KPI Tree

Google Ads Metric

Paid Advertising

Ad frequency analysis examines how often individual users see your Google Ads and the relationship between impression frequency and engagement, conversion, and cost metrics. It identifies the optimal exposure level before diminishing returns or ad fatigue set in.

Google AdsPaid Advertising

Ad Frequency Analysis

Ad frequency analysis examines how often individual users see your Google Ads and the relationship between impression frequency and engagement, conversion, and cost metrics. It identifies the optimal exposure level before diminishing returns or ad fatigue set in.

Why ad frequency analysis matters for Google Ads users

Showing ads too infrequently fails to build awareness. Showing them too often wastes budget and irritates potential customers. The optimal frequency varies by campaign type, audience, and funnel stage. Most teams set frequency caps based on intuition rather than data.

Tracking frequency metrics in your metric tree reveals the causal relationship between impression volume and conversion outcomes. Statistical correlations show where additional impressions drive conversions and where they produce diminishing returns.

Understand and act on ad frequency analysis with KPI Tree

KPI Tree connects impression frequency data from your warehouse and maps it alongside CTR, conversion rate, and cost metrics. Identify the frequency threshold where performance peaks.

Assign RACI ownership to your display and video campaign manager. Set alerts when frequency exceeds optimal levels and track adjustments to frequency caps and audience targeting.

Get started with your Google Ads data

Query using MCP
MCP

Pull metrics from Google Ads directly through the Model Context Protocol.

Data Warehouse
SnowflakeBigQueryDatabricksRedshift

Connect your existing warehouse where Google Ads data already lands.

Professional Services
FivetranSnowflakedbt

Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.

Related Google Ads metrics

Impression Share

Paid Advertising

Metric Definition

Impression Share = (Impressions Received / Total Eligible Impressions) x 100

Impression share measures the percentage of eligible impressions your Google Ads actually received compared to the total impressions available for your targeted keywords and audiences. It indicates your market coverage and competitive presence in the paid search landscape.

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Click-Through Rate

Paid Advertising

Metric Definition

Click-Through Rate = (Clicks / Impressions) x 100

Click-through rate measures the percentage of Google Ads impressions that result in a click. It indicates how relevant and compelling your ads are to the audience seeing them, serving as a primary signal of ad-audience alignment and creative effectiveness.

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Conversion Rate

Paid Advertising

Metric Definition

Conversion Rate = (Conversions / Clicks) x 100

Conversion rate measures the percentage of Google Ads clicks that result in a defined conversion action - such as a purchase, signup, form submission, or phone call. It quantifies how effectively your ads and landing pages turn paid traffic into measurable business outcomes.

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Cost per Click

Paid Advertising

Metric Definition

Cost per Click = Total Ad Spend / Total Clicks

Cost per click measures the average amount paid for each click on a Google Ads advertisement. It reflects the competitive intensity of the keywords and audiences you target, the quality of your ads, and the effectiveness of your bidding strategy.

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Audience Segmentation Analysis

Paid Advertising

Metric Definition

Audience segmentation analysis compares performance metrics across different Google Ads audience segments - including in-market, affinity, custom, remarketing, and customer match audiences. It evaluates which segments deliver the best conversion rates, cost efficiency, and return on ad spend.

View metric

Empower your team to understand and act on Google Ads data

Map what drives your metrics, measure progress at any grain, prove what works statistically, and deliver personalised action plans to every team member.

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