Summary
Big thank you to Dan Willoughby and the team at Adevolver for the help with this.
Skip the explanation and jump to the tool ◀◀◀
If you’ve managed Google Ads Accounts for a while, you’ve likely intuitively used them. For example, you might have a phrase match of “how to” or “diy” negatives for your accounts.
You know that these terms are very unlikely to bring in quality searches.
N grams are a way to use your data to find how common phrases do across a large amount of search terms.
If you put a 1000 search terms and find the common phrases, or “n-grams”, you can quickly make judgements on the efficacy of those n-grams.
The common phrase or 2 gram of “near me” for a local account is likely very positive.
The common phrase or 3 gram of “how do I” for a local account is very negative.
Using n grams helps you get data out of your search terms faster.
Let’s say you’re a D2C deodarant company. You’ve got about 1,000 ways that people search for deodarant.
Most of those long tail search terms don’t have enough data to say if they’re “good” or “bad”
For example, “best deodarant for men mint smell no aluminum” might only have 3 clicks. Is the term worth continuing to bid on or not?
This is where n grams come in.
An n gram analysis might now that the 4 gram of “best deodarant for men” is highly profitable. Therefore, it is likely that this search term will become profitable.
In a traditional analysis, n grams are all aggregated together and produce a score.
The 4 gram of “best deodarant for men” may have spent $10,000 and generated $15,000 in profit.
However, in most PPC accounts, it is likely that $8,000 of that spend resulted in $14,500 in that profit.
If you are able to find and cut the $2,000 in spend that lost your $1500, you can achieve more profit.
Let’s say you have a 3 gram of “dove men deodarant” that spent $5,000 and only brought in $1,500 in revenue. Any PPC manager would be tempted to do a phrase match exclusion.
However, what if you could find out that all $1500 of that revenue came from search terms with $200 in spend?
For example, your exclusion of “dove men deodarant” could have negatived out “dove men deodarant alternatives” which is a great term.
In a traditional N Gram analysis, you would be open to making this mimstake. With layered n gram analysis, you will not.
Layered n gram analysis allows you to set a CPA target or ROAS goal.
Each gram analysis is given two scores:
The regular score factors in every single search term. The efficient score only factors in search terms that reach your ROAS or CPA goal.
If you have 1000 search terms and 200 of them beat your ROAS/CPA goal, you will get:
For example, the gram “deodarant for men” will have the two different scores. The first generated from all of the matching terms. The second generated from all terms beating the CPA/ROAS target.
By looking at the above, you can learn:
In a proper report, like below, you’ll get a report showing multiple dimensions for each gram.
This tool is free to use. Upload a CSV here to get an analysis emailed to you.
Important privacy notes:
Export these columns from your search term report for this to work. You will be able to keep the default names that Google exports.
Important: After you export, delete the first two rows of your export as well as the summary rows at the bottom.
Take this data and find the high performers and low performers in your account.
Consider giving your high performers special treatment, and segmenting (or adding negatives for) your low performers.
It can be tempting to exclude phrases too early because of data from n gram analysis.
If you’re dealing with low volume of data, it’s better to “quarantine” your searches into specific campaigns with lower bids rather than excluding them outright.
Enough people hire me to automate big accounts or increase account efficiency making this worth it. Send me an email at [email protected] if that’s something you’re looking for.