Google Ads IntegrationYour Google Ads spend is visible. What it actually drives is not - until now.
Google Ads tells you CPC, CTR, and conversion counts. KPI Tree connects those metrics into a causal tree that traces how paid search spend flows through your acquisition funnel - from impressions to clicks, clicks to leads, leads to pipeline, and pipeline to revenue. Connect via MCP to pull Google Ads data directly, point KPI Tree at your existing data warehouse where Google Ads data already lands, or let our Professional Services team build the AI foundations for you. KPI Tree maps your data into metric trees with ownership, statistical correlations, and action tracking. Stop optimising bids in isolation. Start understanding how paid acquisition actually drives your business.
From connection to paid-search accountability in under an hour
KPI Tree offers three ways to connect your Google Ads data: pull it directly via MCP with no warehouse needed, connect your existing data warehouse where Google Ads data already lands, or let our Professional Services team 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).
Connect your Google Ads data
Three ways to get started, depending on your stack.
Pull metrics from Google Ads directly through the Model Context Protocol.
Connect your existing warehouse where Google Ads data already lands.
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.
Map metrics from your Google Ads data
Define metrics from your Google Ads tables - cost per click, click-through rate, cost per acquisition, ROAS, impression share, quality score, conversion rate by campaign, and revenue attributed to paid search. Use SQL, your dbt semantic layer, or natural language with Cortex Analyst.
Build metric trees and assign ownership
Arrange paid acquisition metrics into causal trees. Link CPC and CTR to cost per lead. Connect cost per lead to pipeline value. Map pipeline to closed-won revenue and ROAS. Assign RACI owners - your paid search specialist owns keyword-level metrics, your demand gen lead owns campaign-level CAC, your VP Marketing owns blended ROAS.
Paid search metrics that connect to revenue, not just conversions
Google Ads gives you granular campaign data. KPI Tree adds the layer that connects click-level metrics to the revenue outcomes your leadership team actually cares about.
Causal trees from clicks to revenue
Map how impressions drive clicks, clicks drive leads, leads drive pipeline, and pipeline drives revenue. When ROAS drops, trace it through the tree - is it a CPC increase, a CTR decline, a landing page conversion issue, or a sales cycle problem? The tree shows you where the breakdown is, not just that it happened.
Cross-channel attribution in a single tree
Google Ads does not operate in isolation. Build metric trees that include Google Ads alongside organic search from Google Analytics, email from Customer.io or Klaviyo, and product metrics from PostHog. KPI Tree runs correlations across all channels to show which acquisition paths actually drive long-term value - not just last-click conversions.
Campaign-level ownership and accountability
Assign RACI ownership at the metric level. Your paid search manager owns CPC and quality score. Your demand gen lead owns cost per MQL. Your growth director owns blended CAC. When any metric moves beyond its expected range, the owner is notified with statistical context - not a raw number in a shared Slack channel.
Trace paid acquisition spend all the way to revenue.
Google Ads reporting stops at conversions. Your CRM starts at leads. KPI Tree connects both into a single causal tree that traces how every pound of ad spend flows through your funnel. When ROAS declines, you do not need to cross-reference Google Ads, your CRM, and a spreadsheet - the tree shows you whether it is a cost problem (CPC up, impression share down), a conversion problem (landing page, ad relevance), or a sales problem (pipeline velocity, close rates). One view, end to end.
- Causal trees linking ad spend to clicks, leads, pipeline, and revenue
- Trace ROAS changes to the specific funnel stage causing the drop
- Combine Google Ads data with CRM data in a unified tree
- Period-over-period comparisons with statistical significance
Correlations that reveal which campaigns drive long-term value.
Google Ads optimises for conversions within its own ecosystem. But not all conversions are equal - some campaigns drive high-LTV customers, others drive churn-prone signups. KPI Tree runs statistical analysis across your full acquisition funnel, correlating Google Ads campaign metrics with downstream retention, expansion, and lifetime value data from your warehouse. Discover which keyword themes drive customers who stay, and which ones drive customers who cancel within 90 days.
