Looking at how efficiency is measured internally within a business and then breaking out all of the components within that allows you to identify the biggest pain points, the best areas for growth, the areas with the largest potential for improvement and more.

Let’s think about conversions. As a key metric, you might want to compare conversions over two different time periods. At its simplest, this could be reported as a raw number, e.g. “conversions rose by 15”.

A slightly more sophisticated method could use a table to display the change in conversions over that period alongside some other key metrics, using raw numbers and percentage changes, as shown in the image below:

The grey bars on the far right and left compare conversions at the two different time periods. In between all of those are a number of other metrics. These are carefully selected micro-factors that feed into the change in conversions. A purple bar represents when there has been a positive change in one of these metrics that would have supported driving an increase in conversions. A yellow bar represents an area where there has been a negative change that has hindered performance.

This visual representation makes it clear to identify specific pain points. In the example above, we can see that a drop in conversion rate has occurred over the time period, while click-through rate also saw a very small drop. The impact of these factors has been outweighed however by a very large uptick in estimated searches, leading to an overall rise in conversions.

This quick identification then helps facilitate a further conversation around account management and strategy. Breaking down results in this highly visual but also granular way can save time in daily reporting; making trends easily identifiable at a quick glance. It also makes them perfect for sharing performance insights with those less familiar with or more removed from in-platform metrics, helping for example to tell a story to stakeholders that can be clearly and illustratively explained.

The ‘controls’ area at the top of your ‘Performance Decomposition’ tab allows you to influence what your report shows.

This dynamic reporting gives the ability to explore specific areas of your accounts and understand what has driven performance at a very granular level, without having to create or work through several pages of reports.

Controls: Entity Selection

Account: if you have set up your sheet to work across multiple accounts, here you can select which of those you wish to show the data for.

Campaign filter:

• Selecting ‘show all’ here will show data from your entire Google Ads account.
• Very often however it is useful to break down your performance to deep dive into what is happening in specific areas. To do this, you can use the ‘contains’ or ‘does not contains’ filters. How you choose to use these depends on the naming convention you have set up in your account.
• An example may be that you use the ‘contains’ filter and type ‘shopping’ in the box alongside, to show only performance for shopping campaigns, if your naming convention allows.

Decomposition metric: select the metric whose performance you most want to understand and breakdown. This is the metric that will show in the grey bars on your chart. You can choose from:

• Conversions
• CPA
• Conversion value
• ROAS
• Conversion action: the values listed here will update dynamically according to the conversion actions available in your given account. It will usually be most helpful here to view data for the primary conversion action in your account however; understanding the performance of any secondary metrics can sometimes go a long way to understanding your full funnel journey and breaking down performance at a deeper level.

The chart can show a breakdown for only a single action at a time. If you have multiple primary conversion actions in your account, you will have to view this separately.

Controls: Period Selection

Under period type, you can select a fixed period type (last 7 days, last month etc), or custom.

When selecting a fixed period type, you will see the top right box populate with three comparison options: previous period, previous period (-1) and (-2). In practice this means that if you are in September and select last month vs previous period, you will be looking at data for August vs July. If you select last month vs previous period (-1), you will be looking at data for August vs June.

If you choose instead to use the custom period, you may enter the dates you wish to compare into the rows below. Ensure you use the format shown (DD MMM YYYY). Note that while you can compare any time periods of your choice, comparing periods of an equal number of days will usually provide the most fair comparison of data.

Once you have completed filling in the details in your “Controls” tables, hit “Run” at the top of your sheet. The first time you do this you will be prompted to authorise your script – hit run once more after doing this to populate your sheet.

Performance Overview

This is another interactive table, that time lets you decide which metrics you want to view data for – you can view up to 7 at a time.

Clicking the drop down arrows across each column enables you to select a metric – you may select from a choice of 12. This will then show the values for that metric for the time period you have selected.

The final row (∆%) shows the percentage change between the two periods being compared.

Decomposition metrics

Below that, the decomposition chart is viewable – refer to the section above ‘Reading a decomposition chart’ for more details on interpreting the data shown there. A further explanation is shared in the video linked above.

One consideration to make when using this tool is the way the data export works from Google Ads. In instances where you are running campaigns that do not have the ability to export impression share statistics (for example, Performance Max campaigns) it is assumed that these campaigns have 100% impression share.