7 ways Google Ads can influence marketers’ decisions

The information that attracts your attention in Google Ads can influence where you allocate your advertising budget, what changes you make to your campaigns, and how you evaluate their performance. Here’s what to pay attention to.

Experienced Google Ads specialists know where to find the data they need to optimize and analyze advertising campaigns. At the same time, many less experienced advertisers are not even aware of the layers of information they are missing.

In such an environment, misleading or incomplete information can effectively replace data that is less visible or more difficult to find. As a result, advertisers may unconsciously adopt approaches and conclusions that align with the logic of the advertising platform.

If you are not a beginner and regularly monitor your advertising accounts, why should this concern you?

Because of second-order effects.

If you are Advertiser A and manage your account effectively enough, shortcomings and under-optimization in the accounts of Advertisers B, C, D, E, and F can create various changes in advertising auctions. Those changes can ultimately affect your campaigns as well.

That is why it is important to understand what incentives and information signals Google Ads creates within the platform, why advertisers tend to respond to them, and how to minimize their influence on decision-making.

Below are seven examples of information and settings in Google Ads that may be overly prominent, misleading, or, conversely, insufficiently accessible for analysis.

How Google Ads uses the availability heuristic

The availability heuristic describes a situation in which people tend to form judgments based on information that is easy to recall or immediately available at a given moment.

For example, consider the safety of air travel. If someone regularly hears vivid stories about plane crashes, they may overestimate the risks of flying, even though statistically, aviation remains one of the safest forms of transportation.

This is how the information environment works: vivid examples and narratives often have a greater influence on perception than dry statistical data.

Google Ads adds another layer to this situation. Google itself directly shapes a significant part of the information environment within the advertising platform.

This makes platform-oriented ideas more prominent to advertisers precisely when they are making decisions about how to use their advertising budgets.

Even the names of features and campaign types can be part of this approach. For example, names such as Performance Max, AI Max, Smart Bidding, and Demand Gen can influence how advertisers perceive the corresponding tools.

Names matter when they influence decisions about budget allocation.

Let’s look at seven of the most common examples.

Dashboard data presentation

At the account or campaign level, many advertisers may leave the default set of key performance metrics provided by Google Ads, including comparisons with the previous period.

However, this approach is not always optimal.

First, it is worth asking: why are results being compared specifically with the previous period?

For most businesses, a year-over-year (YoY) comparison may provide much more useful information. This approach helps avoid misleading conclusions caused by seasonal fluctuations.

For example, comparing December advertising results with November may not provide enough context to evaluate performance. By contrast, comparing December of the current year with December of the previous year provides a better way to account for seasonality.

Second, aggregated impression and click volumes do not always have the same significance for a business as revenue or ROAS.

For a company investing significant amounts in Google Ads, it is important to understand not only how much traffic campaigns generated, but also what financial results that traffic produced.

If a marketer constantly sees impressions and clicks on the main dashboard, these metrics may gradually become perceived as the primary indicators of performance.

Therefore, it is worth configuring the dashboard around actual business KPIs rather than simply using the default set of metrics.

Columns

A similar issue applies to the default set of columns in Google Ads.

By default, the advertising interface may display a large number of metrics, some of which are not critical for a particular account.

As a result, information overload can overshadow the data that is actually needed for decision-making.

The following metrics may be important for analyzing advertising campaigns:

• number of clicks;
• CTR;
• conversion value;
• conversion value divided by cost;
• CPC.

However, the set of metrics should be determined by the specifics of the particular account and business model.

Therefore, it is worth determining as early as possible which metrics are critical for evaluating campaign performance and which are not needed for regular monitoring.

In Google Ads, you can customize the displayed metrics through Columns > Modify.

At the same time, even the names of some available columns can influence how a situation is perceived.

For example, Absolute Top Impression Share and Top Impression Share can be useful for assessing the competitive environment.

Other metrics, such as Search Lost Top IS (Rank), may create additional information noise if a marketer does not use them for a specific analytical purpose.

The general principle is simple: if a particular metric constantly prompts you to react to it but does not help you make informed decisions, it is worth asking whether it should remain part of your core set of metrics.

Number of rows

When working with data in Google Ads, advertisers may notice another issue: the number of rows displayed on a page sometimes returns to the minimum value of 10.

For many accounts, 50 or 100 rows may be a more practical working setting.

At first glance, this may seem like a minor detail. However, additional page navigation creates friction when working with an account.

The more pages you need to review, the more likely it is that some campaigns or other account elements will receive insufficient attention.

As a result, some advertisers may optimize only a few campaigns or review the data on the first few pages before moving on to other tasks.

This friction directly affects the quality of account management.

The more unaddressed or insufficiently optimized areas remain in an account, the longer they may continue accumulating problems.

This is particularly relevant for large or inherited accounts with a high number of campaigns.

If a marketer takes over a complex account with an excessive number of campaigns, they should not simply maintain the existing structure. It is worth assessing whether the structure should be consolidated.

In many cases, simplifying the structure and eliminating duplication can make budget management more effective and improve financial results.

Optimization Score and recommendations

Google regularly encourages advertisers to review and apply recommendations within their accounts.

