The state of Adwords Advertiser Accounts have changed over the years where it was once very common to find an account without negative keywords and now it is rather uncommon. In time, advertisers have either become savvier to Adwords best practices or they have hired agencies to implement strategies.

But how far have they really evolved?

I can tell you for certain that the Google’s profit algorithm has evolved even further and is always 10 steps ahead of its advertisers. So my job is to make sure you guys are keeping up with the times.Search queries happen to be a major part of the account research we do here at our ppc management company. Looking at what people actually type into Google tells us a lot about the visitors you are attracting and what they are looking for. Routine search query analysis is a paramount component for many advertisers but we feel most have just gone part of the way to maximize its usefulness.

3 Things to Analyze with Search Queries

Irrelevant Queries-This is the area where we’ve actually seen progress from Adwords’ customers. They pull a [Search Term] report, look through it, and add negative keywords for any irrelevant searches. Easy enough.

Incorrect Adgroup-This is where we start to see major problems. Incorrect adgroups refer to when the search query is relevant to the business offering but not the specific adgroup it is in. When this happens, the visitor can sees the less targeted ad and; if clicked, is sent to the wrong landing pages.

Example: query=dark bold coffee when adgroup=light body coffee; you might sell them both but you want the dark bold queries to go to the dark bold page, not the light body page.

This error is commonly overlooked because when Adwords managers review the query list, they are looking for discrepancies in the query defined but not which adgroup it belonged to. Problems with incorrect adgroups lead to lower CTRs, lower quality scores, higher CPCs, higher bounce rates, higher conversion costs, etc. A process which guides traffic down the appropriate avenues will have a positive impact on the account.

General Queries-This is the easier fix but often a more dangerous culprit. General terms tend to have more volume, competition, and cost associated with the clicks. So when general terms are plagueing the account, they are often putting a big dent in the wallet.

General terms can describe your business offering in either an overly vague sense or a more general category sense. When queries are general, it helps to evaluate how general it is and if it should be considered a candidate for your keyword list.

Example: query=coffee beans when adgroup= light body coffee; you certainly sell coffee beans but maybe they want to see the entire coffee selection of light and dark body types.

When general queries go to specific landing pages, the visitor often mistakes that page for the entire product offering. They are more likely to bounce and have the same negative effects as incorrect adgroup discrepancies. They are actually one in the same.

Sometimes you find that a general query doesn’t refine the visitor to be qualified enough to be a good paying customer for you. In this case you don’t want your ads to show for general queries. For example, “coffee” by itself might be too general for your taste (pun intended) but you would like ads to show for “gourmet coffee” and “dark roast coffee.”  Negative exact matched keywords are in order for these. i.e. [coffee]

When attempting to lower high conversion cost, it is important that you take all the preceding steps to lower conversion cost before applying match settings. Match setting will likely result in lower traffic and consequently lower sales volume. If you race ahead and apply match settings prematurely, you might forgo the opportunity to lower conversion cost without lowering traffic and sales.

This is disastrous because once you apply the match settings, you won’t be able to receive as much feedback from search query reports that could help you better qualify visitors to start. Also, you will effectively be taking other underlying problems having to do with inefficiencies in the website and just shoving them under the carpet. In other words, if we apply match settings simply to lower conversion cost quickly, you might lower your conversion cost and not be motivated to fix the other lingering inefficiencies in the campaign or on your site.

So when is it a good time to apply match settings? I recommend applying match settings in 2 scenarios:

1) The Conversion Cost is way above your target CPA (cost per acquisition/conversion) AND there are alot of single occurrences of irrelevant variation appearing in the search query reports that is too difficult to control with negative keywords.

2) The budget is extremely limiting compared to available impressions and you want to make sure the clicks you do pay for go toward the exact or phrase match variation of the keyword.

Testing ad variations simultaneously should always be done in the first scenario since the objective is to lower conversion cost. You’ll want to make sure you know which match setting variations are going help you achieve your desired CPA before you rule out any of them.

To run you through a short example, let’s assume the Target CPA is $50 per conversion. Historically, you have been running this particular keyword at $120 per conversion which is totally unprofitable for this product. (You know it is unprofitable because the keyword describes a product that you could never make a profit on by paying $120 to advertise it.) You have tried optimizing your website for a higher conversion rate and also applied necessary keywords but the conversion cost is still too high for the keyword.

It’s time to test out some match settings. You might do this for several keywords with higher conversion costs so be prepared to test multiples.

Keyword Before Match Setting Variations

Keyword = $120 per conversion

Keyword After Match Setting Variations

Keyword (Broad Match) = $170 per conversion (Conversion cost is likely to go up because phrase and exact match settings will trigger most of the very relevant queries and their volume.)

“Keyword” (Phrase Match) = $60 per conversion

[Keyword]  (Exact Match) = $ 48 per conversion

I would advise everyone to let the data population add up before making any official assessment about the new conversion cost stats. The above example portrays the possible outcomes of three different match settings. After enough clicks have accrued and we see numbers like the ones above, I would either pause the broad match version or isolate it into another campaign with a smaller budget. I am always hesitant to simply pause out words because a huge lack in visitors could shock the system resulting in extremely low sales. If you isolate these words, you can lower its spend and try and work on its conversion cost later through other methods.

I would keep the phrase and exact match even though the phrase is still above the target conversion cost. It’s much closer now and you can continue to work on it. You might find you can get it down to the actual target with some more negatives and ad text qualifiers.

With broad match setting out of this campaign, you have effectively freed up some of this keyword’s wasted budget allocation which can now be spent on profitable keyword click costs. The result is more profitable sales and overall net returns.

DISCLAIMER: In my experience, advertisers claim to be focused on conversion cost but tend to be even more sensitive to total sales volume. The above techniques are designed to lower conversion cost but could and probably will result in lower but more profitable sales volumes.

My only disclaimer is that advertisers who are specifically going to Analytics for answers of what to change in their Adwords account might be quick to jump the gun before learning all the answers. I want to remind you guys that Analytics should be used, not as a change agent, but as a tool that allows us to get the entire story about your campaigns before making any decision at all. In other words, we use Analytics to paint the entire picture so that we can process all the information and eventually come to a justifiable conclusion about what is actually happening when people visit our website.

So for the purpose of this segment, I only want to give you tools that might help paint that picture clearer for you. In reality, everyone who follows these steps will achieve different results that will eventually demand different actions. What you learn today might be change the way you see your campaigns and even your business. Once the picture is clearer, what you do about it should become clearer too.

Note: Because Google Analytics contains information about your website from all referring sources, it is important that you observe the correct source segment (Adwords or Google) and compare to others.

1. Explore Bounce Rates in Comparison to Other Referring Sources

2. Explore Exit Pages (Top Exits and Percentages) in Comparison to Other Referring Sources

3. Explore Average Time on Site

4. Examine Content Page Views and Sort by Source

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Great job. By now you should have a stronger approach to Analytics and because you have more of the story, your decisions will be more informed and you won’t put yourself in a bad position because you took action prematurely.