Google makes offline conversion tracking easier with Enhanced Conversions for Leads

If you want to see how this can apply to your business, keep on reading.

Google Ads launched Enhanced Conversions for Leads as an alternative to Google Click ID-based offline conversion tracking method. It may be easier to adopt for advertisers since this can be set up directly from your Google Ads account, so this data could mean more efficient conversion tracking.  

Have you ever used offline conversion tracking? If so, how tedious was the setup experience?

How does it work?

When users fill out a form on your site, you’ll receive data including email, name, address, and phone number. This data is captured in your conversion tracking tags and then sent to Google. When it converts, Google matches the information received to the ad that caused the lead, providing a more complete picture of the user journey. 

The issue with the existing Google Click

Offline conversion tracking can help Google get the idea of the value of leads, prioritizing the most valuable ones. Even so, this method has not been widely adopted due to the difficulty of implementation

However, the new Enhanced Conversions with Leads uses the information you’ve already captured such as email addresses, so there is no need to modify CRM systems or invest more time figuring out complex integrations between CRM and Google Ads. This is why Enhanced Conversion with Leads might be a convenient solution for many advertisers.

Did you encounter this issue? Let us know in the comments below! 

Where can you find it?

Enhanced Conversions for Leads can be found in Google Tag Manager if you have Google Ads conversion tracking set up. Also, it can be configured using the global site tag on your page if you already have conversion tracking implemented.

We will continue keeping tabs on this new method and see if it is a more convenient solution. Stay tuned!

About Quantikal

Quantikal is a data-driven performance marketing agency based in Buenos Aires, Argentina. We help clients scale their business through profitable digital ad spending by constantly obsessing over clients’ key metrics. Quantikal’s experience working in diverse online companies in marketing roles including media buying allows us to provide solutions in the ever-demanding increase of marketing performance, doing more with less thus becoming a strategic partner.

Google Introduces Short Titles for Product Ads

Google Merchant Center launched a new feature called the short title for product ads. Here’s what’s in it for you:

Unlike the required “title” attribute, the short title is optional, and it will be shown in places where users do more browsing, such as Discovery, Gmail, and Shopping ads. Google claims that it’s a brief and concise identification of your product that will match the title in a shorter, easy-to-read way. But how brief is too brief? 

How does it work?

Google recommends keeping the character count between 5 to 65 characters. This character limit is important, given that short titles are used in a more scrolling context where the user’s interaction is shorter and quicker. 

Another requirement for using short titles is to describe the product on your landing page, which doesn’t necessarily need to match the title, but it should at least refer to the same product. Google also recommends that you list the important details first and add the brand name as a differentiating factor. If you do not follow these requirements, they will effectively disapprove of your product. 

Our Point of View

This new Google Ads feature allows advertisers better control in creating a more eye-catching title that will not be truncated because of its length.  

In the images below, we can see that “GE – Classic Drip” only shows its full title once your mouse is placed on top of the ad. Google encourages advertisers to shorten their titles so that they can be fully read, even if the user’s mouse is not interacting with the ad. Results show that Google shows only the first 15 or 20 characters of your title, even if they allow you to stretch to 65. Here’s the visual:

Title shown (no interaction)
Title shown when mouse is interacting

What happens once you capture the user? Do they completely understand what you’re selling in 5 to 65 characters? Browsing usually refers to a short-sighted visual, but it doesn’t really sell an accurate description of your product. Let’s see it in an example:

It is easier for users to read “Converse High Sneakers” and see which one fits their ideal best. But what if they need to know the size of the shoes? What if they are looking for a limited special edition? Do these short titles allow advertisers to provide enough information about what they are selling? We don’t have an accurate, precise way to know for sure. These short titles should be monitored and studied so that we can assess their performance better.

Advertisers can’t really differentiate themselves and their products clearly by reducing descriptions to a minimum. However, short titles do give every advertiser an equal opportunity to capture a user’s attention, so if your team can build a strategy around a short and efficient title, you can use this feature to your advantage.

Here’s a quick checklist that could help:

  • Keep characters between 5 to 65 (for optimal results, stick to 15 if possible)
  • Describe your product on the landing page
  • List important details first
  • Add the brand’s name as a differentiating factor

Do you think shorter titles are better to catch the consumer’s eye? Tell us what you think in the comments below.

