This is the third part in our series on Google AdWords’ Quality Score. The first was a general overview of QS, while the second looked at landing page factors that can instantly torpedo a keyword’s Quality Score. This article, the final one in this series, will look at how to analyze a keyword’s QS and how to raise one that is lower than desired.
One great way to analyze AdWords data is to use pivot tables in Microsoft Excel or Open Office Calc. Pull a report including the keyword, ad group, impression data, cost data, and Quality Score. Using a pivot table, it is relatively easy to find ad groups with a high cost and low QS overall. With this data, it becomes easier to fix problems and write better ad copy.
With so much data offered by AdWords, it is a great idea to look at the normalized Quality Score. This can be done by Ad Groups with a simple formula that can easily be calculated in Excel:
Normalized QS = (Quality Score x Impressions) / Impressions
Excel is also good for looking at low-volume AdWords data. Some keywords may not get enough impressions to give a good indication of QS. Filter just the Quality Scores from 1-4, then create a pivot table including the Ad Group, Quality Score, and Cost. This will aggregate the data and make it easier to analyze.
Generally a 7 or higher is considered a good Quality Score which does not need more work. It is usually not worthwhile to bring a QS7 to QS10 unless it is a very high-cost industry where every penny counts. A Quality Score between 1 and 3 indicates a landing page problem, which would bring into account the eight factors we looked at in Part 2 of this article series.
One way to keep track of changes in QS is to schedule keyword reports to be sent to an email address once a week. This will show the Quality Score of keywords at that point in time, so it will be a matter of simple research to find when a QS dropped for a particular keyword. Also, looking at the Change History in Google AdWords itself can indicate if there have been any unexpected changes in the account.
When attempting to raise Quality Score, organization of keywords and ad copy is essential. Since a higher Click-Through Rate leads to a better QS, CTR is a logical starting point. With low CTRs, writing different ad copy may be an easy fix, or adding more keywords to a new ad group. A/B testing of new ads is also a strategy to improve CTRs.
The relevancy of the landing page may also need to be evaluated. This can include looking at how relevant the content on the page is to the ad copy and keywords, and testing new ad copy that more closely echoes the message on the landing page.
It should be noted that Google updates Click-Through Rate numbers daily, while relevancy is updated ten times per quarter. Landing page factors are updated every six weeks. If Quality Score does not increase after changing the landing page, this may be completely natural. It will take Google days or weeks to update the relevancy numbers and reflect them in the Quality Score.
If you notice that Quality Score has dropped, the first factor to look for is exactly what date it dropped. This is why we recommend scheduling weekly reports with this information. Then, examine the change history of the account, checking for site changes especially. Also, look for any changes in the natural search results, and use the AdWords Editor’s notes function to look for changes.
Then, look at the relevancy between the keywords, ads, and landing page content. Break down the keywords and look at their Click-Through Rates, looking for changes. Finally, look at the landing page itself, examining keyword-landing page relevancy. The Google AdWords Keyword Tool can help identify related keywords, while Webmaster Tools can help identify crawl or page load problems.
Typically, a drop in Quality Score will quickly reverse itself. Google may have crawled a site when it was down or slow, or recent news may relate two usually unrelated keywords. Recovering from a QS drop is usually easier than increasing a new keyword’s QS, but both can be done. Using a spreadsheet application to dig into this data is also vital for increasing AdWords Quality Scores and optimizing a pay per click campaign.