Google Ads matches – what is it?

When using Google Ads, sooner or later we always come across the term “keyword matching”. What is under this name? Well, each keyword in Google Ads can be added in three match types: exact, broad, and phrase match. Which option we choose depends on how widely the system will search for recipients to whom our ad should be displayed. Thus, Google Ads matching determines, in short, how exactly the password entered by the user in the search engine should match the one we added as a keyword. Depending on the selected match, the system may display the ad only to recipients who entered the same phrase, or also to recipients who specified their password with additional terms or entered a password only loosely related to the keyword. What meaning ranges do the individual matches cover?

Match types

Exact match – This is the most precise match of Google Ads. It reaches the narrowest group of recipients, but it allows you to maintain the greatest control over who our ad will be displayed to. By using this type of match, we only get to users who entered the exact same keyword or phrase with the same meaning (or differently – with the same search intention). When entering an exact match keyword, put it in square brackets, eg [men’s pajamas]. Then the advertisement will be displayed for this slogan and very similar slogans, such as pajamas for men, pajamas for men, etc.

Phrase match takes into account all searches as exact match, and also allows you to show your ad on terms where the keyword has been specified by the user. We’ll still show your ads only for searches that include our product or service, but it doesn’t have to be an exact repeat of the keyword. So this is a slightly more casual match type, but still allows you to keep a relatively large amount of control over how your budget is spent. We mark phrase match by placing the keyword in quotation marks. If we enter, for example, the word “women’s boots”, the ad will also be visible on more specific inquiries, e.g. black women’s ankle boots, comfortable high-heeled women’s boots, etc.

Broad match allows your ad to appear also on queries that are very loosely related to the selected keyword. Thanks to this, on the one hand, we reach a very wide audience, and on the other hand, we have little control over the contexts in which the system shows our advertisements. Broad match doesn’t have any special characters, so when you type just a keyword into the system, no additional characters, it defaults to that type of match. If you enter, for example, low-sugar diet as a keyword, your ad may also show results such as: low-carbohydrate recipes or low-sugar books.

How to use broad match wisely?

Does this mean that by using broad match, we are wasting resources on users who will not buy our product anyway? Not necessarily. Showing your ads to audiences who are not yet ready to buy is part of guiding them through the buying funnel. So, if your ad is shown to users who are not yet looking for our product, but are interested in a given topic, it may later lead to conversion.

However, to make sure your budget is used optimally, it’s a good idea to use Smart Bidding for each Google Ads match type – and broad match in particular. Thanks to this solution, the system will decide what chance for conversion is given by a specific recipient, and thus how high the rate should be determined in a given case. Considering how much he knows about the users, one can be sure that his forecasts regarding the effectiveness of activities will most often be characterized by high accuracy. What does Google Ads take into account when searching for audiences? Among other things, it may be influenced by the user’s last searches, the content of the page to which the ad leads, or other keywords from a given ad group.

Additionally, in each match type, we can narrow down the search context by introducing the so-called negative keywords. Excluding certain words will result in the ad not being displayed if the user includes these words in the keyword entered into the search engine. This feature allows us to gain a bit more control over the ad and prevent it from showing in contexts that we deem unprofitable.

Which type of approximation is best to use?

There is no clear answer to this question. Exact matching allows you to keep a lot of control over your expenses, but on the other hand, it narrows the field of activity and may deprive you of valuable recipients. Phrase match gives you more freedom and broadens the audience, but still ads are displayed only on terms strongly related to a given product or service. Broad match, in turn, carries a potentially high risk of reaching uninterested recipients. On the other hand, we can reach completely new groups of recipients and learn new keywords that are highly effective for our brand. So let’s just use keywords tailored to the specific goal that we want to achieve thanks to a given campaign.

Google Discovery Ads – emission places

Discovery Ads has a reach of 3 billion Internet users. At the same time, however, this format allows for a very precise selection of the target group – we can target audiences with specific behaviors and demographic characteristics, interests, but also the lists of recipients we have created. Users can see our ads during their daily activities on the Internet, thanks to which information about the product or service reaches them at every stage of the shopping path. Google Discovery Ads appears in places such as:

– Discover cards – these are cards in the browser in which Google displays personalized news to the user, tailored to his interests, based on previous activity on the Internet,
– in Gmail – Discovery Ads replaced traditional advertising in Gmail. Currently, it is only possible to use them to display the promoted content to the recipients in the “Offers” and “Communities” tabs,
– on YouTube – on the platform’s home page or in the “Worth Watching” section.

In Google Discovery Ads, the system automatically selects the best display places for a specific advertisement. It also adjusts the rates for it and adjusts its size to the place of broadcast and the size of the device on which it appears.

What does Google Discovery Ads include?

Discovery Ads, as we have already mentioned, is a type of creative in which the system itself assembles an advertisement from the available elements. Therefore, before launching this type of campaign, appropriate resources must be provided to the system. These are:
– headings – up to 5 titles, each for no more than 40 characters,
– descriptions – a brief introduction of the product or service and the benefits of its purchase. You can add 5 descriptions, each for a maximum of 90 characters,
– company name,
– company logo,
– images in horizontal rectangle and square format. There can be a maximum of 15 of them,
– final URL – address of the subpage to which the user will be directed after clicking the ad,
– CTA – Call to Action. Select them from the list offered by the system.

It is not necessary to use all the available images, headlines or ad text, but it is worth remembering that the more resources you share, the greater the chance that the system will find effective connections for a given audience.

Images in these types of ads can be displayed in different ways, so it’s best not to include logos or subtitles in them. These elements will be borrowed from other resources that we will upload to the campaign builder. It’s also a good idea to make sure that all your headlines, descriptions, and images match each other. We do not know in which configurations they will be displayed, so make sure that they create a coherent message together wherever possible.

