however, is not as clear-cut as it first seems.
Here's the TL;DR version: the audience for Bayern/Juve was actually quite robust and active, but separate team markets and probably also language differences prevented individual Twitter users from interacting on Twitter to the same extent as the audience of Barca/Arsenal, resulting in a misleadingly skewed "impressions" total in favor of the latter. Bayern/Juve had a very good audience; they just didn't communicate with each other as well.
What are "Twitter impressions"? An "impression" is a tweet about a given thing - let's say the Bayern/Juve game - that has been delivered to the Twitter stream of a particular user. Now, if two different people ("unique authors") tweet about the game, and their tweets appear respectively in the streams of two different users ("unique audience members"), but not in both, then those tweets will register only two impressions (in other words, 1x1 + 1x1 = 2). If, though, those two tweets appear in the streams of both audience members, that will translate into four impressions (1x2 + 1x2 = 4).
Follow me so far?
So, what do these numbers tell us about the ratings for Bayern Munich's match against Juventus? First of all, the discrepancy with Barcelona/Arsenal is not nearly as great as it first seems. Going by impressions alone, it would seem as if Barca/Arsenal was almost five times as popular. That is not really the case: their unique audience - the number of people actually receiving tweets about the game - was only about 2.5 times as large, 3,372,000 versus 1,345,000. Given the combination of world-marketing colossus Barcelona and a very popular English side in Arsenal, that number is not so shocking.
Authors and Audience
The numbers tell us even more. The most significant difference is that the Barca/Arsenal users were far more active in producing tweets: Barca/Arsenal had a much higher proportion of authors/audience members than Bayern/Juve (1/45 versus 1/71), and those authors also tweeted almost 40% more often (3 tweets/author versus 2.16 tweets/author). In other words, the Barca/Arsenal users included a far greater proportion of authors who generated a far greater number of tweets than their Bayern/Juve counterparts.
That brings us back to impressions: the ratings for Barca/Arsenal show that there were 4.5 impressions for each unique audience member, whereas there were 2.6 impressions for each Bayern/Juve audience member. What I think that ultimately means is that the audience for Barca/Arsenal was far more integrated than the audience for Bayern/Juve. Tweets sent about Barca/Arsenal were reaching a far higher proportion of unique audience members. Tweets about Bayern/Juve had a relatively large unique audience, but the unique authors for that game were reaching a much smaller proportion of the total: it was more like the two authors who each reach one audience member, rather than the two authors who reach both.
Failure to Communicate (Communitweet?)
Given the major English market for both Barca and Arsenal, but the primarily German and Italian markets for Bayern and Juventus, it makes sense that the Barca/Arsenal Twitter users should be better interconnected: they presumably follow more of the same authors, and so receive the same tweets, resulting in a far greater volume of impressions.
Something similar appears if we compare Bayern/Juve to the basketball games in second, third, and fifth place. Bayern/Juve drew roughly as large an audience as these games, but had far more unique authors and unique tweets: 19,000 unique authors and 41,000 tweets compared to just 12,000 unique authors and 22,000 tweets for the second-place Pelicans/Wizards NBA game. The authors and audience for this NBA game must be much more homogeneous and thus better connected on Twitter. The overlapping audience thus leads a significantly higher number of impressions relative to the number of authors and tweets.
Judging by the high number of authors and tweets for Bayern/Juve, the game was a far greater success than its fourth-place finish by unique audience suggests. Twitter users were seriously interested in Bayern/Juve, but they just didn't connect with each other to come closer to the ratings of Barca/Arsenal.