Best practices to monitor your ads performances in Looker Studio

In this article, we'll share with you best practices to monitor your ads performances in Looker Studio / Data Studio. But in reality it could be applied to any dashboarding tools, feel free to share with friends & colleagues :)

Disclaimer: we're no ads experts (we'd be more like dashboards freaks, the kind of guys that start a Shopify business to gather real data to play with. And yes, it's been a disaster!), but working with many clients over the year (either e-commerce or agencies), we gathered some knowledge that we'll kindly share with you here.

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A yesterday KPIs page as an alarm system

As of today, Looker Studio / Data Studio does not offer any alarm system to be notified when a metric goes off the rails. It's a pity, and we hope that they will implement it soon.

Even if you've set maximum bid / spends in your different online advertising channels (shall it be Meta/Facebook/Instagram Ads, Google Ads, Twitter Ads, Tiktok Ads, LinkedIn Ads, ...), we've seen that sometimes, for an unkown reason (but more than often, a mistake from a junior team member...), it just breaks.

How to prevent this from impacting your business too much? Build a new page with just 3-5 KPIs forced to yesterday's date (with maybe a morning single-page e-mail to your inbox), with just your spends across the different tools you're using. So when you arrive in the morning, in a blink of an eye you'll know if something is off, and you'll be able to fix it quickly (for weekends, you might want to lookt at last two days).

Again, we've seen in the past, although people do have dashboards, they also have a work to do and these things can be missed very easily.

Take advantage of conditional formatting

You've got your summary table with all campaign groups, all campaigns, all ads, displaying loads of metrics from Impressions to Conversions / ROAS / ...

That's cool. But what do you do with it? Do you want to frenetically open it everyday and spend 10 hours on it?

Not really, at this stage you should use it as a support to validate your advertisment strategy, not to drive it. It should not give you answers, but more questions so you can always improve your ROI.

In order to make the most out of it, we encourage you to set conditional formatting on your most important metrics (usually spends / ROAS / CPA), so if an ad is performing extremely well, or poorly, you don't have to deep dive into every single cell to notice it.

And please, avoid color scale. You don't want all your cells to be colored, it's not a minimalist paiting we're doing here (although it looks great).

Actually, there should be very few cell colored so you know where to focus. Red if it's 30% below your objective, green if 30% above, period. Your table should bring your attention to the major variations here.

Beware of comparison and cannibalisation

Let's say you spend $100 on Facebook Ads, and $100 on Google Ads. And the return is $150 on Facebook Ads, and $200 on Google Ads. Where should you invest more? Sounds like an easy one, right? Well, damn wrong.

You're missing the cannibalisation part. Maybe that the $100 Facebook investment is generating a purely incremental $150, whilst the $100 Google investment generates $125 incremental, but $75 are robbed from your Google SEO.

How to prevent this? You know the usual metrics to track (Spends, CTR%, ROAS, ... at the end of the day you're the expert, not us), but you should look at revenue & revenue share over time, spliting free channels Vs each of your paid channels.

It's going to take some efforts to make a proper analysis, but if everytime you double your paid investment, the revenue share from paid quadruple, the revenue share from free is on free fall whilst the total revenue is only up a few %, you've got a good candidate for cannibalisation here.

Take seasonality into account to make meaningful comparison, and don't hesitate to make 2 comparisons at the same time

Most business are seasonal. It could be daily seasonal (more sales when people are at work...), weekly (more sales on weekdays or weekends), or even yearly (sales periods, christmas, ...).

When looking at your ads performances over time, make sure you're comparing against the right period. When doing a year over year graph, try to control for the day of the week (we've got an article on that ^^). When looking at an extended period of time, maybe looking at the previous period is better than last year, as your business might have drastically changed.

But in general, don't hesitate to display 2 comparisons at the same time in your table (against previous period AND against same period last year), so you've got all the numbers at hand to better understand if you're doing better (or worse) than you used to. The why, we'll leave it to you.

Focus on the right KPIs, set objectives & look beyond the first sale

Today, we can track pretty much everything. It doesn't mean you have to!

What's your ads strategy? Do you have an official objective? If you don't, we encourage you to set one on only a FEW metrics, and then use it as a comparison basis in your different dataviz. With some conditional formatting, you'll easily know which ads are doing the job, and which aren't.

Some companies want visibility and will focus on Impressions + CPM, some want short-term performances and will focus on ROI + CPA, others will take into account 12-months ROI to take decisions, ...

We know cash-flow can sometimes be limitating, but try to look beyond the first sale before deciding if an ad is working or not. Maybe the quality of the clients is better on a channel when compared to another one. So try to compare in a dataviz the 12-months revenue based on adquisition channel, it'll add insights to your analysis.

Don't lose time on sociodemographic profiles

Yes, all ads offer nice split to look at performances across gender, age, interests, ...

You could lose time building a lots of dataviz around this topic, and then spend time looking at these.

But in reality even before advertising you should know who your target is, so it shouldn't come as a surprise, plus it will only reflect your strategy: if you target female 25-34, you'll get female 25-34, no kidding!

So please, you can build a pie chart if you think that's funny, but put it bottom of your page and never look at it again!

Categorize your ads to better understand drivers of conversion

Having tens or hundreds of ads performances in a table doesn't tell you the whole picture. Why do people are clicking and buying?

So for each ad, you should attach one or several categories representing the product advertised, the intent of the ads, if there is a discount or not, ... (could be directly in the name of the add).

Then, you can extract the category (something along the lines of LEFT_TEXT(Ad name,3), if all your ads start with a 3 letter code for instance), split all your ads performances according to the category defined, and then compare performances.

You'd be surprised by the insights you could get from such a well categorized view. Some of our clients noticed that discounting wasn't actually doing great against ads on their latest shinny product, and decided to go full throttle there (we wouldn't recommend to act so, but who are we to opinate?!).

Challenge your advertising agency

Ok, haters gonna haters. But that's a reality, you start working with an agency, they build and publish your ads, they provide a nice dashboard.

And that's it. Weekly meeting, a couple of comments, and the money goes out without you even noticing.

So (of course) try to find the right partner that care about your success, and make sure you get insights every week, not just mere information. Reporting shouldn't give you answers, it should validate your hypothesis/strategy and bring more questions to the table so you can get better everyday!

In this article, we've reviewed a few best practices to best monitor your ads performances in Looker Studio.


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