Automatic Discovery campaigns – what do they give and what they take away?

Google Discovery Ads, as a campaign type optimized almost exclusively by self-learning algorithms, does not allow the use of some functions known from other Google Ads formats. Such campaigns may not, among other things, target placements or devices, limit the number of impressions for a given audience, or exclude inappropriate contexts. However, do these limitations make us a waste of the budget? On the contrary, the system is already so efficient that it does not display advertisements in inappropriate contexts that threaten the brand or bombard the recipient with the same advertisement dozens of times a day. What’s more, he has so much information about the behavior and preferences of recipients that he can almost always choose display parameters much better than a human.

In addition, Discovery Ads provide the option of automatic ad targeting – after enabling this option, the system itself extends the group of recipients with new ones who will most likely be willing to take advantage of the offer. Enabling this type of targeting isn’t mandatory, but it can often benefit you, especially if your ad has been online long enough to exhaust the potential of remarketing lists.

Discovery Ads – why is it worth it?

– wide range of advertising – Discovery campaigns can potentially reach billions of people around the world, in various places on the web,
– precise targeting – this format offers many options for selecting target groups, including the possibility of targeting non-standard recipient lists and automatic targeting, thanks to which you can reach new, promising recipients,
– modern multimedia format – Discovery Ads are advertisements tailored to the needs of today’s recipient. They do not have strictly defined content, adapt to the size of the device and the place of display, and display a given product or service just when the user is looking for it,
– maximum use of the budget – thanks to intelligent bidding, the system can manage the budget precisely. This, in combination with a well-selected group of recipients, prevents the budget from being burned out,
– saving time – the system automatically optimizes the campaign, so we do not have to waste time manually changing the settings. Of course, this does not exempt us from overseeing the campaign and monitoring its results.

Google Discovery Ads is an ad type that is definitely worth exploring. It is an excellent complement to other formats, such as responsive advertising on the search network, advertising on Google Display Network or YouTube Ads. If you want to use this type of campaign to promote your brand, see our offer subpage.

Why is product feed optimization so important?

At the beginning, it is worth asking yourself the basic question why the care of the product feed is so high in the hierarchy of activities that we undertake when creating a PLA campaign. It is such an important factor for several reasons. First of all, in this type of campaign, we have no influence on what key phrases our ad will be displayed on. It is the Google Ads algorithm that decides when to show our product, based on the information contained in the product feed. Therefore, optimizing this file, for example by adding key phrases of interest to us in the title or description of the item, gives us at least an indirect influence on to whom and in what context our products will be published.

Secondly, a number of attributes can be added to each product, i.e. product features, such as, among others, size, color, material, gender (e.g. in the case of clothes) or pattern. In the Google Shopping tab, the user can filter the results based on exactly the same attributes. So the more fields describing the product are filled in, the greater the chance that it will also appear in filtered views. The third reason to optimize the feed is that Google Ads algorithms constantly determine its quality and reward products from those files that they consider to be of high quality in views.

High feed quality, in addition to influencing your impression position, can also help reduce CPC, the rate per click on your ad. If the feed is well structured, our product is more suited to the customer’s inquiry, thanks to which we burn less budget. This means that the campaign can achieve much better results, as it gives more clicks within the set budget and reaches a better selected audience.

What must be included in the product feed?

In the case of the product feed, some information is mandatory for the feed to be accepted by the system, and some is optional, and in addition, some options are required only in campaigns for selected countries or only in the case of specific product categories. Therefore, when creating a product campaign, it is best to check the feed requirements in our industry and in the country where we want to publish the advertisements. In simplified terms, however, it can be said that the information that must be included in the product feed includes:

– ID – unique identifier of the product. Ideally, it should be the same as in our warehouse identification.
– Title – the name of the product and the most important information about it. We will write a little further about what exactly it should look like.
– Description – in this field, describe the product in detail, using the keywords that are most relevant to you.
– Link – this should lead to the product page where you can make the purchase.
– Image link – address of the main product image, which will be available for indexing by Google.
– Availability – product status. It can have the value “in stock”, “unavailable”, “temporarily unavailable” or “presale” (in the case of the last two options, it is also obligatory to complete the attribute indicating the date of availability).
– Price – it must be consistent with the price on the store’s website and on the payment page.
– GTIN – Global Trade Item Number – GTIN is required only for products that have this manufacturer assigned number, but Google strongly recommends it be used for all products.

If the product feed includes the above-mentioned elements, it will be accepted by the advertising system, but it is not tantamount to high quality of the feed. These are only the basics and to get a high rating for the algorithm, you should also complete some of the attributes from the optional list. Before we get down to describing them, however, let’s figure out how to optimize this basic product data.

How to optimize your product feed titles?

The title is a very important element not only because it is one of the first pieces of information the user sees. It is also important because it is one of the main parameters that the algorithm takes into account when determining which keywords to display a given product on. Therefore, it is worth including not only information about the name of the product, but also, for example, its brand, color or size. We will repeat this information in other attributes, but if we also include it in the title, we increase the chance that the products will be displayed with the best queries in their case. The order in which the information is provided is also very important, which may be slightly different for different product categories. Google states that the best practices for title optimization for the most popular industries are:

– Clothes: Brand name + Gender + Product type + Product features (color, size, material, etc.),
– Food: Brand name + Product type + Product features (taste, number of pieces in a package, weight),
– Home & Garden: Brand Name + Product Type + Product Features + Model,
– Electronics: Brand Name + Product Features + Product Type + Model,
– Seasonal products: Opportunity + Product Type + Product Features.

Of course, these are not universal models that will work in all cases. For example, a brand name in a title will only attract an audience if it is recognizable and has a good reputation. So it’s best to experiment with names and test different options to choose the combination that works best for you.