For this purpose, the platform uses, among other things, the Optimization Score and categorized recommendations.

Visual elements within the interface further draw attention to these suggestions and encourage advertisers to review them.

However, the presence of a recommendation in Google Ads does not mean that applying it will automatically improve results for a particular business.

For example, the platform may recommend removing duplicate keywords and enabling Display Network expansion.

The first recommendation may have a limited impact on performance depending on the account structure.

The second could potentially have a negative impact if the additional traffic does not align with the campaign’s objectives.

Therefore, the Optimization Score should not be treated as an independent assessment of the quality of an advertising strategy.

For a marketer, it is more important to evaluate whether a specific recommendation aligns with the business objectives, advertising strategy, and actual campaign performance.

Target metrics at the ad group level

Surface-level account management may not be enough to understand the reasons behind changes in performance.

Consider the following situation.

Suppose a campaign has a target ROAS of 350%. This target was set by a previous specialist.

The marketer gradually increases the target, expecting this to make the campaign more efficient, reduce costs, and increase ROI.

However, the results do not change.

In this situation, the marketer may begin to assume that the campaign is not working properly. Eventually, they may reduce the daily budget, pause the campaign, or attribute the deterioration in performance to external economic factors.

But the real reason may be something completely different.

Target metrics may be set at the ad group level in the range of 210% to 260%.

These settings may take precedence over the campaign-level setting that the marketer has been repeatedly changing.

If the marketer does not open the campaign and check the settings at a lower level, identifying the cause may be virtually impossible.

This example demonstrates why a surface-level campaign analysis is not enough.

Marketers need to understand the hierarchy of settings and check at which level the parameters that affect automation and performance are actually configured.

Search query report

Beginners often do not fully understand the difference between keywords and users’ actual search queries.

A keyword in an account and a specific query entered by a user are not the same thing.

In addition, less experienced advertisers may not use the search query report to regularly monitor traffic quality.

This creates a risk that advertising budgets will be spent on queries that do not match the business’s specific offering.

Examples of search queries that may need to be added as negative keywords at the ad group, campaign, or account level include:

• navigational branded queries that artificially increase ROI metrics for campaigns focused on acquiring new customers;
• single-word queries, such as “office,” if a company sells specific products or services within this category;
• brands and products that are not part of the company’s offering;
• competitor names, if targeting them is not part of the advertising strategy;
• brands and products that should be directed to other campaigns or parts of the advertising account.

Regular search query analysis helps maintain better control over how closely paid traffic matches the advertising offer.

For companies with large budgets, this is particularly important because even a small share of irrelevant queries, when multiplied across thousands or tens of thousands of clicks, can result in significant unnecessary costs.

Conversion counting

Another important aspect is conversion tracking and determining which conversions should serve as primary KPIs.

The first step is to identify the business’s key performance indicators, select the primary KPI, and retain a few secondary metrics for monitoring and additional context.

If the business requires more detailed analysis or needs to work with several primary metrics, some goals can be analyzed through Google Analytics or the relevant conversions can be imported into Google Ads and classified as primary or secondary.

However, as new conversions are added, the system can quickly become more complicated.

This is particularly relevant for mature accounts that have been managed by different specialists and teams over an extended period.

In such cases, different managers and stakeholders may have added their own conversions and established different rules for how they should be used. As a result, the logic behind KPI management can become inconsistent.

The first step when auditing such an account is to check whether different users have set practically identical conversions as primary.

In practice, this happens quite often.

After that, the remaining conversions should be reviewed.

For example, events such as store visits or requests for directions to a store may have limited value. At the same time, they can be useful as indicative metrics if they occur infrequently and provide additional insight into user behavior.

However, if such conversions are generated too frequently and distort the assessment of actual revenue, using them may negatively affect optimization.

In some cases, it may be appropriate to exclude such events entirely from the primary performance measurement system.

How to avoid platform influence on marketing decisions

These are just seven examples. In reality, there are many more ways in which the structure and information environment of Google Ads can influence advertiser behavior.

Working with an advertising platform involves constant choices: which metrics to review, which recommendations to apply, which campaigns to scale, which settings to change, and which results to consider successful.

The problem arises when these decisions are based primarily on what the platform makes most visible.

An advertiser may see a recommendation without seeing the full context of its potential impact.

They may see an increase in the number of conversions without considering their quality.

They may see a high ROAS without noticing that a significant portion of the result comes from branded traffic.

They may increase the target ROAS at the campaign level without knowing that settings at the ad group level are actually determining different system behavior.

That is why it is important to regularly look beyond a surface-level view of the advertising account.

Marketers should independently determine which data matters to the business, which KPIs should be used to evaluate results, and which settings actually affect performance.

One advantage is that Google Ads does not hide every level of configuration. In many cases, marketers can still open the relevant section, move to a lower level, and check what is actually happening within the account.

The key task, therefore, is not simply to use Google Ads tools, but to control the information environment on which decisions are based.

The larger a company’s advertising budget, the more important it becomes to understand the difference between what the platform encourages you to see and what the business actually needs to know to manage advertising investments effectively.

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