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Beyond the click: The hidden relationships driving your Google Ads performance

The metric overload trap

Whether you’re a seasoned PPC pro or a novice in the industry, looking through the readily available metrics in the Google Ads UI can seem daunting. Understanding the Google Ads metrics relationships will make your life a lot easier.

It’s true that there are a lot of metrics on the platform these days, but each one helps paint a clearer picture of how campaigns are performing at a general level. On top of this, you even have the option to create and track your own metrics using custom columns. This helps you to better understand your campaign performance based on KPIs that are unique and beneficial to your business.

These custom columns are formulaic in nature and can reference existing columns or use your unique conversion actions and goals within the formula to build out new metrics.

To master the art of PPC, you not only need to understand what each of these key metrics mean, but you should also understand how one metric relates to another so you can identify optimisation opportunities to drive more conversions and profit.

The core metric stack

In the Google Ads UI, you can find general advertising metrics to help you evaluate campaign performance. Here is a breakdown of some of the most popular metrics across each stage of the user funnel:

Attention Stage

  • Impressions: Whenever your ad is displayed to a user on the search engine results page – whether it’s shown for a split second or longer – it counts as an ad impression.
  • Impression Share (IS): The percentage of times your ads were shown versus the total number of times they were eligible to show.
  • Lost IS (Budget): The percentage of impression share lost because your campaign budget is too low. In this scenario, your campaign budget is being used up too early in the day, which may require additional funding. However, it is always recommended to check campaign performance and profitability before increasing budgets.
  • Lost IS (Rank): The percentage of impression share lost because your Ad Rank is too low (meaning your bid or Quality Score is insufficient). A high percentage here means your ads aren’t competitive enough and need optimising.

Engagement Stage

  • Clicks: The total number of times users actually clicked on your ads.
  • Click-Through Rate (CTR): The ratio of clicks to impressions, expressed as a percentage. A click-through rate is calculated whenever a user clicks on your ad after seeing it.
  • Average CPC: The average amount you pay for every click on an ad.
  • Cost: Your total ad spend within the selected timeframe.
  • Quality Score (QS): A rating from 1 to 10 applied to each keyword in your campaigns. This metric serves as a diagnostic tool that looks at expected CTR, landing page experience, and ad relevance, rating each as either below average, average, or above average. A better overall score contributes to more efficient CPCs and better ad positions.

Action Stage

  • Conversions: A conversion happens when a user completes a predefined action on your website (e.g. a purchase, sign-up, or quote request). You can define what counts as a conversion for your business when setting up your account, or in the conversion goals section if an account is already live.
  • Conversion Rate (CVR): The percentage of ad clicks that resulted in a conversion.
  • Cost Per Conversion (CPA / Cost Per Acquisition): The cost associated with turning a click into a conversion. For example, if you run a lead generation business, this metric tells you the cost of acquiring a lead.

Bottom line

  • Conversion Value: The monetary value associated with a conversion. Revenue is a common example of what conversion value could be.
  • Return On Ad Spend (ROAS): Calculated as total conversion value divided by total cost. This is a key efficiency metric that helps businesses understand how much revenue is generated for every pound spent on ads.

The Relationship Matrix: How metrics talk to each other

The metrics above are just a snapshot of the standalone options available within Google Ads. However, as previously touched upon, there are many more metrics available in the platform, along with the option to create even more by creating custom columns.

To make the most of this data, you need to understand the relationships between metrics and what different combination of metrics can tell you about overall campaign performance:

