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Visualizing Quality Score - Google/Bing PPC Optimization Strategy

08 Aug 2020

Quality Score is undoubtedly the core anchor of your Paid Search performance. Knowing how to control and influence it to your benefit determines whether you win or lose against the competition.

While you can analyse the performance in your Keywords' quality score performance table in Google Ads / Microsoft Ads, it can be difficult to identify the right place to start. 

That's where visualizing the data can be useful, not just in identifying where to start but also to present to stakeholders on why and how the actions are being taken.

To start, we'll talk about the methodology.

Components of Quality Score

There are two main components of Quality Score on Paid Search / PPC:

  • Ad Copy Relevance
  • Landing Page Experience

In simple terms, Ad Copy is the onus of the account manager, PPC agency or copywriter, while Landing Page is the onus of the client, landing page or website UI/UX designer.

It's useful to analyse these separately, as it'll determine who takes the action to improve on it.

From my experience, Landing Page has more influence on the Quality Score vs Ad Copy. One step improvement from "Below Average" to "Average" can bring a +2 in Quality Score, but the same for Ad Copy usually only brings a +1.

By analysing the ad group's Ad Copy Relevance and Landing Page Experience's distribution, we can then determine:

  • where to start (i.e. which ad group to prioritise)
  • who is responsible to improve on the quality score (ad copy and/or landing page)

Visualization Case Study

After trying out different visualization, I find that a Heatmap is the easiest and the most visual representation of Quality Score components.

Here is a way to visualise it:

Quality Score - Ad Copy Relevance Analysis

How to read it:

  • Each number indicate the number of keywords in the ad group that falls in the ad relevance score buckets (Below Average, Average, Above Average)
  • The colour corresponds to the number and its range applies to the entire dataset (i.e. not by rows)
  • Keywords that do not have quality score are not represented in this chart
  • Impression Volume & Spend are not accounted for here! It's useful to complement this analysis with an understanding of impression volume & spend.

Here we can see 3 groups that will need some work

Group A

We can assume just by looking at this chart that this is the top volume ad group, as it has the most number of keywords with Quality Score.

As it's the top volume one, despite its relatively good performance compared to the rest as it has a large proportion of keywords in "Average" vs the rest, a bit of improvement on those "Below Average" will go a long way as it's the highest volume group.

The sensible approach is to:

  1. Improve the ad copies in the ad group to cater for those keywords in "Average".
  2. Split the keywords in "Below Average" to another ad group with their customized ad copy, or pause them if their volume is negligible.

Group B

These groups tend towards the "Below Average" but a small proportion does fall under those higher buckets.

This indicates that the ad copies in the ad groups do not cater for most of the keywords in the ad group.

Hence, this can be corrected by having more ad copy variations to cater for the different keywords (Responsive Search Ads might help). Dependent on the volume, splitting the keywords out might make sense too.

Group C

This is the most serious one as all the keywords are in the "Below Average" bucket for Ad Relevance.

However, this is easily corrected by having a total overhaul of the ad copies in the ad group.

 

Upon doing these changes, it's useful to run the visualization again to determine the progress of the optimization. The same visualization can certainly be done for Landing Page Experience too.

Final Thoughts

Sometimes it can be easy to analyse but difficult to execute, as the stakeholders might want the copy to mention certain things or structured in a certain way.

Other times, you might want to bid for keywords you can't mention in the copy e.g. competitor brand/product names.

Hence, it's important to pick your battles and determine the leeway for CPC. Double-down on the keywords with less competition or those where your Quality Socre can be maximized while leveraging it to subsidize on the weaker performance of the keywords with high competition and/or low Quality Score.

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