How to Build a Cross-Platform Paid Media Dashboard in Looker Studio

You manage ads across Google, Meta, and LinkedIn. Each platform has its own dashboard, its own metrics definitions, its own attribution model, and its own version of the truth. Every Monday morning, you open three tabs, export three CSVs, and spend two hours building a report that combines them into something your CMO can understand. By Thursday, someone asks a question the report does not cover, and you start the process over. This is the wrong way to report on paid media. The right way is a single cross-platform dashboard in Looker Studio that pulls data automatically, normalizes metrics, and answers every question before it gets asked. This guide shows you how to build one from scratch.

Looker Studio is the right tool for this because it is free, connects to every major ad platform natively or through connectors, and produces dashboards that auto-refresh and can be shared via URL. No licenses, no installs, no engineering tickets. You can build a production-quality cross-platform dashboard in a single afternoon and never export a CSV again.

Why You Need a Cross-Platform Dashboard

Platform-native dashboards are designed to make each platform look good. Google Ads shows you every conversion Google touched. Meta shows you every conversion Meta touched. LinkedIn shows you every conversion LinkedIn touched. When you add up all the conversions from all three platforms, the total exceeds your actual conversions by 30-80% because each platform is taking credit for shared conversions. This double-counting makes it impossible to understand your true cost per acquisition or your true ROAS from platform-native reporting.

A cross-platform dashboard solves this by providing a single source of truth. Instead of asking "what did Google report?" and "what did Meta report?" you ask "how many total conversions did we generate, how much did we spend, and what was our blended CPA?" The blended view reveals the real economics of your paid media program: total investment in, total conversions out, total revenue generated.

The dashboard also saves time. A manual reporting process typically takes 2-4 hours per week: exporting data, combining spreadsheets, updating formulas, formatting charts, and distributing the report. Over a year, that is 100-200 hours spent on reporting mechanics rather than analysis and optimization. A Looker Studio dashboard reduces this to zero recurring effort. You spend 4-6 hours building it once, and it runs forever.

Most importantly, the dashboard changes how your team thinks about paid media. When everyone looks at the same numbers, discussions shift from "my platform is performing well" to "our program is performing well." Platform managers stop optimizing their individual channel in isolation and start optimizing for portfolio performance. This shift in perspective is worth more than any single metric improvement.

Data Sources and Connectors

The foundation of your dashboard is the data connections. Looker Studio needs to pull data from each ad platform and present it in a unified format. There are three approaches to connecting data, each with different tradeoffs.

Option 1: Native Connectors (Free, Limited)

Looker Studio has a native Google Ads connector that pulls data directly from your Google Ads account with zero configuration. For Google Ads reporting, this is the best option because it is free, fast, and provides the most granular data available. However, Looker Studio does not have native connectors for Meta Ads or LinkedIn Ads. For a Google-only dashboard, native connectors are sufficient. For cross-platform, you need a third-party connector.

Option 2: Supermetrics ($39-119/month)

Supermetrics is the most popular third-party connector for Looker Studio. It provides connectors for Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads, and 70+ other data sources. Data is pulled into Google Sheets, which Looker Studio then reads. The workflow is: Platform API, Supermetrics, Google Sheets, Looker Studio. Setup takes about 30 minutes per data source. The monthly cost is justified if you run ads on 2+ platforms and the time saved exceeds the subscription cost (which it almost certainly does at 2-4 hours per week of manual reporting).

Option 3: Funnel.io ($399+/month)

Funnel.io is an enterprise-grade data aggregation tool that pulls from 500+ data sources, normalizes metrics automatically, and feeds clean data to Looker Studio (or any BI tool). It is expensive but eliminates the Google Sheets middleman and handles data normalization that you would otherwise do manually. For teams spending $50,000+/month on ads across 3+ platforms, Funnel.io pays for itself in time savings and data accuracy.

Metric Normalization: Making Platforms Comparable

Before you can build a cross-platform dashboard, you need to normalize metrics so they mean the same thing across all platforms. This is harder than it sounds because each platform defines metrics slightly differently.

Impressions

Google Ads counts an impression when an ad appears on screen. Meta counts an impression when an ad is delivered to a person's feed (whether or not they scroll to it). LinkedIn counts an impression when at least 50% of the ad is visible for at least 300 milliseconds. These differences mean that 1,000 Google impressions, 1,000 Meta impressions, and 1,000 LinkedIn impressions are not equivalent. For your dashboard, note this discrepancy but do not try to normalize impressions. Instead, use CPM (cost per 1,000 impressions) as a relative efficiency metric within each platform, not across platforms.