In any case, be sure to follow Google’s guidelines to avoid unwanted product disapprovals. Stay tuned for more!

About Quantikal

Quantikal is a data-driven performance marketing agency based in Buenos Aires, Argentina. We help clients scale their business through profitable digital ad spending by constantly obsessing over clients’ key metrics. Quantikal’s experience working in diverse online companies in marketing roles including media buying allows us to provide solutions in the ever-demanding increase of marketing performance, doing more with less thus becoming a strategic partner.

Google Ads Makes Updates to Automated Extensions

Here are the facts: Google announced that automated extensions will be able to show alongside the manually added extensions. Updates are coming to sitelink, callout, and structured snippet extensions. However, there’s always some fine print in Google’s glowy improvements.

How was your experience with Google extensions so far? Which extensions do you think are most effective?

At Quantikal, we like to use different extensions and analyze them in comparison to non-brand base search ads (ads that show without any extensions). With our top client, we can compare call, image, and callout extensions to our base click-through rate (CTR), which was 4.5%*. Our call extensions ads showed a 7.7% CTR, image extensions a 4.9%, and callout extensions 6.2%. In general, we see that extensions do create opportunities for a lift in CTR. Therefore, we believe that a proper setting for extensions needs to be in order, and that’s why we care about any feature that Google decides to put out in this area.

These Google changes are soon to be available in mid-March. Let’s take a closer look at the details, shall we?

Previously, if your ads had manual extensions created, your ad would only be eligible to show those. With this update, your ad would now be able to show your manual extensions and automated extensions simultaneously. This is another ongoing automation move from Google, trying to provide ads with more tools to allow advertisers to increase their ad’s CTR. Keep in mind that your account must be opted into automated extensions to show. You will be able to pause or remove any automated extension, allowing easier management of your campaigns. You can now identify which extensions were created manually and which ones were automatically created by Google.

With this new feature, ad eligibility will change. Extensions are eligible to show if Google’s machine learning algorithm predicts that your ads will improve performance. As always, Google assumes that advertisers prefer their machine algorithm above their team-created ad version. Are we sure that their algorithmically generated ads are failproof?

Google’s constant push towards automation means that advertisers will continue to give up control for easier implementation. To give you more intel, we want to share some of our experiences with Google automation tools gone awry.

At Quantikal, we had some mishaps recently with Responsive Display Ads (RDA). With this format, Google allows you to upload a series of headlines and descriptions so that the algorithm can automatically mix and match to optimal combinations. However, we found an example where the combined ad headlines were missing a critical piece of information. In this particular case, we were selling car tires through RDAs with an automobile accessories client of ours that has many important financial offerings. Things went amiss when we realized that the combined ads listed out these financial offerings without detailing that the product was a specific car accessory and not a car itself, so the ad was easily mistaken for a new car advertisement. 

Google’s faulty ad combination algorithm could never figure out if the ad created with this method makes actual sense. This automation feature does not allow advertisers to anchor specific titles that they want to make sure are included, so sometimes the main product descriptor is missing to create an effective ad. Today, still, machines can’t grasp semantics as well as humans, so clearly there are limitations to these types of automation.  

So, creators beware: although these changes allow for easier management and visibility regarding the automated extensions created and allow higher lift in performance, you must review extensions in their final stage, as it would be shown to the consumer to make sure it all makes sense.

Without fail and as we always do, we will review these features and analyze them as soon as they hit the market to keep you in the loop of Google’s changes. Stick around!

*Quantikal MCC Google Ads aggregated account data from different client 23/01/2022 to 21/02/2022

Google Launches Placement Reports for Performance Max campaigns

Google recently launched new placement reports for Performance Max campaigns, but nothing is ever quite as shiny as it seems. Have you tried it yet? Tell us what you think in the comments below!

Here’s the lowdown: Google Ads’ placement reports were made for advertisers to see where ads are placed for Performance Max campaigns along with the amount of impressions they get. The catch? Despite this alluring new feature, Performance Max campaigns have been poorly designed from the start.

For those not familiar with this campaign type, Performance Max campaigns allow advertisers to access their Google Ads inventory from a single campaign that’s designed to complement keyword-based search campaigns in order to find more converting customers. It can “drive better performance against your goals, unlock new audiences across all Google channels, steer automation with your campaign inputs and simplify campaign management,” according to the Google Ads Help platform. But according to us, this is just a clever new way to mask something mediocre by trying to sell it as “easy.”

