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Case Study: How Negative Keywords Can Pump Up Paid Search Performance
Once campaigns reach a certain size, successful paid search marketing becomes less about generating traffic and more about identifying and driving the highest value visitors. At the same time, however, scale makes creative testing and ad group refinement difficult to implement across hundreds of thousands or even millions of keywords.
In a high-volume world, actively managing negatives is possibly the single most impactful opportunity you have for increasing conversions and decreasing costs.
Keyword building is a continuous process for both positive and negative keywords. If you have not been regularly managing your negative list, chances are that you are getting some “bad impressions” on your paid search ads. Bad impressions are instances when your ad is served to a consumer whose search term is not going to lead to a valuable conversion for your business.
Negative Keywords In Action
Let’s use a sporting goods retailer as an example: assume a consumer searches for “road bike repair” and gets served an ad set on phrase match for the keyword “road bike.” Since the consumer is looking for something the retailer doesn’t offer, even if they click on the ad they are highly unlikely to convert.
Using negative keywords to eliminate these bad impressions will help cut unnecessary cost and improve ROI, but the benefits of negatives go far beyond simple cost reduction.
Let’s look at an example of how adding negatives can deliver impressive results. PowPow Sports has a paid search campaign that is driving both good and bad impressions, each subset of which performs differently as described in the graphic below.
To eliminate these bad impressions, PowPow Sports used negative keywords to get rid of irrelevant and non-converting terms. Raw search query data is a great way to identify potential negative keywords that are driving bad impressions from broad and phrase match terms.
Review this report specifically for queries that are irrelevant to your business, and add these terms to your negative keyword list at the campaign or even account level to eliminate non-converting impressions.
Pruning your keyword list should have a significant impact on overall campaign performance. Going back to the PowPow Sports example, look at the table below to see the impact of eliminating the bad impressions from irrelevant keywords.
Because the click-through rate was low, and conversion rate was zero for the bad impressions, adding negatives significantly improved the overall financial performance of the campaign. PowPow sports is paying for less clicks but still generating the same number of conversions.
But that’s not all, eliminating irrelevant searches boosts the click-through rate, which typically increases quality scores. This improved quality ranking provides even more reduction in cost as well as improved ad position, driving more traffic and conversions.
Finally, the increase in conversion rates from existing terms allows you to bid more for keywords, reinvesting the money you have saved from bad impressions into high performing terms.
With higher bids comes higher average positions and increased revenue, while maintaining consistent spend levels. This virtuous cycle of lowering costs per click, while at the same time increasing quality and position, results in a win-win for the marketer: increased revenues and ROI.
Eliminating unwanted impressions and clicks from your paid search program is more than just a nice to have; it is becoming increasingly critical for your bottom line. Most optimization efforts require investment – raising bids to increase position, adding keywords to acquire more traffic, or even the opportunity cost of spending time testing creative.
Negative keywords, on the other hand, are an efficient way to decrease costs while increasing ROI and top line revenues. As you consider options for optimizing paid search, eliminating non-converting impressions with negative keywords should top out your list as one of the best investments money can’t buy.
Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.