It is also worth remembering that product titles may be displayed differently on different devices and thus the system may cut them off in some cases. We have 150 characters to use in the title field and it is good to use them, but make sure you have the most important information at the beginning of this section. In the Google Shopping tab, the titles are truncated after 70 characters, so it’s best to fit the most important data in this pool.

How to optimize the descriptions in the product feed?

In the case of the product description in the feed, we have 5,000 characters at our disposal. Of course, we don’t have to use all of them, but this field is a place for us to place many keywords. Admittedly, this will not guarantee that the product will show up for these words, but it does significantly increase the chances of it happening.

The description should not only be saturated with keywords, but also valuable for the user. Therefore, it is worth ensuring that it describes the product in detail and is of high quality. The description for each product should be unique, which increases the chance that the system will correctly select the one that best suits a given search query from the list of our products. For this field it is best to use a minimum of 500 characters, although of course the more useful information for the user, the better.

However, the question of where to get the information from which keywords will be most valuable for a given product remains. This is where the free Google Trends tool comes in handy. In it, we can enter terms that are associated with our product and check which of them are most frequently searched by users of the search engine. Thanks to this, we can include in the description those key phrases that have a chance to bring us the most impressions and clicks on the ad. For example, if Google Trends shows that “women’s black high heels” than “women’s black pumps” are more frequently searched for, it is worth using the first option in both the description and the title.

How to optimize product photos in a product feed?

An obligatory element of the feed is a link to a product photo, which the system can then use in advertisements. However, in order to obtain the best possible file quality, it is worth not to stop at one photo, but add a few to show the product more precisely. This can be done by using the Link to additional photo attribute. This attribute can be repeated 10 times for one product, which means we can add up to 10 additional photos. However, the standard is that for one product, we put 3-5 photos that show the product from different angles.

All photos should be of good quality, but their weight must not exceed 16 MB. Although in the official specification of the feed on the Google website we can find the information that the photos should have a minimum of 250 × 250 pixels for clothing and 100 × 100 pixels for other products, it is better to focus on photos with a higher resolution. The optimal size for product photos is 800 × 800 pixels. It’s a good idea to stick to these guidelines, because high-quality images improve your click-through rate and, as a result, can also increase your conversions.

Optional attributes that should be completed to optimize the product feed

As already mentioned, in addition to the basic data, it is also worth supplementing at least some of the attributes that are considered optional by the system. It is true that the file without them will be accepted and the ads will be displayed, but their effectiveness will not be as good as if we added additional information. Here are some attributes that should definitely be supplemented.

Brand
The Brand Attribute is most helpful when we sell products of well-known and frequently searched brands, but it is worth using in any case. However, this is an attribute that is often misspelled and can make your ads less effective, so pay close attention to it. A common mistake is to enter the name of your online store here, while the correct value is the name of the manufacturer of the product. So if, for example, we sell Nike sneakers in our store called XYZ, we should enter “Nike” in the brand attribute, not “XYZ”. Enter the name of your online store here only when our company produces the item from the offer. If the product does not have a brand or the brand is unknown, do not complete this attribute. It is a mistake to enter a value of the type “not applicable” or “missing” here.

Product group ID
This attribute is used to group products that come in different versions, such as sizes and colors. Thanks to this, they will not be displayed to users as separate products, but as variants of the same item, which will make it easier to get to know the offer and make a purchase decision. For all products to be grouped, we should add the same product group ID.

Size
This attribute is mandatory for clothes and shoes, but recommended for all products with different size variants. It is best to use the most popular sizes in the country where the campaign is to be used to determine this parameter. If a product is available in multiple sizes, it is important that you add the Product Group ID to all versions of the product. If the garment we sell has one size, we can enter the value “universal size” in the attribute.

Material
Material is one of the most important attributes for many products, including clothing, accessories, footwear and furniture. If the product has different material variants, each of them is added to the file separately and combined into one offer using the same product group identifier. It happens, however, that an item is made of several materials, e.g. a mixture of cotton and polyester. Then all the materials are added in one version in the Material attribute, separating them with the “/” sign without spaces, eg “cotton / polyester”.

Mobile link
If we have different URLs for traffic from computers and mobile devices, we can also complete the Mobile link attribute. Thanks to this, we will make sure that users using smartphones and tablets, after clicking the ad, will go to the subpages of our store optimized for these devices. This, in turn, will give them a better shopping experience for our brand. If the page URL is the same for both the desktop and mobile versions, we don’t need to complete this attribute.

What else can be done to optimize the product feed?

The high level of the product feed is also influenced by including information about product types in it and filling in the field with Google categories. Thanks to the proper classification of the product, the system is better at positioning the offer and adjusting it to the needs of the recipients.

It is also worth ensuring that only up-to-date information about our product range appears in the product feed. For this purpose, it is best to set up automatic product feed updates in Google Merchant Center once a day. You can also fix more frequent updates (up to 4 times a day), but such frequent refreshing of the product feed is only necessary in individual cases. In addition, if we make changes to the website, e.g. we add new products to the offer or introduce a promotion, we can also force the feed update manually, without waiting for the automatic download of data. When setting automatic updates, it is a good idea to choose night hours so that refreshing the file does not interfere with the display of ads to recipients.

SEO – increases after a year

We started cooperation in the field of online store positioning in July 2020. The website visibility status at the start of our activities was as follows:
31 phrases in TOP3,
366 phrases in TOP10,
3027 phrases in TOP50.

What does it mean? The website has already developed visibility in organic results for several dozen phrases. Therefore, our task was to increase the volume and calorific value of traffic from organic search results. We started by optimizing the site so that it would meet the high requirements of search engine web robots. We worked on improving the page loading time and organizing the assortment in terms of belonging to specific categories.