- Pearson correlations between campaign metrics and customer LTV
- Granger causality testing across paid and organic channels
- Identify keyword themes correlated with high-retention customers
- Partial correlations controlling for seasonality and market factors
Every metric in your paid funnel has a name next to it.
Paid acquisition involves specialists (keyword bidding, ad copy), generalists (demand gen strategy), and leadership (budget allocation). KPI Tree assigns RACI ownership at the metric level so the right person is accountable for the right number. When quality score drops on a high-spend campaign, your paid search specialist is notified. When blended CAC exceeds target, your VP Marketing sees it. Actions are tracked against the metric they target and verified for impact after the fact.
- RACI ownership from keyword-level metrics to blended CAC
- Push notifications via Slack, email, WhatsApp, or SMS
- Action tracking tied to specific metric movements
- Impact verification closes the loop between action and outcome
All your paid search data, analysed off-warehouse.
KPI Tree syncs Google Ads metrics from your warehouse on a configurable schedule. All downstream analytics - correlations, regressions, outlier detection, period comparisons - run in KPI Tree's engine, not against your warehouse. Your finance team can check ROAS, your paid search team can monitor CPCs, and your leadership can review blended CAC - all without firing additional warehouse queries.
- One scheduled query per metric, regardless of how many people check it
- All analytics computation runs off-warehouse
- Supports BigQuery, Snowflake, and other major warehouses
- Works alongside your existing dbt semantic layer if you have one
How KPI Tree uses Google Ads data differently
Google Ads has excellent native reporting for campaign optimisation. BI tools put that data in dashboards. KPI Tree connects paid acquisition metrics to downstream business outcomes with causation, ownership, and accountability.
From campaign dashboards to full-funnel causation
Google Ads reports show campaign performance in isolation. KPI Tree connects those metrics into a causal tree that traces spend through clicks, leads, pipeline, and revenue - crossing the boundary between marketing data and business outcomes that no single tool covers.
Cross-channel statistical analysis
Most Google Ads tools optimise within the Google ecosystem. KPI Tree correlates paid search metrics with organic, email, product, and revenue data from across your stack - showing you which channels actually complement each other and which are cannibalising conversions.
Budget accountability, not just budget visibility
Dashboards show you what you spent. KPI Tree assigns ownership to every metric in your paid funnel and tracks actions against specific movements. Your team does not just see that CAC increased - they see who is investigating it and what they are doing about it.
Metrics you can track
27 Google Ads metrics ready to add to your metric trees.
Ad Copy Testing Analysis
Paid AdvertisingMetric Definition
Ad copy testing analysis evaluates the performance differences between ad creative variants in Google Ads campaigns. It measures how headline, description, and call-to-action variations affect click-through rates, conversion rates, and cost efficiency to identify the most effective messaging for each audience.
Ad Frequency Analysis
Paid AdvertisingMetric Definition
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.
Audience Segmentation Analysis
Paid AdvertisingMetric 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.
Average Position
Paid AdvertisingMetric Definition
Average position indicates where your Google Ads typically appear on the search results page relative to other ads. While Google deprecated the exact average position metric, top impression share and absolute top impression share serve as modern proxies for ad placement visibility.
Bid Strategy Performance Analysis
Paid AdvertisingMetric Definition
Bid strategy performance analysis evaluates the effectiveness of different Google Ads bidding approaches - including manual CPC, target CPA, target ROAS, maximise conversions, and maximise conversion value. It compares how each strategy performs on cost efficiency, conversion volume, and return on ad spend.
Budget Allocation Analysis
Paid AdvertisingMetric Definition
Budget allocation analysis evaluates how Google Ads spend is distributed across campaigns, ad groups, and audience segments, and how that distribution relates to conversion volume and return on ad spend. It identifies over-invested and under-invested areas to optimise overall portfolio performance.
Campaign Attribution Analysis
Paid AdvertisingMetric Definition
Campaign attribution analysis determines the contribution of individual Google Ads campaigns to conversions and revenue across multi-touch customer journeys. It evaluates how different attribution models - last-click, first-click, data-driven, and time-decay - change the perceived value of each campaign.