  • CTR ←→ CVR: The ideal situation is to see both metrics increase. However, if you have a high CTR but a low CVR, it could be a sign that your ads are too clickbaity or that the offering on your landing page isn’t what the user expected to see. Conversely, a low CTR paired with a high CVR signals an opportunity to refine your ad assets so they appeal to more users and drive more clicks.
  • CTR ←→ Clicks ←→ Spend: Starting with ad impressions (how often your ad shows in the SERPs), if you can improve your ad messaging to generate a higher CTR, it will lead to more clicks, which in turn will impact your total spend.
  • Max Bid ←→ avg. CPC ←→ Impression Share (IS): One way to get more impressions and eyes on your ads is to reduce your Lost IS (Rank). You can achieve this by increasing your max bid (or, on modern Smart Bidding campaigns, adjusting your target CPA or target ROAS). Just be cautious when optimising for higher bids, as your average CPCs can climb quickly if pushed too aggressively, leading to fewer overall clicks on budget-constrained campaigns.
  • CPC ←→ CPA: Assuming landing page conversion rates remain static, optimising your ads to lower your average CPCs, whether through improving Quality Scores or lowering max bids, will produce a direct, proportional improvement in your CPA.
  • CVR ←→ CPA: In a competitive SERP with multiple advertisers pushing hard, you may find your average CPCs increasing. To combat this, you can focus on landing page optimisations to improve CVR. This creates a positive domino effect that helps lower your overall CPA.
  • Conversion Volume ←→ Smart Bidding Strategies: With the prominence of automated bidding today, the more conversion data you feed Google, the better. Google’s algorithm requires high volumes of data inputs for its machine learning models to accurately optimise bid strategies like tROAS or tCPA.

Metric Impact Matrix

The blind spots: Vanity Metrics vs. Value Metrics

Working in Paid Search means dealing with data all day, every day. However, having access to so much data can make it easy to fall into common traps:

  • Vanity vs. Value Metrics: When you see a metric like clicks increase, it’s easy to think, “Great! We’re getting more traffic!” While it’s true you are getting more sessions on your landing page, if those clicks don’t convert, it just leads to wasted spend.
  • CPC Isolation: When reviewing average CPCs, don’t simply chase after the cheapest clicks to get more volume. Cheaper traffic often converts poorly on-site, leading to lower conversion rates and an inefficient return on ad spend.
  • Chasing 100% Impression Share: Reaching 100% impression share means capturing maximum ad exposure. However, a major pitfall is pushing for this without monitoring its impact on performance metrics like CPA or ROAS. Increasing impression share is only valuable if the additional traffic contributes to revenue and profit (unless you are running a campaign purely for brand awareness).
  • Attribution Realities: With Data-Driven Attribution (DDA) enabled, Google looks at all of the converting and non-converting touchpoints and uses machine learning to fairly distribute credit to the interactions that contributed most. Instead of giving 100% of the credit to the last click, DDA spreads value across the entire customer journey. This helps Google assign proper credit to the campaigns, ad groups, ads, and keywords that were actually most impactful, allowing you to optimise performance far more effectively.

Turning metrics into performance

Here are 3 common situations you might encounter when running campaigns in platforms like Google Ads, along with action steps to resolve them:

Situation 1: High Clicks + Low Conversions

  • Ads: Check that your ad copy matches the messaging on your landing page. Disconnects occur when users land on a page that doesn’t align with what the ad promised.
  • Negative Keywords: Review your Search Terms Report. Your ads may be showing for irrelevant search queries, causing users to click through without converting. Add these irrelevant terms as negative keywords to preserve budget and protect your conversion rate.
  • Landing Page: Review your Quality Score sub-metrics, specifically Landing Page Experience. This provides clear insight into whether your landing page is relevant to search intent and whether it offers a frictionless user experience.

Situation 2: Low Impression Share + High ROAS

Having a low impression share means there is room to expand your reach. If you have campaigns that are profitable but losing impression share, look for ways to scale them. This could be as simple as adjusting targets on automated bidding strategies or increasing daily budgets if campaigns are budget-limited. You should also look for optimisation opportunities to improve Quality Scores across the board.

Situation 3: Surging CPCs

If your average CPCs are increasing, a few factors could be at play. First, new competitors may have entered your auctions, or existing competitors may be bidding more aggressively. Second, your Quality Scores may be declining, signaling a drop in ad or keyword relevance. To combat rising costs, make sure your ads closely align with user intent and that your landing pages are operating at peak efficiency.

Final thoughts

To wrap up: Google Ads provides a wealth of default metrics to help advertisers evaluate campaign performance, alongside the flexibility to create custom columns tailored to specific business goals. Make sure you’re tracking metrics that are actually meaningful for you and your business and not just standard vanity metrics.

Finally, remember that when troubleshooting or optimising PPC campaigns, looking at metrics in isolation is rarely beneficial. Always evaluate the relationship and how different metrics influence one another, to get a complete and accurate picture of true performance.

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