Clicks

Google Ads reports "clicks" as clicks on the ad that lead to the website. Meta reports "link clicks" (clicks to external URLs) and "all clicks" (which includes likes, comments, and shares). LinkedIn reports "clicks" as any click on the ad content. For your dashboard, use Google's "clicks," Meta's "link clicks," and LinkedIn's "clicks to landing page" to create a comparable metric across platforms. Label this metric "Landing Page Clicks" to distinguish it from engagement clicks.

Conversions

This is the most critical normalization. Each platform counts conversions differently based on its attribution window. Google Ads default is 30-day click, 1-day view. Meta default is 7-day click, 1-day view. LinkedIn default is 30-day click, 7-day view. To make conversions comparable, either standardize the attribution windows across all platforms (set all to 7-day click, 1-day view) or use a platform-independent conversion source like your CRM or analytics tool.

The best approach is to use UTM-tracked conversions from your analytics platform as the single source of truth. Every ad on every platform should have UTM parameters (source, medium, campaign, content, term). Your analytics tool counts the conversion once, attributes it to the UTM source, and eliminates double-counting. Your Looker Studio dashboard then pulls conversion data from Google Analytics or your CRM, not from the ad platforms themselves.

Cost

Spend data is the easiest metric to normalize because it means the same thing everywhere: how much money left your account. Pull spend from each platform's native reporting. The only nuance is currency conversion for international campaigns and tax treatment (some platforms report pre-tax spend, others post-tax). Standardize on pre-tax spend in your local currency.

Dashboard Architecture: The Four Pages

The best paid media dashboards follow a pyramid structure: start with the highest-level summary and allow users to drill down into progressively more granular data. Each page serves a different audience and answers different questions.

Building Page 1: The Executive Summary

Open Looker Studio (lookerstudio.google.com), create a new report, and add your data sources. If you are using the Supermetrics-Google Sheets approach, add the summary Google Sheet as your data source. If you are using native connectors, add each platform connector individually.

Start with four scorecards across the top of the page: Total Spend, Total Conversions, Blended CPA, and Blended ROAS. Each scorecard should show the current period value and the comparison to the previous period. In Looker Studio, add a scorecard, select the metric, and enable the "Comparison date range" option to automatically calculate period-over-period change. Use conditional formatting to color the change green (improvement) or red (decline).

Below the scorecards, add two charts side by side. On the left, a donut chart showing spend distribution by platform. This immediately answers "where is the money going?" On the right, a line chart showing blended CPA over the last 12 weeks. This answers "is our efficiency improving or declining?" The 12-week window is long enough to show trends but short enough to reflect current conditions.

At the bottom of the page, add a table with one row per platform showing the key metrics: spend, conversions, CPA, and ROAS. This provides the numerical detail behind the donut chart and line chart. Keep this table simple: 4-5 columns maximum. Executives will scan it in 10 seconds. If they need more detail, they go to Page 2.

Add a date range control at the top right of the page. Set the default to "Last 28 days" but allow users to change it. Also add a "Compare to" control that defaults to "Previous period." These two controls let users answer ad-hoc questions without the dashboard builder needing to anticipate every question.

Building Page 2: Platform Breakdown

Page 2 is for the paid media team. It answers "how is each platform performing relative to the others and relative to its own historical trend?" The main element is a comparison table with platforms as rows and metrics as columns.

Build the table with these columns: Platform, Spend, Impressions, Clicks, CTR, CPC, Conversions, CPA, ROAS. Use conditional formatting (bar charts within cells or color scales) to make the best and worst performers immediately visible. In Looker Studio, you can add bar-chart visualization within table cells by clicking the column settings and enabling "Data bars."

Below the table, add three time-series charts: CPA by platform over time, ROAS by platform over time, and spend by platform over time. Use a line chart with one line per platform. Color-code the lines consistently with the table (Google blue, Meta blue-purple, LinkedIn blue-teal). These trend charts reveal trajectory, which is more important than point-in-time values. A platform with a $60 CPA that has been declining for 6 weeks is healthier than a platform with a $40 CPA that has been rising for 6 weeks.

Add a "funnel stage" filter to this page: Prospecting, Retargeting, Branded. When the head of paid media selects "Prospecting," all metrics filter to show only prospecting campaigns across all platforms. This enables apples-to-apples comparison: how does Meta prospecting compare to LinkedIn prospecting? Without this filter, the comparison is misleading because one platform might be dominated by retargeting (which naturally has lower CPA) while another is dominated by prospecting (which naturally has higher CPA).

Building Page 3: Campaign Drill-Down

Page 3 is the working page for campaign managers. It shows every campaign across all platforms in a single sortable, filterable table. This is where the day-to-day optimization decisions are made.

Add three filter controls at the top: Platform (Google, Meta, LinkedIn, All), Campaign Type (Prospecting, Retargeting, Branded, All), and Date Range (default to last 30 days). These filters let campaign managers quickly narrow to their area of responsibility.

The main table should include these columns: Platform, Campaign Name, Status (active/paused), Spend, Impressions, Clicks, CTR, CPC, Conversions, Conversion Rate, CPA, Revenue (if available), and ROAS. Enable sorting on all columns so managers can quickly find the highest-spend campaigns, the worst-CPA campaigns, or the best-ROAS campaigns.

Below the table, add a scatter plot with CPA on the X-axis and conversion volume on the Y-axis. Each dot represents a campaign, color-coded by platform. This visualization instantly reveals the portfolio dynamics: campaigns in the upper-left quadrant (high volume, low CPA) are your stars. Campaigns in the lower-right quadrant (low volume, high CPA) are candidates for pausing or optimization. Campaigns in the upper-right (high volume, high CPA) are scaling problems. Campaigns in the lower-left (low volume, low CPA) are scaling opportunities.

Add a daily trend chart at the bottom showing spend and conversions by day for the selected campaigns. This catches daily anomalies: a sudden spend spike without a corresponding conversion increase indicates a problem (audience exhaustion, bot traffic, bidding error). A sudden conversion drop without a spend change indicates a tracking or landing page issue. These anomalies are invisible in weekly or monthly aggregates but obvious in daily charts.

Building Page 4: Creative Performance

Page 4 bridges the gap between the media team and the creative team. It answers "which ad creatives are performing and which are fatiguing?" This page is critical for maintaining creative velocity because it gives the creative team direct visibility into what works.

Build a table with these columns: Platform, Ad Name, Ad Format (image/video/carousel/text), Launch Date, Days Running, Impressions, CTR, Conversion Rate, CPA, and a "Status" column that flags creatives as "Scaling" (CPA below target), "Stable" (CPA at target), or "Fatiguing" (CPA above target and rising). The status column is a calculated field: compare the creative's CPA in the last 7 days to its CPA in the prior 7 days. If CPA increased by more than 20%, flag it as fatiguing.

Add a chart below the table showing the average CTR by ad format across all platforms. This reveals which formats perform best in aggregate: maybe video consistently outperforms static images, or maybe carousels outperform both. These format-level insights guide the creative team's production priorities.

If your data connector supports ad-level creative fields (headline, description, image URL), add a section that groups ads by creative theme or angle. This requires some manual tagging: add a column to your Google Sheet that categorizes each ad by its creative approach (pain-focused, outcome-focused, social proof, etc.). Then add a chart showing average performance by creative theme. This is the most valuable view on the page because it connects creative strategy to performance data.

Advanced Features: Calculated Fields and Blended Metrics

Looker Studio's calculated fields let you create custom metrics that do not exist in your raw data. These are essential for cross-platform reporting because the blended metrics you care about (blended CPA, blended ROAS, channel contribution) require arithmetic across data sources.

Blended CPA

Create a calculated field: Total Spend (sum across all platforms) / Total Conversions (from your analytics source, not from platform reporting). This gives you the true blended cost per acquisition that accounts for double-counting. If your platforms report 500 combined conversions but your analytics tool shows 350 unique conversions, your blended CPA is based on 350, not 500.

Channel Contribution Percentage

Create a calculated field: Platform Spend / Total Spend. Display this as a percentage in each platform's row on the comparison table. Add another field: Platform Conversions / Total Conversions. When a platform's spend share exceeds its conversion share, it is less efficient than the portfolio average. When its conversion share exceeds its spend share, it is more efficient. This simple ratio reveals cross-platform allocation opportunities at a glance.

Marginal CPA Trend

Create a calculated field that shows the CPA trend direction: (CPA this week - CPA last week) / CPA last week. Display this as a percentage with conditional formatting. Green for declining CPA (good), red for rising CPA (bad). This field is more actionable than the absolute CPA because it tells you where things are heading, not just where they are.

Budget Pacing

Create a calculated field: (Spend to Date / Days Elapsed) * Days in Month. This projects the end-of-month spend based on current pacing. Compare it to the monthly budget to flag over-pacing (you will exceed budget) or under-pacing (you will have unspent budget). Display this as a progress bar or scorecard with the projected spend vs. the budget target. Under-pacing by more than 10% signals a delivery problem. Over-pacing by more than 10% signals a bid or audience issue.

Automating Delivery and Alerts

A dashboard that people have to remember to open is a dashboard that gets ignored. Automate delivery so the right information reaches the right people at the right time without anyone needing to take action.

Scheduled Email Delivery

Looker Studio supports scheduled email delivery of report PDFs. Set up a Monday 8am delivery to your CMO and VP Marketing with the Executive Summary page. Set up a daily 9am delivery to your paid media team with the Campaign Drill-Down page. Each recipient gets the information they need at the cadence they need it. To set this up, click "Schedule email delivery" in the File menu, add recipients, set the frequency, and choose which pages to include.

