Amazon Negative Keywords: Why & How to Use Them Effectively

When it comes to Amazon, it is critical to continuously do keyword research as trends and consumer behavior change, but researching keywords can come at a steep cost as you inevitably test by spending on some Search Terms that don’t convert.

So if we know we need to spend some money on terms that inevitably don’t convert, what can we do to reduce wasted spend?

The traditional approach: Negative EXACT matches

The traditional approach to reduce wasted spend is to download search term reports, monitor what search terms have multiple clicks and no sales, and to apply a negative exact match to these search terms. This can be challenging as you traditionally want to wait until a term has quite a few clicks to ensure that it won’t convert for your ASINs prior to applying the negative match.

Additionally, although this stops the wasted spend on this specific search term, this is a reactive approach and doesn’t influence further irrelevant search terms.

Perpetua’s approach: Negative PHRASE matches

You may find that there are words your campaigns continue to spend on in multiple search terms that aren’t relevant to your products. For example, if you sell dog chews and use “dog chew” as a BROAD keyword, you may find the word bed appearing in a search term (e.g. dog chew bed). If you apply a negative exact match to this specific term, this will not stop your campaigns from spending on other search terms with the word bed in them (e.g. chew proof dog bed).

However, if you apply a negative PHRASE match on the term “bed,” this will prevent all future search terms that contain this word - this proactive approach will allow you to reduce wasted spend much more significantly than if you were to negative exact match many keywords.

So why doesn’t everyone do this already? Combing through Search Term reports to find these words to negative PHRASE match is not as simple as finding keywords to negative EXACT match - but that is what the Data Science team here at Perpetua is here to help with.

Introducing Negative Match Recommendations

Perpetua will now surface these keywords for you to negative phrase match with one click - this is available in both our web platform as well as iOS app:

Why don’t we automatically apply these negative matches?

You might wonder if we can identify these negative phrase match opportunities, why don’t we automatically apply them?

As negative phrase matches can exclude a wide range of future search terms - this is a situation where we believe you need a human in the loop to make the final decision. But you can lean on Perpetua to analyze conversions, click-through rate, conversion rate, average order value, etc across your data to find these terms.

If you want to read more about how our Data Science team used Natural Language Processing and Statistical modeling to build a model that identified these keywords - read up on our tech blog here.

And if you want to learn about how you can use Perpetua to accelerate your growth, reach out to us at hello@perpetua.io