PPC Investigator - User Guide

As account managers, we are frequently asked questions around why an AdWords or a Bing Ads account's performance changed. For example, Why did conversions/clicks drop last month? The PPC Investigator answers such questions by finding exactly which element in an AdWords account caused a metric to increase or decrease. Is it a keyword, placement, or an entire network that caused the change.


How does it work?

Select the metric for which you noticed a change and choose the date range over which you want to compare performance. The system will display two different tabs that will show different levels of detail.


Cause Chart

This feature is available for analyzing AdWords and Bing Ads accounts. The concept of the Cause Chart is based on the fact that the performance of every metric depends on the performance of other underlying metrics. In the Cause Chart, we use the relationships between different metrics to show potential causality.

In the example below, clicks have decreased (highlighted in Red) and its cause can be determined by analysing the underlying related metrics: impressions and CTR. In this case it shows that CTR has increased (it’s Green). Now, we can check the other underlying metric - impressions - which shows a drop (it's Red). Further down, we can observe an increase in impression share (IS) lost due to ad rank on display and search network. This is most likely the cause for the decrease in impressions and clicks. 

Another interesting observation is the decrease in the impression share(IS) lost due to budget on search network which means that the account has enough budget. On collaborating results from the Search Lost IS from Rank and Budget, we can improve the ad position by improving the quality of the ads and by increasing bids.

On the whole, we can observe that there is enough budget available in this case, which can be used to increase bids to get a better ad rank -> higher Impression share -> more Impressions and better ad position which can further improve CTR and cumulatively increase the clicks received.  


Root Cause Analysis*

After identifying which metric needs to be worked on, the Root Cause Analysis goes a step further and highlights the exact Campaigns/Ad groups/Product partition/Keywords etc. that were responsible for the change in an Account. 

It shows top movers that are significant contributors to the change in the account when compared across the two date ranges. You can view the top three positive and negative movers for a particular account. These can be further broken down to sub-contributors to check where exactly the drop/surge happened. The tool finds the contributors by taking into consideration individual keywords/ad groups/network/device and even specific combinations like keyword+device or network+ad group. 

Insights from the snapshot:

  • Optimization - New (Campaign) seems to have received a lot more traffic from Tablets and Mobile devices which led to an increase in clicks.
  • Brand (Campaign) saw a 90% drop in clicks. Such a huge change may indicate that the campaign was paused or some other big change was made. 
  • Tools (ad group) saw a drop of 88% in clicks and the system shows that the "optmyzr" keyword in the ad group contributed to a drop of 95% in clicks. Using this information, we can further investigate what caused the huge drop in clicks for that keyword. Was the keyword paused, moved to a different ad group or, saw a huge change in Quality Score.

Positive Top Movers 

This shows the Campaigns/Ad groups/Product partition/Keywords/etc that had the highest increase in the metric that is being investigated. These elements had the highest contribution in increasing the metric across the account.

Quick insight tips from this section:
1. Easy to recognize what is working well for the account in order to replicate it in other campaigns or ad groups. For example, if mobile as a device shows up as a top contributor for an ad group, you can consider setting mobile bid adjustments for other ad groups.
2. A growth of Infinite% indicates that the contributor is a new addition to the account. For example, if you created a new campaign that led to a huge increase in conversions, it may show up here.
3. Easy to identify which level is contributing to an increase. For example, Campaign A saw a growth of 100% and its ad group X saw a growth of 160% and its keyword C saw a growth of 188%, this can help a user identify the cause for the increase right down to the keyword level.

Negative Top Movers

This shows the Campaigns/Ad groups/Product partition/Keywords/etc that had the highest decrease in the metric that is being investigated. These elements had the highest contribution in decreasing the metric across the account.

Quick insight tips from this section:

1. Identify the pain points and work on improving it in the account to counter the decrease in account performance.
2. A 100% change may indicate that the Campaign/Ad group/Keyword may have been paused which is impacting account performance. So, this can help make a decision on whether you would like to enable it or keep it paused. Also, if the 100% change is at the keyword level, then it is possible that the keyword has been moved to a new ad group.
3. Easily identify what is causing a drop in account level performance. For example, an ad group saw a 50% drop and under that ad group a keyword saw clicks drop by 100%. In this case, it is clear that other keywords in that ad group are performing well to cope with the 100% drop in clicks from the identified keyword. This helps make a decision on whether that keyword should be paused or optimized.

*Root cause analysis is not available for Bing Ads account analysis. 


Demo Video



Can’t find what you’re looking for?

Our award-winning customer care team is here for you.