N-gram analysis on Keyword Planner data

You can discover interesting search patterns for your SEO strategy by analyzing n-grams in big keyword lists. Here is a real life example of how easy and fast it can be done.

This will be a short how-to on applying n-gram analysis on search queries extracted from Google Keyword Planner. The main goal of this analysis is to better understand patterns in big keyword lists. In our example, we’ll use the monthly search volume and the indexed competition as KPIs. Use our free N-Gram Analyzer to get the exact same output I’m showing in this post.

We created a keyword list in Google Keyword Planner and imported the CSV data to Google Sheets. This is how our data looks like:

Instead of looking at the complete queries, we’re interested in single words (1-grams). Maybe there are some query patterns that appear over hundreds of queries—none of the single queries would have caught my attention when looking on search volume. By summing up the volume on n-grams, interesting search patterns can be discovered. For running the n-gram analysis, copy your table columns to your clipboard.

Then paste the data into our free N-Gram Analyzer tool:

Download the CSV file and import it to Google Sheets or Excel and your result of the N-gram Analyzer is looking like this:

N-gram results with aggregated KPI data.
  • Keyword: This is the result of the n-gram transformation. Instead of full queries, single words appear.
  • Avg. monthly searches / Competition: These two columns were part of our file input — they get aggregated by default. In the case of competition, we need a small adjustment, which we’ll come to in a second.
  • Count: This is the number of queries where the n-gram appeared.
  • AvgCompetition: This is the adjustment we were talking about. To get correct averages, we take the aggregated competition numbers and divide it by the “Count” of the queries.

This was just one small example of how you can use n-gram analysis in real world use cases. It isn’t only great for discovering interesting search patterns for your SEO strategy — it’s also great to identify negative keywords for your PPC accounts. But this is another story for a standalone post.

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