Managing search terms is one of the most time-consuming tasks in Google Ads. Since search terms are the actual queries users type into a search engine, they must be reflected in ads and landing pages to avoid wasted ad spend.
Not all search terms are relevant to your business. It’s crucial to review them to decide whether to add them as keywords or negatives. For PMax campaigns, you’ll also need to determine the appropriate campaign for the search term.
With thousands or even millions of search terms in many accounts, manually assessing them isn’t feasible. This is where n-grams can help.
N-grams are one, two, or three-word patterns found in your search terms. You can aggregate performance data for each n-gram to evaluate its impact on your account.
For instance, if you have a list of search terms like these:
You can break them into n-grams and evaluate the data:
This is a sample of the above n-grams. In a full analysis, there would be more n-grams such as: San, Diego, in, number, phone, etc.
Instead of analyzing each search term individually, you’re looking at patterns that appear across many terms. An account with a million search terms often only has 30,000–50,000 n-grams. While still a large number, filtering and sorting this data makes it far easier to find insights.
Let’s look at the most common ways to use n-grams.
By far, the biggest use of n-grams is finding wasted spend and potential negative keywords.
There are two common filters you can apply to your n-grams to find potential negatives:
When reviewing this data, two n-gram-specific columns can help guide your analysis:
For instance, the phrases ‘and leisure’ and ‘lawn and leisure’ appeared in 265 search terms. With 99 clicks each, the average click per search term is less than one. Finding this type of pattern manually across thousands of search terms is almost impossible.
With n-grams, it becomes clear that search terms including ‘and leisure’ or ‘lawn and leisure’ have spent over $1,000, with zero conversions.
At this point, you have two options:
Looking closer, many search terms relate to an event called ‘Lawn and Leisure’ in Missouri. We’re not associated with this summit, and yet, we’ve spent over $1000 on search terms related to it.
This is an easy negative keyword to add since it’s unlikely to bring any additional value to our company.
In our previous filters, we looked at n-grams with zero conversions. You’ll often have search terms that are converting, but at very high CPAs.
Sorting your n-gram data by cost per conversion (CPA) or conv. value/cost (ROAS) will show you which terms perform the worst.
However, Google’s data-driven attribution can make some search terms look worse than they really are. For instance, our most expensive n-gram has a CPA of $17,377, yet it’s only spent $173. That’s because it has 0.01 conversions. Small fractional conversions can make CPAs and ROAS numbers highly misleading.
Additional filter criteria can help you narrow down your search, such as:
You can then sort by higher CPA or lower ROAS to find n-grams to evaluate.
In this example, people looking for ‘today’s mortgage rates’ don’t convert well. You could add that as a negative keyword or go further and examine the word ‘today’.
In the n-gram data for the past year, there has been a single conversion for search terms that contain the word ‘today’. That would also be a candidate for a negative keyword.
However, you can also look at the data from an organizational perspective.
In the screenshot below, search terms that contain the word ‘conventional’ have an extremely high CPA. If we offer conventional loans, adding the term as a negative keyword might not make sense. Instead, it’s worth digging deeper.
Many of the search terms that contain ‘conventional’ are comparison terms:
If we don’t have an ad group specifically for comparing FHA and conventional loans, we could create a new ad group for those terms to see if we can convert them.
Once you add negative keywords, you will no longer show ads for those search terms. There are times when creating new ad groups is a better solution.
This Adalysis customer produces personalized products. When they reviewed their n-gram data, they saw a lot of search volume for wine.
They also discovered a lot of volume for custom-printed wine glasses, a product they didn’t offer. As a result, they made the search term ‘wine’ a negative keyword while they developed a new product line.
After several months, they removed the negative keyword for ‘wine’ and launched a new product to convert the searches into new customers.
There are two primary ways of getting n-gram data:
There are several scripts that can write your search terms to a Google Sheet, where you can evaluate them. The biggest disadvantage of this method is that the search terms aren’t usually listed with the n-grams. It’s simply too much data.
You may need to use Google Sheets alongside the Google Ads interface for evaluation. If you have a lot of search terms, the scripts might also not be able to evaluate your entire account.
Some third-party tools, such as Adalysis (where these screenshots were taken), automatically create and evaluate your n-grams. This makes it easier to jump straight into your analysis. You can spend your time assessing and working with the data, instead of compiling your dataset.
Adalysis offers a 30-day free trial so you can see how n-gram analysis can help manage Google Ads accounts.
For your highest volume search terms, you’ll need to evaluate and decide what to do with each one. However, when evaluating your search term data at scale, nothing beats n-gram analysis.
N-grams make it easy to find and analyze:
Don’t just ignore your low search volume terms. In aggregate, you can gain many insights from them. Instead of trying to make sense of them manually, turn to n-gram analysis to make your search term evaluation insightful and quick to manage.