Advanced Negative Strategies For Improved Paid Search Performance: Part II
As discussed last month, negative keywords are an extremely important part of any top performing paid search program. Negative keywords help marketers both avoid non-converting impressions as well as shape traffic for better converting results. Implementing “Match Type Silos” Before I delve into new tips, I got a number of questions in response to last […]
As discussed last month, negative keywords are an extremely important part of any top performing paid search program. Negative keywords help marketers both avoid non-converting impressions as well as shape traffic for better converting results.
Implementing “Match Type Silos”
Before I delve into new tips, I got a number of questions in response to last month’s suggestion to create “match type silos,” so I want to provide a bit more detail on how to implement this approach.
Creating match type “silos” by using a different AdGroup for each match type enables advertisers to force Google to trigger the correct keyword match type combination that triggered the user’s raw query.
Using this approach, if there is a keyword in the account matches the raw search term exactly the exact version (and related creative and landing page) will be triggered and, if a keyword in your account contains the phrase searched, the phrase version of that keyword will get the impression and finally, broader searches will trigger the broad keyword AdGroup.
While re-organizing AdGroups, and managing multiple instances of the same term might seem daunting, this approach isn’t very difficult to deploy. We suggest using copy-and-paste in Excel to build bulk sheet, or for larger scale campaigns, creating a quick Excel Macro to create the iterations for you.
Once you have created these lists in Excel, you can quickly create match-type gropus with a bulk upload.
The real challenge with this approach is maintaining this structure as you add and pause keywords by editing all three groups each time. In order to make the match type silo structure manageable after creation, I suggest using it solely for your highest volume ad groups.
Use Negatives To Shape Traffic & Avoid The Broad Match Trap
“Traffic shaping” is an advanced negative strategy used to ensure that the most relevant keyword is shown when groups represent different levels of detail or themes.
For example, consider a campaign that has two keywords in separate group. One keyword is ‘pet supplies’ and the other keyword is ‘San Jose pet supplies’. The generic keyword ‘pet supplies’ is in a group with generic ad copy and directs traffic to a generic landing page.
The other keyword, ‘San Jose pet supplies’ is in a group with location specific ad copy and benefits from a geo-specific landing page with a unique local message to appeal to the residents of San Jose.
A typical search query might be ‘best pet supplies store in San Jose’. With this search, the advertisers risks Google serving the generic keyword with the generic ad, which doesn’t best match the user intent and could deliver poor results. However, if the query triggers the ad for ‘San Jose pet supplies’ chances are the user will be more likely to click and convert.
Broad and phrase match keywords can help Google match searches to the most relevant ad. For example, adding the negative keyword ‘San Jose’ to the generic group will ensure that the San Jose themed ads will appear over the generic ad when a search could have otherwise matched either group.
This strategy should be used when the following criteria are met:
- There is a strong difference between landing pages
- The ad copy is very targeted and extremely relevant to the keywords in a group.
- Evidence of poor matching is seen in the Google Raw Query Reports.
Negative shaping is an advanced strategy and caution is recommended when implementing this because the wrong negative can significantly cut down volume.
Quick Tip: To help this process, Jellyfish Online Marketing suggests using case to differentiate between the types of negative keywords you are using. Because keywords are not case sensitive, this won’t affect the campaign, but gives you a quick way to differentiate the keywords. For example, regular negatives i.e. those that stop unwanted traffic can be lower case and negatives that are designed to silo match types or shape traffic to the appropriate group can be marked with upper case letters as the example below shows.
Xbox 360 Phrase Adgroup – Google
Don’t Forget To Think About Plurals!
One common misconception is that Google’s negative broad match is similar to how Google’s regular keyword broad match behaves when matching traffic. For example, a broad match keyword ‘car’ will also broad match to queries that contain ‘cars.’
However, the negative match types work differently; if a boat rental company wanted to block queries for users looking for cars instead of boats the marketer will have to add the word ‘car’ as well as ‘cars’ as negatives. The problem is further exacerbated if you have lots of multi-token negative keywords because then even more variations are needed.
Continue Expanding Negatives As You Scale
Refining clicks driven by broad and phrase match terms are more than just an ancillary step, it is an important piece of maintaining profitability as you scale your search program. Each time you add new keywords, don’t forget to think about how they will affect your negative keyword list.
Are they going to lead to new, unrelated search queries that should be eliminated with negatives? Or, if you product offerings have expanded, should you remove some negatives that prevented your adds from showing before you offered this new product or service?
Proper negative management involves careful planning and a mindset of continuous improvement. Whether the goal is to increase conversion rates, grow revenue, or increase profits, negative keywords are a simple tool allowing marketers increase efficiency in the marketplace.
Contributors: Special thanks to Jellyfish Online Marketing, a pay for performance media for sharing their tips on negative keyword management.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.