2. Visibility Benchmarking
Visibility benchmarking reviews a site’s current visibility against competitors and identifies the gaps in current keyword/content coverage.
It also identifies where competitors have visibility your site does not.
Typically, you can pull data with SEMrush, BrightEdge Data Cube, and other data sources.
To do this, you enter the data into Excel and organize the data by branded and non-branded keywords and in different visibility zones.
This is quite challenging if you have a lot of non-branded keywords, business lines, and competitors – and if you have multiple categories and subcategories.
Using Python scripts, however, you can automate the process and analyze cross-site traffic with overlapping keywords to capture untapped audiences and find content gaps.
This is much faster and can take only hours to do.
Visibility benchmarking reviews a site’s current visibility against competitors and identifies the gaps in current keyword/content coverage.
It also identifies where competitors have visibility your site does not.
Typically, you can pull data with SEMrush, BrightEdge Data Cube, and other data sources.
To do this, you enter the data into Excel and organize the data by branded and non-branded keywords and in different visibility zones.
This is quite challenging if you have a lot of non-branded keywords, business lines, and competitors – and if you have multiple categories and subcategories.
Using Python scripts, however, you can automate the process and analyze cross-site traffic with overlapping keywords to capture untapped audiences and find content gaps.
This is much faster and can take only hours to do.
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