Google has explained that now the Ads platform provides more in-depth information about where the Performance Max campaign ads are being displayed, but the data provided only shows where they are served and the amount of impressions. This leaves out a very important detail: click data. Why wouldn’t they show the most important part of the ad landscape?

Although this campaign type combines search, display, and shopping ads, the available metrics and control settings are very limited.  For example, metrics are not broken down by search term or keyword, so branded keywords cannot be separated from non-branded keywords—a critical oversight. Also, there isn’t any control offered for selective placements or excluding placements.

The only allowed base setting that’s now included in this campaign type is location and ad scheduling, which makes it incredibly visible that this type of campaign is inadequate in terms of control. Did Google really think that advertisers would be happy about this launch?

Google’s public launch statement says: “Placement reports for Performance Max campaigns are a new reporting resource for advertisers to easily see where on Google’s channels ads have served and associated impressions. We created these reports to give advertisers more transparency and assurance around where their ads are showing.”

That’s all well and good, except that we wouldn’t call it “transparent” if it only provides mainly two aspects of ad control. It looks like Google is targeting small account advertisers with this campaign type. Even for advertisers that want to minimize the complexity of their ad setup, the sacrifice of control is just too much of a downside to make the change worthwhile.

It’s understandable that Google wants to help smaller advertisers grow, but giving up so much agency on critical settings like keywords, negative keywords, and negative placements—just to name a few—simply doesn’t add up.

As this story unfolds, we intend to follow along with this blind-as-a-bat campaign type and its placement reports to see if it evolves or gets any advertiser adoption. We’ll make sure to share any updates or changes over time. Stay tuned!

Google Launches Free Deals Listings in Search Results

Google’s latest offering for e-commerce businesses is an option to list deals within search results. The tool is free for all merchants and takes advantage of the fact that today’s consumers are looking for ways to save money when they shop.

This launch may sound like a win for brands, but is it really? Google is almost universally beloved by consumers as a search platform, but as a merchant or advertiser, the story is a little bit different. Because Google’s focus is providing a positive search experience—and increasing its own revenue—it doesn’t always favor businesses on the other side of the equation.

With each new feature, it’s important to look beyond the initial praise to understand what the change really means for businesses. Here’s what we know about the free deals listing so far.

First, the deals will show up in the regular shopping tab, allowing consumers to monitor one single location for all relevant products. The difference is that the tab will now show product listings that are discounted, highlighting the savings with a green tag in the top left corner of the listing.

Google also announced that in October, it will use this same feature to highlight the best deals for Black Friday, Cyber Monday, and other significant shopping moments throughout the year.

Unfortunately, even with a discount loaded into your product listing, there’s no guarantee that Google will display your offer to consumers. Its algorithm will still take into account other factors like the product’s popularity, your site’s popularity, and how significant the discount is. This could mean that despite taking the time to update your listings, you won’t see any results from the change.

With all this in mind, here’s our take: Because the tool is completely free for merchants to use, there’s very little downside to running a few tests and monitoring how the deals tool performs for your products. If you already have shopping campaigns set up, setting up the deals feature for a few of your bestsellers should be a simple update. Just make sure to test a variety of products and discounts to understand what works best for your brand.

If you decide to go this route, now is a great time to get started. You may still be able to take advantage of early adopter benefits before the tool is widely used by your competitors. You’ll also have time to learn how to optimize your use of the tool before we hit holiday shopping booms. At that point, you’ll be in a prime position to capitalize on your (hopefully) increased return.

We’re really hoping this tool gains traction and Google delivers on its promise, but we haven’t forgotten how Google’s first organic search tool was affected (and organic results were diluted) when it expanded from three paid search results to four.

So, will this remain a free deal listing, or will it just be an experiment for a future paid extension? Only time will tell. Drop a comment bellow on your thoughts.

In the meantime, since it’s free to implement, try it out and see what you find. We’d love to hear from you if you have any interesting takeaways from your experiments. As always, we’ll continue to monitor the landscape and report back with any updates or changes over time.


Never Ever Use These Match Types Together

To the tune of Taylor Swift’s song.

