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Page Views, Time On Site & Bounce Rate Reveal Changes In Quality Score & Revenue

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 google adwords (2)About Quality Score

Quality Score in Google AdWords is an indicator of the quality of your ad campaigns, ie. the quality of your advertisements, keywords and landing pages. The Quality score can be accessed by the following path:

Google AdWords—–> Campaigns—–> All campaigns——> Keywords

In the Keywords table, the Quality Score and its elements( Expected Clickthrough rate( CTR), ad relevance and landing page experience) can be seen by clicking on the white speech bubble next to the keyword status. See the picture below.

The more relevant the advertisement and the landing page to the user, more will be the likely Quality Score. Quality Score is measured on a scale of 1- 10.Google Quality Score

Understanding Quality Score

The Quality Score is given to each keyword of the campaigns. It indicates the quality of the ads and landing pages that are triggered by that keyword. A high Quality Score, therefore, means that the ads and landing pages are more relevant to the user looking at those ads and landing pages. It also includes factors such as loading time of landing page, ease of navigation, quality  of content to the user etc.

However, please note that the Quality Score is not used to determine the ad rank during the time of auction. The Quality Score components are given qualitative values like ‘average’ or ‘above average’. The ad rank, ie the position where the ad will be displayed is determined by the auction time parameters of Quality Score( these depend upon other factors like actual search terms used, type of device, location, time of day, language preference etc. ) and factors like bid value.

However, the elements of Quality Score show a  strong co-relation with the ad rank and by improving these factors, you can expect an improved ad rank.

  • Your ad’s Expected clickthrough rate: This depends partly on the historical clicks and impressions data of your ad. Improving this will improve your quality Score and hence the ad rank.
  • Ad relevance: How relevant the text of your ad is to the person searching.
  • Landing Page experience: How relevant, transparent and easily navigable your landing page is.

Thus, we can conclude that Quality Score is an important predictor of the success of your PPC ad campaigns. Having a higher Quality Score will result in lower marketing cost as AdWords charges lesser if the Quality Score is higher. It also gives a better position to the advertisement.

Revenue per click( RPC)

Revenue per click( RPC) determines the success of the PPC campaign in terms of total revenue.

Thus, Quality Score and Revenue per click are the two parameters which give us the success of a PPC ad campaign.

However, we find that the components of Quality Score- Landing Page experience and ad relevance are quite abstract and unquantifiable. Even though CTR is quantifiable, it is a historic parameter. Hence , e need to define better and quantifiable factors that determine the Quality Score so that we can predict the outcome of our digital marketing efforts.

Here web analytics comes to our help. Google Analytics gives the metrics of pages per session, session duration and bounce rates in its audience overview.

audience metrics

Benjamin Vigneron, a digital marketing strategist, ran a multiple regression analysis between the factors of page views, CTR, session duration and bounce rates with Quality Score and Revenue per click( RPC) for millions of keywords. His findings were as follows:

Findings (Quality Score )

Bounce Rate

Bounce Rate had the highest effect on the Quality Score accounting for 2.6- 3.9 of Quality Score points. A high bounce rate( above 40%), guarantees a Quality Score of less than 7. However, a low bounce rate does not necessarily guarantee a high Quality Score, as per Google.

CTR

The CTR was the second strongest predictor of Quality Score accounting for 1.6- 2.4 Quality Score points.

Time spent

The time spent on site accounted for 0.2- 0.5 Quality Score points.

Pageviews

For pageviews, the data was not statistically significant.

Thus having established relationships between these parameters with the Quality Score, we can predict the changes in Quality scores depending upon the changes in these parameters and thus can have a clear- cut strategy for improving these quantifiable parameters.

The objectives can be stated in quantifiable terms such as ‘Target those campaigns for improvement that have high bounce rates, below average CTRs and below average time spent on sites as these campaigns have high Cost per click( CPC) and low impression shares’.

Findings( RPC)

Bounce rates

Bounce rates are even stronger predictors for revenue than for Quality Score with with 61% – 100% degree of association with RPC.

Even if low bounce rates do not guarantee higher Quality Scores, in case of RPC, low bounce rate does guarantee a higher revenue. Thus Bounce rate is a very important determinant of RPC.

Pageviews

Page views were associated with 22%- 39% of RPCs

Time on site

Time on site were associated with 4% -7% of RPCs

Thus we can address the challenge of low revenue ad campaigns by predicting the RPCs according to changes in these engagement metrics and then take suitable decisions obtained from these insights.

Conclusions

  • Easily derivable metrics from Google Analytics like pageviews, Bounce rates and time spent on sites can be used as proxies for abstract metrics like Quality Scores or for RPCs.
  • Changes in Quality Scores or RPC can be predicted using statistical techniques depending upon changes in these Google Analytics metrics.
  • Drives can be undertaken to improve these Google analytics metrics so that the end metrics of Quality Score( indicating impression ratio and cost per click) and RPC( Total revenue) can be improved.
  • The ‘Bounce Rate’ was the most important factor for both- Quality Score and RPC. It affected RPC more than Quality Score. So reducing Bounce Rate could be a good strategy to get a higher Quality Score and Revenue. Thus we get an actionable insight using Google Analytics.
  • Time spent on site and pageviews, indicators of ‘landing page experience’ also influenced both – Quality Score and RPC.

Conclusion

Thus we can conclude that Google Analytics is a powerful web analytics tool that gives actionable insights.

Image courtesies: Google AdWords, Google Analytics

Data Courtesy: http://searchengineland.com/pageviews-time-site-bounce-rate-predict-changes-quality-score-revenue-227898

  • web-analytics

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