- #Keywords everywhere python how to
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Now let’s make some empty lists to store the data. Search_terms = df.tolist() # dump search term queries to a list (to loop through with the Search Console API) # make a temp dataframe to append the word 'stockists'ĭf = pd.DataFrame(brands, columns=)ĭf = df + df There’s probably 100 more pythonic ways to do this, this is just how I choose to do it. I’m doing this using Pandas because it’s familiar. Next we need to append the word ‘stockists’ to each brand name so we can search for the related stockist page in Google. With open(path +'/brands.txt', 'r') as file: # read in the Keywords Everywhere API Key With open(path +'/zenserp_key.txt', 'r') as file: # read in the Keywords Everywhere API Key Once the directory has been set, we can read in both files. The next step is to get the current working directory using the OS module so the script knows where to find zenserp_key.txt and brands.txt # get the current working directory and print Location = "London,England,United Kingdom"
All settings are available at: # zenserp variables used to search google // I recommend updating them for your region and language. This is where the variables are set to search Google with. Next we import everything we need to run the script.
#Keywords everywhere python install
The first thing to do is to install the requests and pandas library, if not done already. To read more about custom extractions, I strongly suggest reading this post on the Screaming Frog blog. This is easily extractable using custom extractions. The image below shows the brand: SHARK for this product on .uk. Scraping the brand attribute from the product schema is a surefire way to extract a comprehensive list of brands from a Website using a custom extraction. Scraping the Brand attribute from Product Schema If you’re not so lucky, then it’s time to fire up Screaming Frog and do some custom extractions. If you’re lucky, the site will have a brands page, such as this one: A list of brands in an easy to use, copy and pastable format. If you don’t have that luxury, then it’s time to get creative… If this is for your own site, this is usually as straightforward as looking through a spreadsheet of suppliers.
#Keywords everywhere python how to
One thing I’d like to touch on briefly is how to find the list of brands to use for the script. Often it’s just a case of picking up the phone or sending an email. This is usually easy to do because of the existing relationship with the supplier.
The only thing left to do is to review the opportunity and reach out to the site owner and ask to be included on the page. To view the output in more detail you can review this Google Sheet The script found some excellent links, such as this one: csv file in the same folder ready to QA.ģ68 links checked for .uk and compiled into a spreadsheet in 22 minutes on autopilot! That’s a LOT faster than manually Googling and a lot less boring too ? Once the script has finished, it’ll output a. Watch as the script does the hard / boring work for you! Output
#Keywords everywhere python code
Open the command prompt and change directory to where the above files are located by typing:įinally run the code by executing the python script If done correctly your folder should look like this: Paste the list of brands you’d like to check for stockist links into a plain text file called brands.txt.Setup an account with ZenSERP, and paste the api key into a plain text file called zenserp_key.txt.
#Keywords everywhere python download
These links are gold dust and really move the needle for SEO.
One of the best types of link for an eCommerce store is from a brand stockist page. Links are still an important aspect of any SEO strategy.