Question 1

Why can't we just turn on tROAS & leave it on?

Accepted Answer

Every time we apply tROAS, it stops the algorithm’s learning process and prevents us from infusing more spend into the campaign. While the tROAS setting is applied, the algorithm "muscle" atrophies.

Often times, over-pacing to force the algorithm to learn and grow, and then pulling back on the spend to allow the ROAS to shoot up, is better than simply applying a tROAS goal - it’s like telling the algorithm to “only use the knowledge you already have to try to spend the budget and hit the goal.”

Doing this causes problems because the knowledge it has doesn't update with the ever-shifting market of new users, which causes the algorithm to not be able to spend the full budget, and ultimately causes us to fall behind on spend, and lose valuable time in the learning process.

We only apply it for short periods of time, and we have to sync it up during a portion of the month when we want to push the algorithm in that particular direction (high return), but it's not a long-term solution to achieve high performance.

Question 2

What's The Downside Of A Too-High ROAS Goal?

Accepted Answer

The higher the ROAS, the less of the market you can capture.

If you want to have a higher return, you need to spend less and make more.

Here’s why. In traditional sales funnels, we always have folks at the “bottom of the funnel” (people who are ready to buy) and folks at the “top of the funnel” (people who aren’t ready to buy yet).

Those who aren’t ready to buy are going to be more expensive. They’ll need to click on two or three ads before converting. Some of them won’t ever convert.

There's also people who will have a lower average cart value than others. So if you tell the algorithm, “I only want those who are cheap to acquire and who will spend a lot of money with me,” then you’re cutting out part of your market.

This is why a high ROAS goal will limit your ad spend and stop the account from growing.

The goal should be to choose the ROAS that’s just right (not too high and not too low) and try to maintain that ROAS while growing spend––gathering conversion patterns, optimizing the settings, keywords, product titles, etc.)

For further explanation, check out this video:

Question 3

Why is Google Ads reporting different numbers than Google Analytics?

Accepted Answer

Google Ads and Google Analytics handle the same data very differently. And for good reason: The two platforms have very different focuses.

Google Ads is focused on tracking 100% of the people who interacted with it and attributing those interactions to a sale.

Whereas Google Analytics, on the other hand, is simply a tool that has been developed to show you what's going on on your website...This means it's more focused on tracking where users came from immediately before converting.

Google Analytics doesn't care that the direct traffic will be high -- and that many of those conversions attributed to "direct traffic" could have interacted with Google Ads at some point on a previous session/day/week/month.

Google Ads does care about that. Because Google Ads wants to show you ALL of the conversions that it helped convert.

The reality is, before a customer converts, they usually go through multiple sessions first – they might click an ad, come back to your site the next day, and purchase on a different day.

Because of this, your conversion data can & will look differently depending on the platform you're using at the time.

Think of the platform like a lens for data interpretation: Google Analytics cares about sessions and Google Ads cares about ad interactions.

Google Ads and Google Analytics show different data because their purpose is different:

Google Ads is trying to show us which ads are profitable, when, why, etc.

Google Analytics, on the other hand, is trying to show us the most straightforward picture of what exactly happened on the site and when.

If you'd like to understand the technical details of how this works, read on...

The Two Platforms Use Different Technology To Keep Track

The two platforms have different levels of tracking capabilities to recognize the same user across different channels, devices, etc:

Google Analytics measures session data using browser cookies. This is all it needs, since it's only looking at data that happens within a single session.

Google Ads measures session data using browser cookies, too. But it also uses IP address, session ID, and even WiFi. It also can recognize Google users if people are logged in on their phone or their Chrome browser and connect the dots that way.

With that said, Google Analytics’ method of storing data can often cause about 15-25% decrease in conversion value compared to Google Ads. In other words, Google Analytics drops data.

The Two Platforms Attribute Conversion Data Differently

If a user clicked on an ad, didn’t buy, and then came back to the site directly the next day to purchase, Google Analytics will likely mark that person as “direct” traffic.

Even if the user clicked your ad, the credits would still go to “direct” traffic because it’s the last action the user took before converting. Why? Because Google Analytics uses the Last Click attribution as its default attribution model.

Depending on which settings your ad manager chose, Google Ads can use several different attribution models.

If a user clicked on an ad a month ago but only converted today, some or all of today's conversion will appear a month in the past – it all depends on the attribution model used.

As you can see, the two platforms almost always end up attributing conversions based on different rules (and attribution models).

Keep this in mind when using Google Analytics:

It is a tool that has been developed to show you what's going on on your website. It only sees where users came from immediately before converting, which means its direct traffic will be high since many people who interact with a paid ad will come back to the site directly when they're ready to convert.

If you’d like to explore this further, here is our chief account strategist, John Moran, on the subject:

Question 4

What time period should I use to judge ad performance?

Accepted Answer

It's tough to look at things on a week-to-week basis. Our team aims for hitting the ROAS goal on a month-to-month basis. Performance is intentionally bumpy throughout the month because we do things like using the Stair-Step Method to push the algorithm to grow, or testing small changes, etc.

Question 5

Why shouldn't I judge the performance of each campaign individually?

Accepted Answer

It is tough to look at a single campaign's performance. Our team views account performance holistically. This is because campaigns often interact with the same leads/customers and depending on the attribution model, those conversions can get divided up in a way that makes one campaign look worse than it really is.

Question 6

How long should I wait to see an accurate Performance Report in Performance Max?

Accepted Answer

According to Google, whenever you make any changes to automated bidding, strategies, and budget, you have to wait for at least 14 days (plus your conversion lag) to view accurate and complete performance reporting.

Conversion lag is simply “the delay when people click an ad and when they perform a specific conversion action (for example with, install, purchase, add-to-cart, etc.)”

What happens is the system will optimize towards what we tell it to do, so you must wait to make any changes for 14 days when Google can accurately assess performance.

Making any changes prior to that learning period will reset the account back into the learning period. This means, you’ll have to wait for another 2-3 weeks.

Question 7

Can I show my product ratings in my ads?

Accepted Answer

Yes, you can. However, we don't have a process to check for product ratings on our accounts with shopping campaigns. And here’s why:

We haven't seen a measurable performance boost by adding product ratings to the ads.
We don't recommend showing the ratings unless the average review capture is high.
The 3rd party review aggregator apps are expensive (popular ones like Trustpilot & ShopperApproved charge about $200/month.) We believe that money is often better spent on ad spend pulling in sales.
Google doesn't show the reviews if they are less than 30 per month (they don’t mention this in their help articles.) So most clients get frustrated when they pay for an expensive app that doesn’t even show reviews for that month.

Question 8

Why is there a discrepancy between Shopify & Google Ads?

Accepted Answer

When you're viewing your Shopify report called "sales from marketing" (not available with all levels of Shopify) to see the total revenue from Google Ads, you'll likely see a lower quantity than what Google Ads reports.

It's not unusual to have a 20-30% loss in conversion value when in Shopify's marketing report when compared with Google Ads.

The lost conversions can be attributed to two things:

Shopify uses UTM parameters, which are often dropped, whereas Google Ads uses a robust tracking algorithm.
Shopify removes conversion value from the reporting if the customer made a return, whereas Google Ads doesn't know about the return so it doesn't get removed from the dashboard.

Here's a video Kasim made on this topic -- Although the video talks about Google Analytics reports rather than Shopify reports, it's still the same phenomenon, because Google Analytics also uses UTM parameters: