Q: How do I advertise holidays and promotions?

Holidays & Promotions Promotions Temporarily change all ad copy to include mention of the promotion. Simply swap out the landing page URL but keep the ad copy the same. Run a promotions-focused campaign (which is described in the holiday campaigns section below). Holiday Campaigns Here is a recommended strategy example surrounding Valentines Day with a $15k spend on holiday-specific ads: Spend $3k three weeks prior to V-Day & then spend the remaining $12k during the last two weeks. Swap out the landing page used in the Branded Campaign to the holiday-specific page temporarily so that anyone familiar with the brand can learn about the limited-time products. Set up a new Smart Shopping Campaign for the holiday-specific products. (If the products are new, then start with a regular Shopping Campaign in order to build conversion data first and then switch to Smart Shopping. See the Bidding Strategies FAQs for more on this.) Set up a new Display Campaign for holiday-specific products. Do not set up a new Search Campaign targeting V-Day Gift search terms (not product specific).

Question 1

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 2

How to share passwords with Solutions 8

Accepted Answer

These instructions will help you add confidential login information to Dashlane, a trusted online program that allows you to securely share login information with us. We use this tool so we can keep your information secure, rather than exchange sensitive information via email.

Go to dashlane.com and click on “Get Dashlane”.
Allow the app to make changes to your device.
Log in or create an account. Be sure to create a really strong password!
Follow the prompts or skip the prompts.
The Dashlane dashboard will pop up.
Click on Password on the lefthand panel.
Click the green “Add New” button at the top.
Enter the information you’re sharing.
Click Ok to create the record.
To share this record with our team, go to the sharing center and click “Add New”
Find the items you would like to share in the drop down menu.
Add solutions8ads@gmail.com to the Recipients box. Be sure to click “Full rights” before sharing.
Click send.

Question 3

What Budget Do You Recommend I Start With?

Accepted Answer

There's no "right answer" to the question "what budget should I start with?" but here's what you need to know to make an educated decision.

Too High Can Be Bad

If you have a brand new ad account and/or a sales & marketing funnel that has not yet been thoroughly tested & honed, then exorbitant ad spend can put you at risk of overspending in areas that don't provide good results.

In the beginning, nothing has been tested just yet:

The algorithm doesn't know which combinations of ad copy, users, search terms, placements, etc. will work best
The ad management experts don't know which settings and campaigns and division of the budget will work best
The business owner doesn't know which parts of the website or call-to-action or lead magnets or emails will work best

If your budget is "too high" then it might outpace the manpower that's needed for iterations (i.e. marketing experts to edit the website, edit the sales pitch to match the new, cold leads from paid ads, fine-tune the settings in the ad account or the CRM email follow-up, catching & negating an irrelevant keyword, etc). It also might outpace the rate at which the algorithm can gather conversion data points to learn from (meaning the user interactions for the sales cycle to complete & the algorithm to observe what worked). It's impossible to know at what point this phenomenon will happen or even if it's happening, but this section is here to explain why we recommend starting with a somewhat conservative budget if it's a brand new ad account.

However, if you've run some ads recently (less than 30-90 days ago depending on how long your sales cycle is) then the algorithm has some data to work with, and if your website and other marketing assets have been tested & perfected then you are many steps ahead and can afford to be less conservative with your starting budget.

Too Low Can Be Bad

When a campaign doesn’t have enough ad budget to show the ad enough, it can have a compounding negative effect on campaigns.

More money = more opportunity for the algorithm to bid at the right time, the right place, and make sure to get the "easy" sale that it's been following for a while.

Here's a rough example: let's say a user interacts with one of your ads, and the algorithm sees them do it again a few days later... If it's out of budget that day, it might not have the opportunity to bid on that user's second search. A competitor's campaign that still has budget might scoop up this lead that was already invested in & "warmed up" by your ad a few days ago.

Budget limitations can also be detrimental to your return on ad spend, because the amount that you're able to spend per click will affect how far up on the page you’ll be. Higher up on the page means higher conversin rates since those users tend to be more eager to buy.

Another issue with low budgets is simply the lenght of time it takes to get through the "learning phase." Less money means fewer conversions and fewer conversions means fewer data points with which to optimize from. So, if it takes many months to get the hang of things, the business can run out of income in the meantime.

Then there's another compounding affect there, which is that more time exposes you to more shifts in the market. If the algorithm is watching a pocket of the market and trying to hone in on what works and then the weather changes...well, it's going to make it even more difficult & slower for the algorithm to decipher what worked well & when & why because you have that "market shift" factor pulling the rug out from it during the learning.

This is why we recommend raising the budget slowly & consistently in the first few months in order to find that perfect starting budget. Many times we discover a threshold where the return on ad spend begins to suddenly improves after a small budget bump.

Every Industry Has A Different Range Of "Ideal Min. Budgets"

What's your average CPA (Cost Per Aquisition)? If you sell consumer goods and your AOV (Average Order Value) is $60, then your CPA might be $20, for example. Whereas if you sell services and your LCV (Lifetime Customer Value) is $5,000, then your CPA might be $400, for example.

In one industry the algorithm only has to spend about $20 to get it's first conversion data point and in another industry the algorithm has to spend about $400 to get it's first conversion data point.

So, if both of these example companies start with a budget of $1000/month then the consumer good company will get about 50 conversions in the first 30 days and the services company will get 2 conversions in the same time period.

With only 2 conversion data points per month (and maybe only 1 in the first few months since it hasn't undergone any learning period yet), it's going to take the algorithm a long time to optimize itself towards what works (meaning which users convert, which search terms, which placements, which ad copy combinations, etc.)

So if your CPA is large, you will need to deal with larger ad budgets, even in the beginning, just to get things going fast enough before the business runs out of income.

Can You Give Me A Ballpark?

Sure.

If you have a brand new account & are working with low CPAs (like in the examples in the previous section), then we recommend choose a budget between $2000 - $5000 to start with depending on how patient you are to get through the learning/optimization phase & see results (lower budget means slower to learn/optimize but less money waste in the process and higher budget means quicker to learn/optimize but more money wasted in the process).

If you have a brand new account & are working with high CPAs (like in the examples in the previous section), then we recommend choose a budget between $5000 - $10000 to start with depending on how patient you are to get through the learning phase & see results (lower budget means slower to learn/optimize but less money waste in the process and higher budget means quicker to learn/optimize but more money wasted in the process).

If you have an account that has a good amount of recent conversion history, then we recommend starting with a budget that's the same (or a bit higher) than you were spending previously.

Whatever number you choose to begin with, we recommend raising the budget slowly & consistently in the first few months in order to find that perfect starting budget. Many times we discover a threshold where the return on ad spend suddenly improves after a small budget bump.

Question 4

Why isn’t the Facebook remarketing campaign running?

Accepted Answer

It's common for Facebook remarketing campaigns to struggle to acquire a large enough audience in order to run. Facebook says their minimum audience size for a pixel-generated audience is 1000.

This means the Facebook pixel on your site needs to be able to match at least 1000 website visitors to Facebook users.

What factors into this?

Match Rate - Facebook doesn't reveal their average match rate (the rate at which website visitors can typically be matched up with Facebook users), and this likely varies greatly depending on the type of user who visits the site (do they tend to have Facebook accounts? Do they tend to reset their cache & cookies often?) as well as a number of other factors.

Pixel Age - The pixel is only able to see website visitors in real time, which means it can't see people who visited before the pixel was added to the site. So, if you've had the pixel on the site for 6 months then it will have 6 months worth of website visitors to try to mach to Facebook users (as long as the settings inside the Facebook ad account are set to look back 6 months, which is the maximum amount of time Facebook allows a pixel to look back).

So, the best thing to do is get the Facebook pixel onto the site early, make sure the settings inside FB pixel area are set to look back 6 months, and consider sending more people to the website with proactive (aka not remarketing) ad campaigns in order to populate that Facebook remarketing pixel audience.

Question 5

When is the best time to run Facebook Ads?

Accepted Answer

Start with a Remarketing campaign only for this first month until the pixel has picked up enough matched users and conversion data in the performance history. As a side note for e-commerce you can do Dynamic Product Remarketing which pulls products from the feed much like a Google Shopping campaign.

Keep in mind that Remarketing campaigns will not be able to spend much ad budget because the audience is made up of a percentage of people that visit your site (Facebook isn't able to match 100% of site visitors back to Facebook users). Start off with $5-$10/day for this campaign and adjust from there based on the frequency of the ads being displayed.

Once you have a good audience size and historical data then you can create a lookalike audience form your existing converters and show proactive ads to that cold list in order to build awareness.

People tend to view FB ads and then convert without clicking in FB. This can happen with Google to but it is more common with FB so it's hard to directly attribute sales and judge the performance of FB campiagns. Some of the people who convert on FB might be the sample people who are converting from an ad on another platofrm like Google. Without an attributuion tracking model it is impossible to know the exact path of conversion.

Question 6

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 7

How do I advertise holidays and promotions?

Accepted Answer

Holidays & Promotions

Promotions

Temporarily change all ad copy to include mention of the promotion.
Simply swap out the landing page URL but keep the ad copy the same.
Run a promotions-focused campaign (which is described in the holiday campaigns section below).

Holiday Campaigns

Here is a recommended strategy example surrounding Valentines Day with a $15k spend on holiday-specific ads:

Spend $3k three weeks prior to V-Day & then spend the remaining $12k during the last two weeks.
Swap out the landing page used in the Branded Campaign to the holiday-specific page temporarily so that anyone familiar with the brand can learn about the limited-time products.
Set up a new Smart Shopping Campaign for the holiday-specific products. (If the products are new, then start with a regular Shopping Campaign in order to build conversion data first and then switch to Smart Shopping. See the Bidding Strategies FAQs for more on this.)
Set up a new Display Campaign for holiday-specific products.
Do not set up a new Search Campaign targeting V-Day Gift search terms (not product specific).

Question 8

Can you provide some guidance on image ads?

Accepted Answer

There are two types of image ads: shopping ads & display ads.

Shopping Ads

Shopping ads are only relevant to you if you sell physical products online & are planning to run shopping campaigns. The images needed for these campaigns are imported into Google Ads directly from the product image on your eCommerce site.

This type of images are relatively straightforward:

Make sure the product is clearly displayed & takes up the majority of the image.
Ideally have a plain background. It can have a subtle pattern, a shadow, or a gradient, for example, but it shouldn't distract from the product itself. Light colored backgrounds tend to convert at a higher rate on Google Shopping. We recommend going to shopping.google.com (or you can use isearchfrom.com if you live in a country that doesn't have Google Shopping yet) and doing a few quick searches to find your competitor's shopping ads to get a sense of what will catch the user's attention & what won't.
Any text in the image must be text that's on the product itself or it's packaging. If you add a logo or a call-to-action to this image, Google's bots will crawl the ad eventually & disapprove it.

FYI if the first image (the primary image) on the product listing is less ideal than one of the other images, our team can override the product image directly in the product feed. This way we can use the best image for the shopping ad in Google Ads while keeping your favorite image as primary on the product landing page.

Display Ads

Display ads are typically used in remarketing campaigns (this means it only shows to website visitors & YouTube channel viewers) and also be in outbound campaigns (meaning it will show to cold leads).

Here's what you need to know:

These should be lifestyle images. If your business sells products, this ideally means images of a person (with their face showing) using the product in some way. If your business sells services, this ideally means images of an employee (with their face showing) either offering the service or a customer receiving the service or benefiting from it's results. Yes, you can absolutely use stock photos.
We can ideally use 7 square images and 7 horizontal images. Google Ads will help us crop them to the perfect aspect ratio, so don't worry too much about getting it perfect.
These images can have text on them if you would like, although they don’t need to have text on them because we use something called “responsive display” which basically uses ad copy & images to create an ad into the perfect aspect ratio needed for whatever placement Google is trying to fit it into. Here’s a video & article from Google that shows how these work. If you want to experiment with adding a short call-to-action as text on these lifestyle images, go for it! We believe that can be very effective if the there are only a few words in total (pick one short phrase). Just don’t make fake buttons on the image, because Google will disapprove those.

Question 9

How Long Google Ads' Learning Phase Takes

Accepted Answer

You launched your Google Ads campaign. You have a ROAS goal you want to achieve and a daily target budget to support it.

But after a few days (or weeks), you noticed that you’re not hitting your ROAS goal…

And worse, Google isn’t spending enough to reach your ad budget.

What’s happening?

One of the most common mistakes people make is setting a ROAS goal and expecting Google to reach it right away.

By doing that, they’re not only slowing themselves down from hitting their goals, they’re also preventing Google from spending their target budget.

And here’s why: Your campaign needs to undergo the “learning phase” first.

It’s that initial time period where Google gathers all the data you’ll need to successfully optimize your campaign and position it to scale.

In this post, you’ll learn about all the different factors that might affect your “learning phase” and how to deal with them so you can reach a point where your campaign looks profitable and scalable.

But first, let’s answer some of the most common questions asked and get them out of the way.

An important update to the "90-Day Rule of Thumb"

In the past, our rule of thumb was 90 days for a campaign to be fully optimized. This meant that after 90 days, we would typically have enough data to know whether or not the campaign would work long term.

With the introduction of Performance Max, the 90-day guideline no longer applies in most cases. Instead, it takes roughly 45 days just to see what we've built and how it's going to work.

Essentially, Day 46 is now Day 0.

This new campaign type is seven campaigns in one—Search, Shopping, YouTube, GSP, Discover, Display, Local, and Remarketing—and all of them are being optimized at the same time. Once Google has gathered and analyzed the available data, then we can start to see how the foundation we've put into place will perform over time.

Put simply, it takes time to successfully optimize a campaign and position it to scale. But more often than not, being patient during that initial learning period pays off in the long run.

How do we "optimize" the campaign?

Optimization means the “things we do to improve a campaign’s performance.” We do that with either one or both goals in mind:

To bring your cost per conversion (CPC) down
To increase your return on ad spend (ROAS)

To reach our goals, we stick to a proven process, go through the learning phase, and make optimizations. Here’s a just few of them:

Implementing data-driven strategies
testing different assets (e.g.keywords, copies, landing pages)
Adjusting the ad budget
Listening to every phone call

These are just a few optimizations we do from the start. The conversions may cost a little more in the beginning, or may be inconsistent. But as your campaign goes through the learning phase, you’ll see results.

How long should we stay in the experimenting & learning phase with our Google Ads account?

The experimenting and learning will slow down a bit after the campaign is fully optimized, but it is important to never stop making changes to the campaign. With live bidding, you often won’t use automated bidding strategies because they won’t optimize performance.

For example, if you tell it to automatically focus on getting the maximum amount of conversions, then it will set the bids in order to get the most amount of conversions, which favors cheaper, poorer-quality traffic because it is not focused on the quality of those conversions.

You could potentially set a goal for the automation to target a specific cost per click, but you don’t have enough activity to use that feature because you would need to have a conversion or two every single day for it to have enough data to form patterns. So, use Manual CPC with enhanced CPC enabled, which means you set the bid based on what you think the keyword should be worth to you, how many clicks per day, and if there are conversions for that campaign.

You could probably not touch a campaign for a month and it would likely perform relatively systematically, but as new competition comes in, old competition falls out, people increase bids or increase their budget, you need to hop back in there and make those adjustments.

So, how do you get past the learning phase and more importantly, what are some of the factors that affect your campaign from moving quickly?

That’s exactly what you'll learn today.

1. State of the Ad Account

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/CDPbaOjSgr/Google%20Ads%20account%20historical%20data%20.png (Google Ads account historical data .png)

No or inaccurate historical conversion data

If you recently launched a brand new account, it won’t have any historical data. Google doesn’t know your target market and it doesn’t have a data-driven and well tested algorithm yet to find your ideal customers.

Unlike an older account that has at least 2-3 months of consecutive and recent historical data, a brand new account takes longer time in gathering enough data.

“But what if my account is about six months old?”

If it’s at least 6 months old but there’s no recent historical data in the past 2-3 months, the algorithm might have already changed, like:

target market
competitive landscape
price points

Which only means one thing—it’s outdated. Unfortunately, that’s worse than a brand new account with no historical data. Here’s why:

Let’s say you were running a campaign and your conversion was set to count “everyone who visits the product page.”

Whether the person who visited your site only viewed the product, added to cart, or bought the product, you counted it as a conversion. This gives you a false conversion value that actually hurts your data.

Instead of having real data, you now have to fix and refocus the algorithm first. And that can take longer than having no conversion data in the first place.

Not running sacrificial campaigns (inbound)

If you’ve been checking out our videos and blogs for awhile now, you probably already know how much we LOVE Smart Shopping.

The problem is while Smart Shopping is pretty darn powerful, it’s kind of a slow learner especially in the beginning.

That’s because it’s still gathering data to figure out what an interested lead or customer looks like.

So if you’re only using Smart Shopping, it’s going to take a very long time—you might as well take that vacation you kept cancelling while waiting for Smart Shopping to scale. (Hey, that’s not a bad idea! ;p)

The trick is to run it alongside other additional campaigns like branded, remarketing, competitor, display, or even YouTube. We call these sacrificial campaigns.

They might not directly bring in profits, but if you’re struggling to get enough traffic that will feed back into your Smart Shopping campaigns and bring more users to your site…

Sacrificial campaigns will help you do the job by monetizing Smart Shopping and feeding it data from other sources.

2. State of the Industry

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/jIUyeXliKC/Google%20Ads%20different%20types%20of%20industries%20.png (Google Ads different types of industries .png)

High CPC (high competition)

“More clicks equal more conversions,” they say. That’s true...until you run out of budget.

See, it’s not uncommon to see a high cost per click in a highly competitive industry. Hopefully, your average order value or your lifetime customer value will be able to balance your expenses.

However, if your clicks are too high and your margins are thin, you have to be very strategic. You might run out of budget faster than you know.

Low market demand

Another factor that can lower your learning phase’s speed is if your product is something new.

While Google’s multi-faceted ecosystem gets over 1.3 trillion global searches per year, it doesn’t mean you can instantly get tons of people searching for your product.

At least not in the beginning or if your product is something new.

Maybe it’s a niche product or a unique product that has yet to be discovered in the market––if people aren’t aware of it, they probably won’t search for it.

This is another reason why using a sacrificial campaign like YouTube is recommended. Not only does it help to increase your traffic, it also helps to increase your conversions – especially if you use remarketing.

3. State of the Business Itself

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/0vvmRxxsFn/Google%20Ads%20remarketing%20.png (Google Ads remarketing .png)

No remarketing audience (low website visitors)

Dynamic Remarketing shows ads to those who previously visited your website or engaged in your ads. Running Smart Shopping with remarketing makes your campaign unstoppable.

That said, if you’re running Smart Shopping without remarketing for a while, it won’t be as profitable because there’s not a lot of existing traffic to convert.

And if you have a small number of website visitors, then it's going to take a long time for the remarketing audience to pixel.

Low ad spend

Low ad spend can result in low conversions. So if you’re spending $1,000 a month, you’re going to get less traffic to the site than if you’re spending $2,000 – assuming your CPC stays the same, of course.

Low CTR (Untested or out of date website design)

Even if you’re using these 5 tips to increase your CTR, and you’re sending 200 people to your site every single day…

If your bounce rate is high and people aren’t converting, it’ll take longer for Google to get enough data to build profiles of your customers. Plus, you’re going to lose more money.

So make sure that you update your website’s design and split test it (if possible) to know which version works best.

4. State of the Products

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/KxcPsHVtPV/large%20quantity%20of%20products%20affect%20Google%20Ads%20conversions%20.png (large quantity of products affect Google Ads conversions .png)

Large quantity of products

The number of products you have can affect the time it takes for the algorithm to reach a point of certainty. Not only that, but the number of conversions for each product determines how reliable the data is.

For the data to be viable (and reliable), the algorithm has to find a pattern first. Think of it like a survey. If you asked the same question to a hundred people, and they all have different answers, then you can’t rely on that data to come up with a solid conclusion.

But if at least 20 of them have the same answer, then you’ll be able to see a pattern – either demographically or psychographically.

Do they all have the same jobs? Do they live in the same city? Do they have the same interests? And so on.

Once you see patterns, you can now create a profile. And based on that profile, all you have to do is tell Google “Hey, this type of person lives in this city, does this type of job, and is interested in these things. Get me more of them.”

Here’s what an account that has a large quantity of products (about 4,000) look like:

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/QDA5EfO6Jf/low%20ad%20budget%20with%20large%20quantity%20of%20products.png (low ad budget with large quantity of products.png)

As you can see in the image above, there are multiple products in the campaign. But each product only has one conversion. Even though some of them have a high ROAS, we still can’t rely on that.

The product you want to scale should have, say, at least 3 conversions to get an average going for it to be certain and avoid getting analysis paralysis.

One of the reasons why we’re only getting 1 conversion per product in this account is because the budget was divided and spread out to different products. That itself––having a low budget––limited our ability to effectively test each product.

If you have fewer products, like this account shown below, it would be a lot faster for the algorithm to see patterns.

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/CCeO7bLVVg/low%20ad%20budget%20with%20low%20quantity%20of%20products.png (low ad budget with low quantity of products (1).png)

But that doesn’t mean you can only sell a few products. The solution is to place your bets on a target ROAS goal and choose specific products first.

By choosing specific products and putting more budget to test them, you’ll get more conversions. Once there’s a conversion pattern, you’ll have enough data to scale that product.

That can help you get past the initial learning phase.

No GTINs

Let’s be clear. You don’t need GTINs (Global Trade Item Number) in order to scale. As long as Google approves your products, you can scale without having a GTIN.

However, you run the risk of losing all your optimized data without it. And you lose the ability to tap into the existing historical conversion data of your products.

Here’s what I mean.

Any product that’s been sold in the market with GTIN has valuable conversion data. If you’re selling the same product, you can use the same GTIN and...voila! You now have data in your products.

It’s like borrowing someone else’s flash drive and uploading their files on your computer instead of searching for files and doing the work yourself.

The problem is if you’re selling a unique item, you’ll probably need to create your own GTIN. Which means there’s no valuable conversion data yet – you have to create it.

That’s one of the reasons why having no GTINs can cause your learning phase to slow down.

New market creation (a new widget no one has heard of)

As mentioned earlier, if it’s a new invention (a product that’s unique), there might be no audience for it yet. You have to educate people about it first – usually done via a discovery campaign – before your product gets momentum.

5. Purchasing habits of the target customer

https://malcolm-en-gb.s3.eu-west-1.amazonaws.com/instances/MpD6OKc9u8/resources/LxuhukGTcs/purchasing%20habits%20of%20your%20customer%20.png (purchasing habits of your customer .png)

Large conversion lag

A conversion lag means the time it takes between product discovery and product purchase. The larger your conversion lag is, the longer it takes for the algorithm to gather data. Ultimately, it affects your learning phase.

There are a few factors at play when it comes to conversion lags:

Price. The higher the price, the more time it usually takes for a person to purchase it.

Needs. The lower the demand or urgency is, the slower the purchase will be.

Decision maker. Even if your lead can afford the product and he needs it right now, if he needs someone else’s permission first, it will delay the purchase. Those decision makers can be the spouse, boss, or a group of people.

Low average cart value

If your average cart value is low, it’s going to be harder to achieve the ROAS you want. Unfortunately, this will impact how long your learning phase is going to last.

And that’s it! Remember, you have control over most of the factors that affect your learning phase. For those you can’t control, just stick to the process. Test as much and as often as you can. Have the patience to wait and go through the learning phase.

In the words of Leo Tolstoy, “The two most powerful warriors are patience and time.”

If all this sounds overwhelming and you need more help, we got you covered. We’ll review your existing accounts (if applicable) and provide a Google Ads Action Plan for FREE. Get your action plan here.

Question 10

How do I set up UTM Tracking?

Accepted Answer

This means you want to manually store data in your CRM platform which tells you where the contact record originated from.

In order to do this, you will have to set up hidden fields on your landing page, and you will select which words (aka parameters) to store (i.e. “source=google” and “campaign=branded”).

Once you determine those parameters, you (or your vendor) will enter into the appropriate campaigns or ad groups.

You can double check that the UTM settings are set up correctly by clicking on "ADS & EXTENSIONS", then click and "EDIT" on an ad and then click “TEST.”

Intro to UTM parameters training here:

Keep in mind: These UTM parameters aren't quite as good as Google at tracking folks with accuracy. It's simply a piece of text that's temporarily stored in the person' browser cache when they visit the site. If they come back to the site again with new parameters sent, then the browser's cache will be overwritten with the new parameters. If they come back to the site on a different device to convert, then the browser won't push the parameters into Shopify. If they delete their cache & cookies between their first site visit and the site visit that they convert on, then Shopify also wouldn't be able to include the parameters with the sale.

Google, on the other hand, is much better at tracking folks across devices and through any accidental cache deletions or overwritings. Google has people logged in on their phones, etc. etc.

But the UTM parameters should be close enough to accurate to get a quick gauge on what percentage of traffic is coming from where! You can also compare this data with your Google Analytics account in the Source/Medium section.