Everybody knows about Broad, Phrase and Exact matches but the Broad Match Modifier, or BMM, as we like to call it, is not so well known. Broad Match Modifiers are are a type of Broad Match that have better precision matching with search terms.
What are Broad Match Modifiers?
In Amazon's own words:
"You can add broad match modifiers to indicate words that must appear in the customers' shopping queries for your ad. Add a broad match modifier by adding a plus symbol "+" before the keyword.
For example, if you use the keyword "+kids shoes" with a broad match modifier, then the ad will match only the searches that contain the word "kids."
The ad may match to "kids sneakers" or “running shoes for kids” but they won’t match any shopping query that doesn’t contain the word "kids," such as “sneakers” or “running shoes.”
If our BMM keyword is +nike +running +shoes, then those three words MUST be present in the matching buyer query.
In other words, BMM match type improves the quality of matches by ensuring that the keywords that we have so painstakingly selected by using a variety of tools such as DataDive or Helium10 are not disregarded by Amazon's broad match.
Which Ad Types do they work with?
BMMs work with both Sponsored Brands (SB) and Sponsored Products (SP), although they were initially created for SB ads to limit the "broadness" of the Broad Match.
Broad Matches with SB ads will match "nike" to "adidas" with their broad match because Amazon thinks they are related as far a sports shopper is concerned. This behavior is not typically seen with SP campaigns but it is not completely out of question, and besides Amazon is slowly heading in the direction.
Recently even Exact match campaigns have been seen to match with synonyms as you can see here.
Speculation has it that in the future Amazon might do away with match types altogether and manage keywords based on AI matching of shopper purchase intent. Do you see it coming?
Which is better: BMM or Exact Match?
Exact match campaigns are great when you can identify highly relevant, long-tail keywords with good search volume. The problem with Exact matches is that the probability of someone typing in the exact phrase you are bidding on, in the same word sequence, and with no extra words is much lower than the probability of the someone typing a search term that is a bit out of sequence, uses a strong synonym and perhaps has additional words before, after or in-between.
For example, our main Exact match keyword is vanilla scented candle with a yearly search volume of 36,760 (monthly 3060).
The corresponding BMM keyword would be +vanilla +scented +candle. What search volume can this keyword attract?
If you refer to the Product Opportunity Explorer for this niche you can see that there are at least 4 keywords with a total search volume of:
36,760 + 23,687+13,173 + 8,845 = 82,465 searches a year (monthly 6872).
This is more than twice the amount of search volume than the Exact match version. Using a BMM is a no-brainer in this case.
The most common symptom of an Exact match-only strategy is low impressions. This is disheartening for most, and might prompt you to substantially increase your bids in the hopes of winning more impressions. This then has the effect of you eventually winning clicks at much higher CPCs than if you attracted the same search term with a broad match modifier at much lower CPCs.
When using BMMs on the other hand, winning impressions is generally not a problem with lower bids as Amazon seems to like the control of broader targeting. The only downside is that you might generate irrelevant searches that need to negated.
For example, if your candle is not soy based you will need to negate that term proactively.
When to use BMMs?
At PPC Ninja, we like to use BMMs in the following situations:
For both SP and SB ads
Use both BMM alongside Exact match campaigns
Once we harvest good keywords from SQP data we add them as BMM and Exact match both for the same reason explained above
Conclusion:
The main issue we are solving with BMMs is that they facilitate high quality search term matching since the terms we pick must be present in the buyer search. The other issue we resolve is that of no or low impressions with the corresponding Exact terms. Use both and dominate your ranking targets!
Final thought: With Amazon rapidly adapting AI, the likelihood os a world without match types is not unthinkable. Imagine just providing Amazon with keywords and the algorithm automatically figures out how best to match that with a customer search term, through syntactical or lexical analysis. But as long as we have access to Broad Match Modifiers, we can future proof ourselves, starting now.
If this post sparked your interest, leave us a comment or a question!
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