The best FREE e-commerce Looker Studio template for Google Ads with performance predictions

Each of you has faced the challenge of creating a universal and well-thought-out report for e-commerce Google Ads accounts, but all the available ones online have a number of shortcomings.

We've decided to fix this and have created an all-in-one e-commerce Looker Studio template that will help everyone (link to its free usage at the end of the article, but I recommend familiarizing yourself with its capabilities by reading everything).

Who will benefit:

1. PPC specialists (in-house and freelancers)
2. Digital agencies
3. E-commerce brands and their teams

Let's break down how to work with it and what it consists of.

First of all you need to select the Google Ads account you want to analyze from the dropdown list.

IMPORTANT! Before analysis, select the key conversion action you want to use for analysis (usually this is a purchase), as by default, due to the features of Looker Studio, all conversions are pulled into the report, including secondary ones, such as add to cart, etc. You can also analyze them separately.

The report consists of two menus and filters.

The horizontal menu contains filters, where you can select specific campaigns, campaign types, regions, date range and devices to analyze only them.

The vertical menu allows you to switch between different report pages and also ask us questions in case of difficulties.

Now let's look at each page.

"Overview" page

In the diagrams, we can see the dynamics of key metrics: cost, revenue, conversions, as well as the trend over the past period (highlighted in light green). At the bottom, there are 12 main metrics for analysis, including AOV (average order value), as well as Google Ads attributed gross profit (revenue minus cost).

"Budget" page

This tab allows you to assess budget utilization for the selected period. We take the daily budget, the number of days, and thus calculate the total planned expebudget and compare it with the actual cost. Here you can identify overspending or underspending.

"Campaigns" page

The table view allows you to filter campaigns as needed and analyze individual performance metrics.

"Devices" page

This page allows you to assess the distribution of revenue and conversions among devices, as well as compare their performance.

"GEO" page

Similarly to devices, you can analyze geography. Pay attention to the drill-down arrows, allowing you to switch between city/state/country levels, as well as optional metric selection for the graph.

"Products" page

A very important report for any e-commerce business is the analysis of all products and their key metrics. Here, there are also necessary filters at the top of the page, as well as a filter by product title.

"Keywords" page

At last, you can easily and quickly compare the performance of different match types and see the impact of QS on revenue and ROAS.

And, of course, there as a table where you can filter and compare each keyword.

"Time" page

Using the drill-down menu, you can easily compare hours, days, weekdays, weeks, months, and years.

"Forecast" page

Our favorite tab. These metrics cannot be seen in Google Ads. At most, there are custom columns, but they lack visualization and charts, which is the main uniqueness here. Here we predict monthly performance.

The anticipated month-end outcome comprises the combination of two metrics:

1. The actual results accumulated from the beginning of the month up to the current date.
2. Projected results for the remaining days of the month, extrapolated based on the performance of the preceding 14 days.

For instance, suppose today is April 4th, and within the initial 4 days of the month, you've already achieved $400,000 in revenue. Over the past 14 days, revenue amounted to $1.68 million, averaging $120,000 per day.

We consider 14 days as optimal. A 7-day period may not capture all conversions yet, while 30 days is too extensive for a dynamic market.

With 26 days remaining until the end of April, we anticipate an additional $3.12 million ($120,000 * 26).

Consequently, our forecast stands at $400,000 (actual) + $3.12 million (extrapolated) = $3.512 million.

The dashed line on the graph indicates the point at which we achieve the forecast.

The light green line reflects the trend from the previous month, while the dark green line illustrates the trend for the current month.

The beauty lies in the daily data updates, refining the forecast's accuracy as the month progresses.

The report is free and accessible to everyone via the link provided here.

Any feedback and ideas for improvement are welcome!

P.S. The report is continuously updated and enhanced by us in real-time.