The site was experiencing cannibalization of content, which means that it was having trouble displaying a specific URL in response to a query that contained a keyword. Effect? Jumping positions of monitored phrases. Therefore, one of the first things we did was organize the texts to get rid of this phenomenon. We also commissioned writing new content – approximately 160,000 characters optimized for SEO enriched the client’s website. At the same time, we took care of external linking, paying particular attention to the diversification of links, i.e. their diversification.

During the cooperation, the client decided to change the category structure and URLs, which entailed the need to implement redirects so as not to lose the results achieved. Nevertheless, after a year of work, the website shows increases in terms of both the number of phrases in top positions and website traffic. In July this year, the client’s website was visible on:
82 phrases in TOP3,
675 phrases in TOP10,
5435 phrases in TOP50.

In the case of phrases from the top three results, this represents an increase of 164.5%. As for website traffic, the change is also clearly visible – it increased by 103% compared to 2020

Google Ads – How the number and cost of conversions have changed

In Google Ads, we run various types of campaigns for the client. Search ads, dynamic search ads, Smart Shopping campaigns (PLA Smart), remarketing and Discovery format are launched. This combination, in the case of the discussed brand, gives the best results and allows you to observe constant increases – both in website traffic and revenues. Let’s take a look at how the overall results for all campaigns changed from January 2021 to July 2021.

In January, the total number of clicks on Google Ads ads was 15,000, while in July it was 35,917, indicating a significant increase in paid traffic. The mere increase in the number of users, however, does not prove the effectiveness of the campaigns carried out. The parameters that indicate this are the generated revenues, the increasing number of transactions or the cost of a single purchase. In January, thanks to the ongoing activities of Google Ads, 196 transactions were registered on the website, and the cost of one was around $ 65.42. In July, conversions were already 796, and the cost of a single conversion was close to $ 40.54.

This means an increase in the number of transactions by 306% with a simultaneous decrease in the cost of acquiring a customer by 38% over the last six months of the campaign.

Regular profits from the campaign at a satisfactory level allowed for a gradual increase in the Google Ads advertising budget. Over the indicated time frame, it increased from approximately $ 6,500 to $ 16,500, representing a 157% increase in ad run. At the same time, revenue increased from $ 40,000 to $ 197,500, or 392%. So the return on investment increased by 175%!

It is also worth mentioning here how important Google Ads are in relation to the total revenues of the website. In 2019, the revenue generated by Google advertising campaigns accounted for 26.7% of the website’s total revenue. In 2020, this share increased to 36.6%, while in 2021, considering the period from January to August, this value is 37.9%.

Facebook Ads – the beginnings of activities

Less than a month ago, the client also transferred advertising in social media under our wings – on Facebook and Instagram. At this point, we are at the stage of determining the operating strategy, testing various advertising formats and collecting data. All these activities are guided by one goal: generating sales equal to the level of Google Ads. The first ads are already on the web and are in great demand, bringing people involved to your site.

Performance Max – what is it?

Performance Max is a new type of Google Ads campaign that is based on the operation of self-learning algorithms. This is not a complete novelty in the Google Ads environment. Users of this system are familiar with other types of campaigns in which ads are optimized automatically, and the tool itself adjusts bids or mixes uploaded advertising elements, such as banners, texts and logos, to find the most effective combinations. We know this model of operation from such formats as intelligent product campaigns or flexible advertising in the search network. Performance Max, however, goes a step further – it ensures optimization of ads in many channels within one campaign. Designed to complement your keyword search campaign, this new feature gives you access to all of your Google inventory from one place.

What does this mean in practice? Using Performance Max, we create one campaign and use it to display ads in all places provided by Google Ads, i.e. the search network, advertising network, YouTube, Gmail, Google Maps or Discover cards. The selection of the best resources for our advertising is done automatically in real time, based on the data collected 24/7 by the algorithm.

How does the Performance Max campaign work?

Peformance Max campaigns are based on marketing goals, which we define in the first steps of creating advertisements. So we can determine at the very beginning whether the goal of the campaign is, for example, target cost-per-action (CPA) or we prefer to focus on target ROAS. The wizard will also ask you to add the appropriate materials and define basic settings. At this stage, you should provide the preferred duration of the campaign (minimum 4 weeks) and specify the budget, geographic coverage of the ads and the group of recipients. In addition, we also need to provide the system with:
– headers and descriptions for text and display ads,
– graphics for Discover and Display ads and on YouTube,
– company logo,
– video for YouTube InStream ads,
– product feed from Google Merchant Center.

When we launch a Performance Max campaign, the system takes into account the data from all advertising inventory, analyzes user behavior at a specific moment and on this basis optimizes bids and buys spots for our company’s ads. It works in real time, so it gives us the best results in all channels at any given time.

Audience Signals – a new method of selecting the target group

With the entry of Performance Max, a new method of searching for the most valuable recipients for given advertising creations has also appeared – Audience Signals. This method of determining the target group is a combination of Google’s automatic targeting with our knowledge of the brand’s customers. As part of Audience Signals, we can identify the group that is the most important for our business and, in our opinion, gives the best chance for conversion. The system may, however, extend the reach beyond this specific group if it foresees that this may increase the profits of the campaign. This solution is to shorten the learning time of the algorithms, and thus improve the campaign results.

Performance Max and other types of campaigns

But why did Performance Max appear at all, when it was possible to run all these formats as part of separate campaigns? This is Google Ads’ response to the constant changes in customer behavior and shopping paths. Today, 70% of consumers buy online more than in the pre-pandemic era. At the same time, however, their path to conversion is changing faster and faster and it is difficult to predict on an ongoing basis what it will look like in the future. In addition, the conversion path often becomes significantly longer – Google reports that in some cases it reaches up to 500 points of contact between the user and the ads before the conversion takes place. In such a changing reality, only a well-developed algorithm that learns consumer behavior can help in data analysis and campaign optimization. If, within one campaign, he can analyze the effectiveness of all channels in which the ads are displayed, he has enough data to better predict what rates, places of emission, etc. will be the best choice at the moment.

