Quality Score Details

The idea of a Quality Score Chart was developed in New York by a marketing agency in 1963, a devastating period in advertising days. Q-Scores were developed after many attempts to make branding more scientific by creating complex and fast measurements. These measurements gauge consumers' responses to a brand, alongside the ongoing relationships with various brands.

To arrive at these scores, companies distribute surveys to a wide range of households. The scores may calculate information about consumers or a particular demographic in general, such as an age range of 20-29 years. The brands involved are not necessarily product brands like the ones sold in grocery stores. Q-Ratings can calculate for individuals such as public personalities, television shows, sports, films, publications, kids programming, and deceased celebrities. At times, the emotional bonding Q-Score can be paradoxical in comparison with a regular one. Emotional bonding is whereby researchers look at the devotion level which people demonstrate towards a particular brand.

A Q-Score can decrease rapidly due to different views concerning the brand. For example, an actor may have a high score today and a low one next week because a particular magazine printed rumors about him. Generally, companies will aim for a high Q-Score regardless of the brand they are marketing. For example, a cereal company would like to know if people are familiar with its brand and have high respect for it. These scores also calculate when companies decide to find a new promoter or introduce a new brand.

Example of a Quality Score Chart

The methodology behind quality score ratings is relatively straightforward. Respondents are asked if they have heard of a particular brand. If a respondent is aware of the relevant entity, the surveyor asks if the entity should be rated poor, fair, good, or very good.

In a particular quality score survey for a specific brand, the following data was obtained from the choices given to score respondents.

  • A. Excellent (72)
  • B. Good (86)
  • C. Fair (102)
  • D. Poor (20)
  • E. I never heard of it (30)

Positive Q Score = (A respondents ÷ A+B+C+D) × 100, I.e., (72 ÷ 72+86+102+20) × 100 = 25.71%.

Negative Q Score = (C + D respondents ÷ A+B+C+D) × 100, I.e., {(102+20) ÷ (72+86+102+20)} × 100 = 43.57%.

Types of Quality Score Chart

  • Account-Level Quality Score - Being one of the most contentious types of Q-Scores, many digital marketers have concluded that it exists and affects all accounts. It has resulted in the historical performance of all account ads and keywords. If you are in a position where you have a low Q-Score, and you would like to improve it, but you don't want to start a new account, you should take some time to overhaul your account completely.
  • Ad Group Quality Score - Google uses ad Group Q-Score to analyze account performance. This metric can be calculated with the average Q-Score of all the keywords in each ad group. Breaking down the ad groups further into smaller ad groups targeting more on the keywords improves ad group QS-Score.
  • Keyword-Level Quality Score - Most people know this quality score type. Q-Score measures the search query performance matching exact keywords. Google takes the keyword Q-Score performance instead of a significant number of searches rating it from 1-10 depending on how it has performed. You must look at the impression share data so that you can improve the Q-Score.
  • Landing Page Quality Score - Landing page quality is one factor used in determining Q-Scores, making a big difference in any online campaign success. This is where users are directed once they click on the ads, thus making or breaking the digital marketing. Advertisers are encouraged to create good landing pages which are considered relevant and valuable by Google.
  • Display Network Quality - This Q-Score type works differently from the search network's quality score. Q-Score looks at the ads' historical performance on the sites a user is running on. Google factors Ad, keyword relevance, and landing page quality to determine the display network quality score.
  • Mobile Quality Score - Google takes this into account to calculate the distance between the users and business location by using location and location extension data. Mobile ads performance affects the mobile Q-Score, i.e., if the site is slow on mobile devices, the Q-Score will be lower.