It has been some time that I wanted to sit down and write this post. I cringe every time I see incorrect use match type in a client’s account.

As of today you can choose from four type of match types:

  • Exact
  • Broad Modified Match (BMM)
  • Generic broad
  • Phrase

Care to guess which ones are ok and which are not?

Explaining this concept to my clients, I always like to do a small exercise of the imagination. It goes somewhat like this: imagine a car. This car is similar to any other car but the difference is each time you press on the gas pedal, the windshield wipers begin working. Every time you hit on the breaks the right doors open. Each time you signal left or right, your car seat reclines. Now imagine trying to drive this imaginary car on your daily commute from home to work. Yes, it will drive you crazy!

Managing and trying to optimize an account with most of the keywords are generic broad or phrase match is like driving that car.

So now you know that Exact and BMM match types are ok, the other two, not so much.

So the begging questions is why?

There are two major concepts on selecting keyword match type, coverage and linear independence.

Coverage is the ability of having a small set of keywords that cover an important amount of user search queries of the interested category you compete in. Coverage is lowest with Exact match as the probability to match a certain user search query is lower than other types of matches. In the other extreme, the Generic Broad has the highest coverage. However, this high coverage comes at a price. A very steep price indeed as you will see below, the price is low independence.

Linear independence is the ability for one keyword of behaving independently of other keywords in the same account. We can think of it as low interdependence or low cannibalization of searches between each keyword. For those of you that remember some algebra, it is similar to the concept of avoiding the co-linearity of vectors. Now, keywords and semantic objects are not vectors. However, organizing an account as clean as possible is the first step to been able to optimize the account in the future through keyword bidding.

Why then do broad generic keywords have low independence? And why should it matter? There two main problems with broad generic keywords:

1) Not all the keywords needed to be present in the query to activate the match. What we call the partial match.

2) Google allows the use of synonyms on broad generic.

This generates many search queries that may not be aligned to your business offerings or there is a lost opportunity of handling a generic keyword as a mixed bag of intentions. Let’s take one example from the auto industry. One might say that the adjective “used” car and “pre-owned” car means the same and Google might interpret them as synonyms. However, I can tell you from experience that keywords +used +car and +pre +owned +car do not behave the same. For a used car classifieds site, generally, the “pre-owned” term usually has a higher conversion rate. Because of this conversion rate difference, it is important to have these terms separated using BMM structure instead of a generic match type. This will allow to bid separately for each term optimizing the account better.

So remember, every time you use a generic broad match a SEM fairy dies. Joking aside, I recommend using a mix of 5%/10% exact match keywords and 90%/95% BMM keywords.

Think about building a good structure and keyword base for account optimization through keyword bidding.

Happy bidding.

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Marginal CPA vs Average CPA: What most people get wrong.

I still get quite surprised about how people within the industry still confuse the two terms: average vs marginal cost per acquisition (CPA).

I remember once I was renewing my drivers license at the local DMV office in Buenos Aires. While attending the mandatory class, the person teaching the class asked us this question: What is the speed limit in a city avenue? Everyone answered simultaneously “60 Km/h”, we were quite confident on our response only to be reprimanded by the DMV teacher that our answer was incomplete. He corrected us saying that the correct response was “30 Km/h as a lower limit and 60Km/h as the upper limit”. That response stuck with me regarding how sometimes one metric by itself might give an incomplete picture of a particular situation.

I believe the same happens relating to CPA, a more complete understanding of how your paid channels are performing involves knowing both average CPA AND marginal CPA.

Calculating Marginal CPA

The average CPA is pretty straightforward, it is the total cost divided by the total amount of paid conversions. An easy way to muddy this metric is to not only use paid conversions but use total conversions (including free/organic).

Ok, so how about marginal CPA? The first key insight of marginal CPA is that it is not a constant. Marginal CPA depends on the amount of conversion one takes as a starting point. The marginal cost for the 100th conversion is not the same as the marginal cost of the 500th conversion. If the sorting of the conversions has been done right (less expensive first), what you will see is that marginal costs is always incremental.

The graph below tries to show both concepts(1). If one were to grab and adwords account and detail the information by grouping the data by keyword adding total cost and total conversions for each keyword. Later ordering the keywords from least expensive to most expensive.