Click-Through Rate
Paid AdvertisingMetric 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.
Competitive Analysis
Paid AdvertisingMetric Definition
Competitive analysis examines Google Ads auction insights data - including overlap rate, outranking share, and impression share relative to competitors. It provides visibility into how your paid search presence compares to competitors within the same auctions.
Conversion Rate
Paid AdvertisingMetric 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.
Cost per Acquisition
Paid AdvertisingMetric Definition
Cost per Acquisition = Total Ad Spend / Total Conversions
Cost per acquisition measures the average amount spent on Google Ads to acquire one conversion. It combines click costs and conversion rates into a single efficiency metric that represents the true cost of each customer action generated through paid search.
Cost per Click
Paid AdvertisingMetric 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.
Cross-Campaign Performance Analysis
Paid AdvertisingMetric Definition
Cross-campaign performance analysis compares key metrics - conversion rate, CPA, ROAS, and revenue contribution - across all campaigns in a Google Ads account. It identifies top-performing and underperforming campaigns to guide budget allocation and strategic investment decisions.
Customer Lifetime Value (Ads)
Paid AdvertisingMetric Definition
LTV (Ads) = Average Revenue per Customer x Average Customer Lifespan
Customer lifetime value from ads measures the total revenue generated over the full customer relationship for customers acquired through Google Ads. It connects upfront acquisition costs to long-term value, providing a complete picture of paid search ROI beyond initial conversion.
Dayparting Analysis
Paid AdvertisingMetric Definition
Dayparting analysis examines how Google Ads performance varies by hour of day and day of week. It identifies time windows where conversion rates, cost efficiency, and return on ad spend are highest or lowest to inform ad scheduling and bid adjustment strategies.
Device Performance Analysis
Paid AdvertisingMetric Definition
Device performance analysis compares Google Ads metrics across desktop, mobile, and tablet devices. It examines how click-through rates, conversion rates, cost per acquisition, and return on ad spend differ by device to inform bid adjustments and landing page strategies.
Extension Performance Analysis
Paid AdvertisingMetric Definition
Extension performance analysis evaluates the impact of Google Ads extensions - including sitelinks, callouts, structured snippets, call extensions, and price extensions - on click-through rate, conversion rate, and overall campaign performance. It identifies which extensions contribute to better outcomes and which add no measurable value.
Geographic Performance Analysis
Paid AdvertisingMetric Definition
Geographic performance analysis examines how Google Ads metrics vary across locations - countries, regions, cities, and postal codes. It identifies areas of strong and weak performance to inform location targeting, bid adjustments, and localised messaging strategies.
Impression Share Lost to Budget
Paid AdvertisingMetric Definition
IS Lost (Budget) = (Impressions Lost to Budget / Total Eligible Impressions) x 100
Impression share lost to budget measures the percentage of eligible impressions your Google Ads did not receive because your daily or campaign budget was exhausted. It quantifies the opportunity cost of budget constraints and indicates where additional investment could capture more conversions.
Impression Share
Paid AdvertisingMetric 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.
Keyword Performance Analysis
Paid AdvertisingMetric Definition
Keyword performance analysis evaluates how individual keywords and keyword themes perform across Google Ads campaigns. It examines click-through rates, conversion rates, cost per acquisition, and revenue attribution at the keyword level to identify your most and least profitable search terms.
Landing Page Performance Analysis
Paid AdvertisingMetric Definition
Landing page performance analysis evaluates how different landing pages perform in converting Google Ads traffic. It examines conversion rates, bounce rates, time on page, and quality score impact per landing page to identify which pages effectively convert paid traffic and which create friction.
Negative Keyword Analysis
Paid AdvertisingMetric Definition
Negative keyword analysis evaluates the effectiveness of your Google Ads negative keyword strategy in preventing ads from showing for irrelevant search queries. It measures wasted spend avoided, impression quality improvement, and the impact on overall conversion rates from excluding non-converting search terms.
Quality Score
Paid AdvertisingMetric Definition
Quality score is Google Ads' rating of the overall quality and relevance of your keywords, ads, and landing pages. Scored from 1 to 10, it combines expected click-through rate, ad relevance, and landing page experience to influence your ad rank and actual cost per click.