Will it be so in reality? Time will tell. Currently, this format is still little used and some river water has to pass before something can be said about the novelty of Google. Certainly, this type of campaign has potential for companies that have a large advertising budget and run many different formats at the same time. Currently, we can read on the Google website that the beta tests for Performance Max have turned out promising, and advertisers who use this campaign are seeing an average increase in the number of conversions of 13% with a similar budget as in the case of separate campaigns for each format. That is why Performance Max is a novelty that is worth keeping an eye on and which in the future may well settle among the most popular solutions for companies with large budgets.

Discrepancies in the analysis of the number of clicks and user sessions

The first differences between Google Analytics statistics and Facebook statistics can already be seen in the method of counting clicks and user sessions. So let’s start by explaining these concepts.

– A click is a parameter that sums up all users’ reactions to a given ad. So if you click the ad once and then click again, Analytics counts that as two interactions with the ad.
– The session, in turn, shows how many users clicked on the ad. Two or more clicks of the same user will be considered by the system as one session, provided that they occur within a 30-minute time window. Only when the time interval between clicks is greater, will the actions be considered as two separate sessions.

Up to this point, everything is quite simple and it would seem that there is no room for discrepancies in the counts here. And yet. Because when can you start counting users who actually reacted to the ad? Google Analytics claims that only when the user is on the page to which the ad is referring him. After all, he might have clicked the ad by accident and stopped loading or closed the tab in the browser before the landing page was fully loaded, and this is hardly an ad success. Therefore, such “incomplete” transitions are not counted in the Google Analytics system.

Facebook, on the other hand, will record each click, i.e. the user’s interaction with the ad, even if the recipient does not fully see the landing page or does not go beyond the Facebook platform at all. It is true that in the Facebook Ads Manager you can measure not only all clicks, but also clicks on links that lead beyond the platform – to the advertiser’s website. However, the Facebook system will also count those clicks that did not fully load the landing page. What is the conclusion of this? The number of clicks reported in the Facebook Ads Manager may be greater than the one we see in Google Analytics.

Tracking users between devices

Analytics is therefore much more accurate when it comes to counting sessions and clicks on a single device level. What about the situation when the user is using different devices and clicks on the ad, for example, first on the phone and then on the computer? Here, Facebook is much better at counting. This is because in order to use Facebook and thus click any advertisement there, the user must be logged in to his account. Most users use the same account on all devices, so Facebook’s algorithm has no problem distinguishing when it is dealing with the same user and when not.

In Google Analytics, the default data collection is based on cookies, and these are assigned to a specific device. Hence, each change of the device by the user qualifies him as a new person.

What does this mean in practice?

If the recipient first clicks on the ad on their phone and then reacts to it again on their computer, Google Analytics will register the ad as two separate users from different traffic sources. On the other hand, Facebook, if the recipient is logged into the same account on both of these devices, will recognize him as the same person.

Differences in attribution models

Conversion may be preceded by a variety of user actions. This means that before he or she fulfills our goal, e.g. buys an item in an online store, he may deal with the website in various ways. Let’s see it with an example. The user sees an ad for shoes from your Facebook store. He clicks it, looks at the shoes, but decides not to shop. After a few days, he decides that he needs shoes and enters a query to the Google search engine, for which he will receive an advertisement in the search engine with a link to your website. He clicks on the link, looks at the same shoes again, but decides to ask his wife for opinion before buying. In the evening, he will enter the search query again, but will not click the sponsored link, but choose an organic result, and this time he will buy shoes.

So to which interaction with the website can this purchase be attributed? Did the first contact with the offer, i.e. Facebook advertising, decide that the user has performed the assumed conversion? Or maybe the user did not remember it anymore when he searched for shoes in the search engine? So then the sponsored link would make it hit your store and make a purchase there. But after all, he did not buy shoes by entering the site through an advertising link, but through an organic result, so maybe he should be “responsible” for the conversion? On the other hand, there is a chance that the user initially had no plans to buy shoes and it was only advertising on Facebook that awakened this need in him. In this situation, the first ad would do its part to persuade him to buy.

The questions are constantly multiplying and it is not easy to find an unambiguous answer to them. Therefore, individual analytical tools may adopt different methods of calculating ad effectiveness, i.e. they have different attribution models. We will now show you what it looks like in the case of the Facebook Ad Manager and Google Analytics.

Facebook Ads Manager – attribution model

If the user makes a conversion on the page within 7 days from clicking on the ad, Facebook Ads will assign it to his ad (of course, if we have a well-configured FB pixel). The same will happen if the recipient meets the target within one day of being shown the ad. It is true that the user could later have contact with ads in other channels, but Facebook will attribute this success to itself anyway. This is currently the default attribution model for this channel and may be objectionable but legitimate. Facebook is not a strictly sales channel, so the task of advertising on this platform is to arouse the user’s desire to buy. So even if an advertisement did not lead to a purchase, but sowed a seed in the user’s mind, which then germinated and gave fruit, it is also a merit of advertising on Facebook.

For example, the recipient might want to compare prices with competitors before buying, or look for opinions about the presented product in order to finally go directly to the company’s website. However, he found it through an ad on Facebook, so the system rightly recognizes its participation in such a conversion. In addition, the Facebook system is not able to control whether the user was later exposed to ads created by other systems, so the assumption that the Facebook Ads campaign influenced the recipient’s decision is the best way to count conversions.