The X-axis shows the accumulated amount of conversions while the Y-Axis tracks the accumulated investment.

In the above example activating only a subset of the keywords, the least expensive keywords to achieve 4000 conversions. One would have to activate 887 keywords for a total of 4012 conversions at a total cost of $31,374. Making the average CPA $7.82.

However the marginal CPA at 4000 conversions is calculated differently. Taking two very close data points we get:

Point A: 3991 conversions, total investment $31,090

Point A’: 4012 conversions, total investment $31,374

In this example and at this specific point marginal CPA is close to double of what the average CPA is. Another benefit of this graph setup is that the slope of the curve corresponds to the marginal CPA.

I usually consider marginal CPA to be a more important metric than average CPA. It is a good indicator that shows how scalable are your current SEM efforts. In the case of selling ad inventory do consider that the real BATNA (best alternative to a negotiated agreement) of the buyer is the marginal CPA and not the average.

Building the graph

Extract and adwords report by keyword export it to an excel. There divide cost by conversions for each keyword (CPA), then sort this column in ascending order. In the same file add two new columns: 1) accumulated conversions: the first row should have the number of conversions of first keyword (KW) , the second row should have conversions of second KW plus the accumulated conversions of the previous row. 2) accumulated cost: same concept of the previous column but instead of accumulating conversion, add total cost invested in each KW. After processing these columns, the last row should show total amount of conversions for the account and total cost.

Once you have this data calculated, select the cells of these two columns and generate a scatter plot where the Y-axis is cost and X-axis amount of conversions. Your plot should like something like the graph shown above.

1.The Google Ads data was taken from an account in the auto industry in Argentina, the absolute values were modified for confidential purposes


What Google doesn’t want you to know about average position

An oldie but good one. Originally published in 2015.

The average position myth

A common phrase that I have heard about average position is the closer to the top of the page the better. I have even heard that the 1st ad position should be coveted by digital marketers specially on the branding benefits. The proliferation of this myth leaves me baffled.

I wanted to shed some light and some humble evidence to contradict this point. That first position isn’t the best position SERP for a performance oriented account. Insteat a target position between 2 and 3 stands what I would call a performance “sweet-spot”. 

Average CTR vs. Average Position

Above shows a graph of accumulated information on a high volume (clicks & conversions) ad group. We will later see it is representative of other ad groups that show similar conclusions. The graph was generated with information of 12 month window. Each of the ad groups analyzed were composed of highly homogeneous keywords and high percentage of ad group traffic was consolidated in a few exact terms.

The graph was generated aggregating daily reports by average position cluster. Within the analyzed time period competitive structure was stable and no major changes were made to the ad group just bidding CPC price updates. 

The X-axis represents the average position cluster, the Y-axis on the left shows average CTR.

Nothing mind-blowing here, CTR generally decrease with an increase of average position. Now (below) we add an overlay of data points with their average CPC (right Y-axis)

Average CPC vs. Average Position

Average CPC declines as well, the closer the position to 1.0 the more expensive it is. Again, no major news.

From this point on, it gets more interesting, let’s dive deeper on the CTR and CPC curves. 

CTR Linear Fit

In this example a linear regression for the CTR curve offers a good fit (R^2=71%)

CPC Exponential Fit

However, the CPC curve has a better fit with an exponential curve (R^2 = 86%). This type of curve shows that CPC has an accelerated decay or accelerated increase, depending if you move left or right within the graph.. 

Finding the sweet-spot

Considering that the conversion rate is stable within the same ad group and independent of average position, then CPC and Cost Per Acquisition (CPA) go hand in hand. 

We can see an area where CTR is stable and CPC has local minimum, behold, our sweet-spot. Let’s call this area the Efficient Position Area (EPA, environmental pun intended). 

As we can see from the graph, as we move to the left of the area, CTR does not increase much however average CPC (also conversion cost) increases dramatically without any significant gain in volume. On the other side, moving to the right, CTR has a significant drop as we get close and cross the 3.0 average position barrier. This decline in click volume is seen across many ad groups. I can be related to going from top ads to sidebar ads in the SERPs.


Optimizing bids taking into account ad position within efficient area can generate savings that can be used to invest in other keywords/adgroups lowering overall CPA of global account. 

So try making this analytic exercise with your own adwords account, let me know through comments if you find similar findings.