Return on Ad Spend
Paid AdvertisingMetric Definition
ROAS = Revenue Attributed to Ads / Total Ad Spend
Return on ad spend measures the revenue generated for every pound spent on Google Ads. It provides a direct ratio of revenue to cost that quantifies the financial return of your paid search investment, making it the primary efficiency metric for revenue-focused campaigns.
Search Term Analysis
Paid AdvertisingMetric Definition
Search term analysis examines the actual search queries that trigger your Google Ads, comparing them against your targeted keywords. It identifies high-performing search terms worth promoting, irrelevant queries worth excluding, and emerging search patterns that reveal new opportunities.
Seasonal Trend Analysis
Paid AdvertisingMetric Definition
Seasonal trend analysis examines how Google Ads performance metrics fluctuate across seasons, holidays, and recurring events. It identifies predictable patterns in search volume, CPC, conversion rates, and ROAS to inform proactive budget planning and bid strategy adjustments.
Related integrations
Other data sources that work with KPI Tree.
Common questions
- Yes. Single-account Google Ads advertisers usually start with MCP, which queries campaigns, ad groups, keywords, and conversion actions directly and gets you cost-per-click, CTR, ROAS, and impression share trees the same afternoon. Large advertisers running an MCC (My Client Center) with dozens of child accounts almost always already replicate to Snowflake, BigQuery, or Redshift via Fivetran, Supermetrics, or the Google Ads Transfer Service, and KPI Tree reads those tables so cross-account roll-ups, blended ROAS, and portfolio-level spend analysis all work against the governed copy your finance team trusts. Agencies and performance marketing teams that want the MCC-aware warehouse built for them engage our professional services team, which delivers the pipeline plus the dbt semantic layer for cross-campaign attribution.
- Any metric you can derive from your Google Ads warehouse tables - impressions, clicks, CPC, CTR, cost per conversion, conversion rate, ROAS, impression share, quality score, cost per lead, cost per MQL, and custom revenue attribution metrics. If it is in your warehouse, you can build a metric from it.
- Yes - that is the core value. Build a metric tree where Google Ads paid acquisition feeds into the same funnel as organic traffic from Google Analytics, email engagement from Klaviyo or Customer.io, and product activation from PostHog. KPI Tree runs correlations across all of them.
- No. Google Ads reporting is excellent for in-platform optimisation - bid management, ad copy testing, keyword research. KPI Tree adds the layer above: connecting paid search metrics to downstream business outcomes (pipeline, revenue, LTV) with causal trees, ownership, and statistical analysis.
- If you use MCP or already have Google Ads data in a warehouse KPI Tree supports, setup takes under an hour. Connect via MCP or point KPI Tree at your warehouse, define metrics from your Google Ads data, and start building trees. If you need a warehouse built from scratch, our Professional Services team handles that for you.
- KPI Tree queries your warehouse and processes aggregated metric values in its own engine for analytics. Raw Google Ads data - keywords, ad copy, audience targeting - stays in your warehouse. All warehouse security remains fully enforced.
- You define the SQL behind each metric, so you can track at whatever granularity your warehouse tables support - keyword, ad group, campaign, account, or any custom dimension. Most teams build a hierarchy: blended metrics at the top, campaign breakdowns in the middle, keyword-level detail at the bottom.
- You have two options. Use MCP to pull Google Ads data directly into KPI Tree - no warehouse needed, ideal for getting started quickly. Or engage our Professional Services team, who will build a production-grade data foundation (Snowflake/BigQuery, Fivetran, and dbt) tailored to your stack, giving you richer historical data and the ability to join Google Ads metrics with CRM and revenue data.
Related guides
Deep dives into the frameworks and metrics that work with Google Ads.
Your Google Ads data tells you what you spent. KPI Tree tells you what it drove.
Connect your warehouse to KPI Tree and turn Google Ads campaign metrics into causal trees with ownership, statistical analysis, and accountability. Trace every pound of ad spend to the business outcome it influences.