However, is it reliable? Unfortunately not. For this system, clicking an ad is not synonymous with loading the landing page, as we have already written about above. It’s even more difficult when counting views. Facebook’s algorithms take into account whether the advertisement was displayed to the user, but they do not measure the time that the advertisement was visible on the user’s screen. So it may turn out that yes, it appeared on the page, but it was scrolled so quickly that the user did not have a chance to even notice it, let alone read its content. Nevertheless, if the user subsequently performs a conversion within a certain period of time, Facebook counts the conversion as obtained from its ad.

Google Analytics attribution models

By default, Google Analytics uses a different attribution model – the last indirect input is counted as the one that decided to convert. What is an indirect input? Simply put, it can be any way to enter a website, except for directly typing its address in the browser bar. So if, for example, a user clicks on a Google Ads ad, but does not buy anything, and then enters the page by typing its address into the browser and converts on the page, Google Ads will receive the credit for it. Comparing this counting system with the Facebook system, it is easy to notice that the results of Facebook Ads campaigns in Analytics may be weaker than in Facebook statistics.

However, Google Analytics also offers other attribution models, and changing the default settings can significantly change the results presented by this tool. We can choose models such as:

– Last interaction – then the system assigns all credit for the conversion to the channel that the user used immediately before the conversion. This setting makes sense when your ad is targeting people who are determined to buy, not those at an earlier point in the funnel.
– Last Google Ads Click – All 100% “responsibility” for the conversion is attributed to the last ad displayed by the Google Ads system that the recipient clicked before converting. It is worth using this model only when you want to compare the effectiveness of Google Ads. Does not apply to statistics for Facebook ads.
– First Interaction – In this model, Analytics considers all credit for conversion to go to the channel where the user first encountered our site. It can be used in this case when we want to build brand awareness with advertising.
– Linear – considers 1 conversion = 100% and grants equal percentage of share to all channels through which the user came into contact with the page. So if he first saw an ad on Facebook, then clicked a sponsored Google Ads link and made a purchase, he will attribute 50% of the value of this conversion to Facebook Ads, and the other 50% to Google Ads. It is best to use this model when each user contact with the website is important to us.
– Timing – assigns different conversion shares to channels, depending on how many days before the conversion was done by the user. The closer the contact with a given channel is in time, the more important that channel is.
– Including items – this model also divides the share between channels that are on the purchasing path, but does not take time into account. Most often, in this model, 40% of the conversion value of the first interaction is assigned, 40% of the last interaction, and the remaining 20% ​​is divided equally among the other channels on the purchasing path.

Google Analytics or Facebook Ads – which statistics should be taken into account?

Advertisers often try to unify the results obtained from both tools as much as possible. You can, for example, change the attribution in Facebook Ads so that conversions are counted only within 1 day of clicking on the ad. However, before taking such steps, it is worth analyzing your business and industry or tracking the average length of your audience’s conversion path. Sometimes it’s not necessarily about fixing the discrepancy, but about accepting that both Google Analytics and Facebook are complementary tools that can be used in parallel to better understand your business with web analytics and make better marketing decisions.

Our client has been operating on the market for almost twenty years, selling cameras and photographic accessories for both amateurs and professionals. It offers high-quality laboratory equipment and services, thus providing its recipients with comprehensive service. In the case of Google Ads for this client, we operate equally completely: we run text, product, video (on YouTube) and display campaigns, including remarketing. We’ve already got to know your audience, so we can focus on campaign optimization, achieving more and more conversions within our budget. Let’s take a look at how the combined results of all these campaigns changed over the course of a few months – from March to June this year.

Clicks and conversions

Testing and optimization measures in the customer’s account have led to a significant change in the number of clicks. At the turn of February and March, advertisements collected about 11,000 clicks, and in May-June it was slightly more than 15,000 clicks per month, which is an increase of 39.9%.

However, this parameter is not the most important in ad statistics – clicks in themselves increase website traffic, but they do not have to be associated with the achievement of the most important goal, which is the purchase. What’s more, a large number of clicks with a small number of transactions may indicate a poorly selected target group or an unclear advertising message. In this case, however, it can be seen that both the recipients and the content of the message have been correctly selected. You can see this clearly in how the number of conversions has changed over the period – it increased by 85%. The cost of obtaining them changed very slightly, only by slightly more than 5%.

Profits from the campaign

The good results achieved in the campaigns made the client decide to allocate more funds to Google Ads – in three months the budget almost doubled (by 94.07%). In February / March, we spent about $ 8,000 on advertising on Google, and at the turn of May and June, over $ 15,000. The client’s willingness to invest led to even more tests, which made the results even more satisfactory. Revenue increased from $ 114,374 to $ 560,431, almost 390%. In other words, raising the budget by about $ 7.5 thousand allowed to achieve income higher by over $ 446 thousand.

Return on advertising investment in Google Ads increased from 1,416% to 3,575%. What does it mean? Simply put, at the turn of February and March, each dollar spent brought about $ 14 in revenue, while three months later it gave almost $ 36.

Facebook Ads

The results from Facebook ads show even greater progress. In their case, however, it should be noted that the default data attribution settings are selected in such a way that the system also counts indirect purchases in the statistics. What does this mean exactly? When counting conversions, it takes into account the attribution model 7 days after the ad is clicked and 1 day after it was displayed. As a result, he also credits himself with conversions that have already taken place in other channels and for which Facebook did not have to be the last channel on the shopping path.

This is justified, because Facebook is a channel that does not respond with advertisements to the directly expressed shopping intention in the search engine, and selects advertisements that best match the user’s preferences.

Clicks and conversions

The number of clicks on Facebook Ads did not change as rapidly as in the case of Google campaigns – it increased from 7803 to 8709, i.e. by about 11.6%. However, as we have already mentioned, clicks do not directly translate into profits, and the most important statistics parameters are the number and cost of conversion. In the case of the number of conversions, the increase is more clearly visible – from 132 to 184, i.e. by 39.4% in three months. As for the cost of a single conversion, the level remained very similar – the fee for acquiring one customer decreased by $ 1.51, a decrease of about 3.5%.

