- 23. August 2018
- Posted by: broschart
- Category: Competitive Intelligence
German Football Clubs – a Website Performance Comparison
In this case study we want to show how the power relations of a brand in the market can be visualized and understood by means of its presence in the search results. We compare the football clubs FC Bayern Munich, Schalke04 from Gelsenkirchen, BVB from Dortmund and the Red Bulls from Leipzig.
The consideration and analysis of the digital presence of football clubs is subject to a special peculiarity. In contrast to classic consumer goods, the purchased product cannot be touched directly. On the other hand, advertising does a lot to emotionally charge the advertised products. And this is exactly what makes football so special: it is all about the acquisition of emotions – which can also be measured in search behaviour, making it an interesting object of research.
It should be mentioned here that the search behaviour has a direct effect on the composition of the search results. If, for example, the goalkeeper of the national team is expected when searching for “goalkeeper”, the FC Bayern website benefits from exactly this expectation. Google & Co. are always anxious to track down such “association clusters” – in advance by means of artificial intelligence, and later by evaluating the search behaviour.
Note: As the source of the data used in this analysis, we use ahrefs.com – unless otherwise noted.
Objectives of the websites
Before we investigate the presence of domains on Google, we should be aware of the communication goals of the websites. What is their raison d’être? What role do they play in the value chain?
As already underlined, football lives on emotions. In order to maintain this, the website serves as an omnipresent interface to relevant information and emotions. And of course the clubs act as commercial enterprises. The fan shop is just as important for economic survival as ticket sales. And finally, the sponsors and partners should also be integrated and represented in a way that is effective for all sides.
First of all, we want to address the question of how present, how “strong” the individual clubs are. For this purpose, we take a look at the following visibility index:
Based on this graph, this is a clear case: FC Bayern clearly dominates the other clubs. Schalke04 achieves about two thirds of this presence, BVB about half. The red bulls show the worst performance here.
The visibility provides an initial overview of the presence in the search results. However, many aspects merge into an “oversimplification”, which makes a differentiated analysis difficult or even impossible. For example, it would be important to know what exactly “works” for which club and what doesn’t. Possibly, however, the high visibility may also be generated through rankings in contexts that are not crucial for economic success. So we have to go into more detail.
A detailed visualization can be realized with our Streamline illustration. The following figure shows a line representing the time course for each ranking (almost 230,000 in total) found in the top 100. Each club is marked with its own color. The rankings 1 to 100 are displayed in descending order. Rank 101 stands for the exit from the monitoring area.
At the bottom of the figure you can see how many Top 100 rankings the respective domains achieve. It is interesting to see here that the BVB quantitatively outperforms Schalke04. In the visibility index shown above, this situation presented itself in a different way.
From search phrase to context
The streamline visualization in the example shown above does not yet seem to be very meaningful. Too many rankings overlap here, so that structures are actually hardly recognizable. Therefore, we should filter or group the search phrases according to meaningful criteria. An elementary criterion here is the word component. Thus, only those rankings are displayed that contain a given word component. In this way, “contexts” can be illustrated.
The following figure shows why this can be of enormous importance using the example of “trainer”:
Here you can see very well that all search phrases containing the term “trainer” are dominated by FC Bayern (blue). This is not only recognizable by the high number of search phrases, but also by the color distribution in the streamline diagram (hemline at the top, corresponds to rankings 1 to 5).
Since in practice often only the first search result page counts, we would like to limit the rankings to the first 10 rankings. The following figure shows all rankings whose search phrase contains “trainer” and was found on the first search result page on July 25th, 2018:
The Red Bulls are only occasionally represented in this context, while FC Bayern stands out from all other clubs.
Let’s have a look at the new entries in the context of “trainer” during the observation period:
FC Bayern is not quite as well represented among the new entries – especially because there are no high entries to more prominent search result pages. Schalkeo4 scores well here.
Now let’s have a look at the exits in the context of “trainer” for the observation period:
The FC Bayern is in the lead here. On closer inspection, however, it can be seen that no previously well-ranked search phrases dropped out of the top 100. In practice, this development is unlikely to affect the number of visitors.
Watch Google learn
It is always interesting to see how Google learns to better understand user intentions. The following figure shows the rankings for “trainer bvb”, which only temporarily entered the top 100:
As you can see here, you could find the Red Bulls in the search for “trainer bvb” on July, 11th, 2018 on the 6th search result page on Google. However, we also registered an increase in rankings with FC Bayern and Schalke04. This observation suggests that this is a systematic cause that influences the contextual understanding. But already on July 18th, 2018 Google seems to have “understood” that the contexts – even if all domains are about football – are not sufficiently similar to consider them.