How to leverage n-gram analysis to shift towards modern search

Matt Shenton

Biddable Associate Director

7th February 2022

~ 4 min read

Among the many changes in digital marketing over the last two years, one of, if not the largest shifts in paid search has been the release of modern search, Google’s latest best practice, which was first announced at the start of 2021. 

Central to this new approach is a simplification of match type coverage and segmentation, validated by the elimination of broad match modifiers (BMM) in July 2021. Moving from BMM to pure broad match may be scary and counterintuitive for classic search marketers. 

While tools like Dynamic Search Ads (DSA), which dynamically match to search terms based on page content, have been around for some time, traditional paid search strategy has largely been about control. This entails utilizing large lists of finely segmented keywords, often segmented by match type. Conversely, a modern search approach relinquishes some control to the “machine,” trusting it to accurately match to and bid on relevant terms at large scale.

N-gram analysis

This is where n-gram analysis comes into play. N-grams are essentially the splitting of a search query string into two, three, four or n numbers of grouped terms. For example, if we take the search query “where to find cheap car insurance”, and want to analyze it using a two-gram approach, the output would be:

  • “Where to”
  • “To find”
  • “Find cheap”
  • “Cheap car”
  • “Car insurance”

Similarly, a three-gram approach would look like this:

  • “Where to find”
  • “To find cheap”
  • “Find cheap car”
  • “Cheap car insurance”

When we collate the performance data associated with these n-grams, we can start to understand patterns. When we use this analysis before and after a transition to a different match type (full broad), we begin to get a much clearer picture of how the search term landscape within our account has changed.

N-gram analysis in practice

At Croud, we recently used this approach for a client shifting towards modern search, where we analyzed 100,000 n-grams which resulted in two impressive findings:

  1. Finding gaps in coverage: The analysis uncovered several mid- to long-tail search query trends that we weren’t covering before. Think of it as the new structured query reporter (SQR).
  2. Understanding unintuitive search behavior: We were able to observe a huge increase in the type of searches involving search behaviors we had not fully appreciated before. This included a higher number of search terms containing adjectives and ‘near me’.


The n-gram analysis is one example of the methods and tools that we, as digital marketing practitioners, need to develop in order to adapt to a modern search approach. We need to create new ways to understand what is actually going on, to the greatest extent the platforms will allow. This isn’t so we can interfere in the minutiae or to exert control, but to help build trust in the systems and to have a high-level understanding of how to manipulate them to best achieve our clients’ objectives.

If you’re interested in learning how to leverage n-gram analysis to shift towards a modern search strategy, get in touch with our PPC team.

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