Profits from the campaign

We increased the budget for the Facebook Ads campaign by 34.6%, or about $ 2,000. The revenue generated thanks to this channel increased by $ 685,573, which, with the given budget, means an increase of 283.4%. ROAS, i.e. the return on investment for this campaign for the period May 16-June 15, 2021 was 11981%, which, even when counting indirect purchases, is a very good result for this type of campaign.

The most effective advertising for big players

The programmatic campaign was carried out in April this year and lasted a month. Our client has just introduced a new product to the market, so the main goal was to achieve the widest possible reach of advertisements to reach the largest possible group of potential customers. At the same time, however, we did not want to lose quality, so the campaign was to be visible mainly on high-quality portals that were very popular among Internet users. We have been cooperating with our client for a long time, creating other types of campaigns, so we knew his recipient profile, which made it easier for us to choose the means to achieve the set goal.

We decided that the best solution for the client would be to use video ads published on YouTube and in places automatically purchased by the Programmatic system as part of Open Auctions. We supplemented these activities with the Display campaign, using, among others, the Rich Media (Parallax) creation, whose advanced functions increase the possibilities of interaction with the recipient. We also decided to use animated HTML5 banners, which draw the attention of a typical user much better than traditional ones. What effect did the chosen strategy bring? In a month, it managed to reach 22,823,700 views in the most attractive advertising spaces on the Internet.

When it comes to impressions, the natural question may arise as to whether the ad was actually spotted and worked. After all, the creations could appear in a place where the user will not notice them, or they could be scrolled so quickly that it was impossible to register the message. To avoid such doubts, the viewability parameter was created, which determines what percentage of displayed ads was most likely actually seen by the recipient. In the case of the discussed campaign, viewability was at the level of 89%, which means that almost every display was related to the achievement of the assumed goal.

The best surfaces at optimal prices

But let’s move on to a more detailed campaign analysis. As the main goal of advertising was to familiarize as many potential customers as possible with the new product, we focused on different formats and different environments – this maximized the chance of achieving the expected reach. Different activities in different systems and display places, however, always carry the risk of burning through the budget. In optimization activities, we focused mainly on minimizing the cost of impressions without losing their number and, of course, the quality of placements for advertising. We also set a common capping for all formats, i.e. the maximum number of ad impressions per day per user. Thanks to this, it was possible to avoid unnecessary expenses on repeating the message to recipients familiar with it, and thus reach a greater number of new potential customers.

We also took care to exclude low-quality placements on an ongoing basis, which allowed us to maintain high-quality broadcasts throughout the campaign. As a result, the ad was most often displayed in such recognizable and prestigious placements.

Of course, we also paid attention to brand safety, i.e. securing the brand’s reputation. Throughout the campaign, we made sure that advertisements did not appear on websites rich in controversial content or in provocative contexts that could harm the client’s image.

Programmatic campaign costs

The entire month of the campaign is also the work of both our specialists and self-learning algorithms on issues such as budget relocation and bid optimization to achieve maximum reach within the assumed budget. As a result, we significantly reduced the costs of the campaign – a single impression averaged 2 cents for open auctions in Programmatic and 3 cents for the YouTube platform.

– Average CPV Video total: $ 0.03,
– CPV Programmatic Average Open Auctions: $ 0.02,
– YouTube average CPV $ 0.03.

In the case of CPM rates, i.e. per thousand ad impressions, the costs were as follows:

– Average CPM total: $ 3.66,
– YouTube average CPM $ 12.7,
– Average CPM Programmatic Video open auctions $ 3.90,
– CPM Display Programmatic average open auctions $ 2.21.

The total cost of the campaign was $ 83,500 and allowed to reach almost 23 million views. So optimizing your bids resulted in a number of impressions close to the population of Texas. Of course, this does not mean that so many people saw the client’s advertising creations, as promotional videos and banners could be displayed several times to the same users. Still, this is the reach that has significantly helped raise awareness of both the brand and the new product.

It should not be forgotten that Programmatic is an advanced system that collects huge amounts of data about Internet users in order to display advertisements only to those who are likely to be interested in the offer. This is a significant advantage over television or outdoor campaigns, in the case of which we have very little influence on the selection of the target group, and thus the final result of activities.

The client in question produces and sells textile products, both wholesale and retail. He has extensive experience in the market and has an excellent reputation among customers, but nowadays – in the era of great competition – it is not always enough to achieve the profits that could be wished. However, if you add an additional brick in the form of optimized Google Ads advertising, the image begins to take on more optimistic colors. What can be achieved by investing in such campaigns and entrusting them to the care of a specialist? We discuss it by comparing the results from the turn of January and February this year with the results for April / May.

Clicks

Ad clicks decreased slightly compared to the beginning of the year, but this decline is not cause for concern. In the optimization process, we constantly strive to reach a specific group of recipients who are actually interested in buying. Therefore, changes to campaigns may result in a drop of non-converting blank clicks. However, as you can see later, fewer clicks doesn’t mean less revenue – quite the opposite in this case.

The number and cost of the conversion

The conversion bars look completely different – in January there were 75 of them, while in May 109, which means an increase by 45.33%. Our goal, however, was not only to increase the number of transactions, but also to increase the number of wholesale B2B orders. Thanks to the client’s openness to our suggestions, we were able to carry out tests and implement changes that allowed us to achieve this goal as well – currently the number of such transactions remains at a very high level.

At the same time, we also worked on reducing the cost of conversion so that we could achieve even better results with the same budget. From January / February to May, it was reduced by a quarter, or almost $ 17.

How does this affect the income?

In recent months, the campaign budget has increased only slightly – a difference of about $ 400, which is less than 10% of all Google Ads funds. With the total cost almost unchanged, however, our revenue was 87.04% higher than 3 months earlier, which in this case is over $ 21,000.

