JD Sports is a sports-fashion retail company with many outlets throughout the UK.
The above metrics give an idea of the initial market share results for JD Sports. They show that the market consists of 224,000 keywords of which, their pages only rank for 13,000.
There are a total of 377 million searches for those market keywords of which, only 5,4 million are for JD Sports’ ranking keywords. By looking at these initial metrics, it is evident that there is room for improvement, and the Authoritas platform gives the insight into these opportunity keywords and content.
From the initial site analysis, the following key metrics were found…
If JD Sports were to optimize their:
- EXISTING keywords for EXISTING content, their traffic could increase by 177%
- EXISTING content with NEW keyword suggestions, their traffic could increase by 589%
If JD Sports had to create:
NEW content from NEW keyword suggestions, their traffic could increase by 118%
JD Sports’ top 100 market domains
Below is a plotted graph of JD Sports’ top 100 market domains. The red bubble illustrates where JD Sports falls within the ‘Core Niche Competitors’ quadrant, and where they fall in relation to their competition.
Create EXISTING content with NEW keyword suggestions
The graph below shows the clusters of new opportunity keywords to use in the optimization of existing content. The cluster of keywords to begin with would likely be the ‘shoes’ cluster.
This is the best cluster to start with as it has a high organic growth potential, and a high relative strength (determined by the average of majestic trust flow and citation flow), in comparison to the other clusters shown on this graph. This ‘shoes’ cluster also has a good amount of opportunity keywords to work with. By beginning with this cluster, changes can be made to start seeing immediate results.
Keywords found within the ‘shoes’ cluster
The table below gives an example of the types of keywords found within the ‘shoes’ cluster. If optimization campaigns are carried out on the short-term quadrant’s clusters, overall traffic could increase by 589%.