The return on investment (ROAS) almost doubled and eventually reached 847%. More figuratively speaking, in January every dollar spent on campaigns brought the customer an income of $ 4.90, and in May the same expense resulted in an income of almost $ 8.50.

Campaign results

Can this result be achieved for each campaign? Unfortunately, the reality is not that rosy. The success of the campaign depends on various factors, some of which are completely independent of both us and the customer (competition, market situation, shopping seasons, etc.). It also happens that the very budget that the client decides to spend on advertising is a limitation. Therefore, for each new contract, we propose the optimal budget and advertising formats, which, according to our experience, should bring the best effect. The fact that we know what to propose is evidenced by results such as those above.

POCM – what is it anyway?

First, however, a short piece of information for those who have not come across this system so far. POCM is our tool that helps in improving the results of campaigns conducted in Google Ads. It is based on statistical models and self-learning algorithms that collect data about campaigns 24 hours a day and automatically optimize them so as to maximize the probability of achieving previously set goals.

When designing POCM, we especially had in mind that the platform should be simple and intuitive to use and that it would enable effective campaigns using the latest and most effective technologies, also for people who do not have specialized knowledge in the field of online advertising.

What’s with bidding strategies?

It sounds specialized and may sound complicated, but choosing a bid optimization strategy is not a plan for the Battle of Waterloo. Strategies are simply used to achieve a selected business goal that we want to achieve through a campaign. These goals may be different. At various stages of marketing activities, we may, for example, want as many people as possible to see our advertisement, to convert as many users as possible, or simply to reduce the costs associated with advertising as much as possible. A different strategy is used to achieve each of these goals. Its choice determines which parameters of the campaign the system will focus on the most in the optimization process.

As already mentioned, we currently have over 50 such strategies. We will not describe all the available options here, but we will focus on explaining what can be achieved with the most popular ones.

Maximize conversions based on your budget

In this strategy, the system uses the available budget in such a way that it appears evenly and as efficiently as possible. This means that if there is little money left, it goes first to the key phrases that generate the most conversions. Therefore, this strategy is a good solution for people who cannot afford large advertising expenses – thanks to it we minimize the likelihood of a budget constraint.

Maximize your income

If we choose a strategy to maximize revenue, the algorithms will focus not on individual key phrases or advertised products, but on entire campaigns. When we run many of them, they analyze the effectiveness of each of them (of course, provided that we have this strategy set for all of them), and then distributes the budget so that the total income from all of them is as high as possible. This strategy works best when the system has a lot of data, so it is intended for people with a large advertising budget and who can afford to run a large number of campaigns.

Target ROAS

Target ROAS is that the system aims to achieve a return on investment as determined by us. Let’s show it with an example – for example, we can assume that we want every dollar spent on advertising to bring us $ 3 profit. In this model, algorithms use data to identify key phrases or products that have yielded a large number of valuable conversions in the past. They set higher click rates for them, while other phrases / products have a lower rate. The danger with this strategy is setting an unrealistic, high ROAS, because it can lead to a budgetary constraint. Therefore, it is worth entrusting the determination of the return on investment to a specialist – he will set the achievable return and will gradually increase it, if the campaign produces satisfactory results.

Target CPA

In the target CPA, we define the rate that we are willing to spend on acquiring one user. However, this does not mean that each conversion will cost exactly the same. The system will analyze the behavior of users and on this basis it will reduce or increase rates on specific devices, at given hours, etc. However, it will always strive to ensure that the average cost of acquisition is at least as agreed. In this way, it will provide us with the greatest number of conversions at a given cost-per-acquisition. This strategy works especially when the specific cost of customer acquisition is important to us and when the algorithm has a lot of data on the basis of which it can predict user behavior.

Maximize clicks based on your budget

As you can guess, the goal of this strategy is to get as many clicks as possible within your budget. It’s similar to budget-based conversion maximization, and is an alternative when we don’t have conversion tracking implemented. It also works well when we have a very small budget, and thus few conversions – then there may be too little data for the system to correctly predict which phrases / products will bring the most of them. In addition, it is not always possible to determine a conversion action, and we often want to get as much traffic as possible on the page – then maximizing clicks will be a great solution.

Target Impression Share

This strategy allows you to achieve the assumed percentage of views – algorithms automatically set bids at such a level to win a certain number of auctions. When choosing this option, we have to decide which ad display place we want to fight for. There are three options here: first result on the page, displayed at the top of the results page, or displayed anywhere on the page. Here you can limit the maximum bid that the system can set, but for the campaign to work properly, it cannot be too low. Then it would be impossible to win the appropriate number of auctions.

Improved CPC

As part of the Enhanced CPC, we set a click bid for your ads ourselves, but the system may automatically increase it if it determines that there are conditions under which the likelihood of conversion has increased, or decreased when the chance of conversion is low. With Enhanced CPC – aka eCPC – you can optimize your bids to increase either the number of conversions or the value of your conversions.

A solution tailored to your needs

POCM users can use many other strategies available within the platform. After signing the contract, the customer is contacted by a specialist from the Support Department, created specifically to support the users of this particular platform. It proposes the best strategy and ad formats in a given industry and budget, choosing from the options available in the package selected by the client.

After accepting the plan, he sets up a campaign and optimizes it manually for a month, while the algorithms collect data in order to adjust the rates independently in the future, implementing the assumed strategy. After the first month, the company no longer interferes with the campaign, but the customer has the option of updating or adding new keywords, ads, etc. He can also view ad statistics and compare the results from different periods. Therefore, it is a platform that gives the client a lot of freedom, while providing advanced algorithms, and this in total gives a tool that allows you to create modern, constantly optimized campaigns with any budget.