Shared Links with View Access

For stakeholders who want to explore the dashboard interactively, share it as a view-only link. Click "Share" in the top right, generate a link, and set permissions to "Anyone with the link can view." Stakeholders can change date ranges, apply filters, and drill into campaigns without accidentally modifying the dashboard structure. If you need to restrict access, use Google account-based sharing instead of link sharing.

Threshold Alerts via Google Apps Script

Looker Studio does not have native alerting, but you can build alerts using Google Apps Script on the Google Sheets data source. Write a script that checks the sheet data every hour and sends a Slack message or email when a metric crosses a threshold. Common alerts: CPA exceeds target by more than 25%, daily spend exceeds daily budget by more than 15%, conversion rate drops below 50% of the 30-day average. These alerts catch problems in real-time rather than waiting for the weekly report.

Design Principles for Readable Dashboards

A dashboard that is technically correct but visually overwhelming is as useless as one with bad data. Follow these design principles to make your dashboard scannable and actionable.

Use a consistent color palette. Assign one color per platform and use it everywhere. Google blue (#4285F4), Meta blue (#1877F2), LinkedIn blue (#0A66C2). Use these colors for chart lines, table highlights, and pie chart segments. When a user sees the Google color, they instantly know which platform is being referenced without reading the label.

Limit each page to 3-5 visual elements. Every chart, table, and scorecard competes for attention. A page with 15 elements overwhelms the viewer and nothing gets read. A page with 4 elements gets scanned in 15 seconds and the key takeaway lands. If you need more elements, add another page.

Put the most important number in the biggest font. The first thing someone sees should be the first thing they need to know. On the Executive Summary, that is the blended CPA or the total conversions. Make it large, centered, and unmissable. Supporting details go in smaller text below or beside it.

Use whitespace liberally. Cramming elements together to fit everything on one page is counterproductive. Whitespace separates visual groups and creates reading flow. Leave at least 20px of padding between elements and 40px between logical sections. The dashboard should breathe.

Add text annotations for context. A chart showing CPA spiking 40% is alarming without context and harmless with it. Add a text box below the chart that says "CPA spike on 3/15 due to Meta account suspension resolved on 3/17." These annotations turn a data display into a narrative that stakeholders can understand without pinging the media team.

Common Mistakes and How to Fix Them

Mistake 1: Using Platform-Reported Conversions as Ground Truth

If your dashboard shows platform-reported conversions, your totals will exceed actual conversions due to double-counting. Fix this by using your analytics tool or CRM as the conversion source and attributing conversions to platforms via UTM parameters. The platform columns in your table should show platform-reported conversions as a reference, but the total row should use analytics-sourced conversions.

Mistake 2: Comparing Platforms on Unequal Footing

Google Search ads and Meta feed ads serve fundamentally different purposes. Comparing their CPAs directly is like comparing the cost of a sales call to the cost of a billboard. They serve different stages of the funnel. Add a funnel stage dimension to your data and compare platforms within the same stage: Google Search prospecting vs. LinkedIn prospecting, Google retargeting vs. Meta retargeting. These comparisons are actionable because the campaigns serve similar purposes.

Mistake 3: Building the Dashboard Before Defining the Questions

Many teams start building charts and tables before clarifying what questions the dashboard should answer. This produces dashboards full of data and empty of insight. Before opening Looker Studio, write down the 10 questions your stakeholders ask most frequently. Then design each page and chart to answer a specific question. If a chart does not answer a question, remove it. The best dashboards are opinionated: they surface the metrics that matter and hide the ones that do not.

Mistake 4: Never Updating the Dashboard

Your paid media strategy evolves. New campaigns launch. New platforms get added. KPIs change. A dashboard built six months ago may not reflect current priorities. Review the dashboard quarterly and ask: are these still the right metrics? Are there new questions the dashboard should answer? Are any pages never viewed (meaning they can be removed or replaced)? A living dashboard stays relevant. A static dashboard becomes a relic.

Template: The Complete Setup Checklist

Follow this checklist to build your dashboard from scratch in 4-6 hours. The order matters because later steps depend on earlier ones.

Hour 1: Data setup. Sign up for Supermetrics (or your preferred connector). Connect Google Ads, Meta Ads, and LinkedIn Ads to Google Sheets. Set up auto-refresh schedules (daily at 6am). Create the summary sheet with unified column names and calculated blended metrics.

Hour 2: Page 1 build. Create the Looker Studio report. Add your summary sheet as the data source. Build the Executive Summary page with 4 scorecards, a donut chart, a line chart, and a summary table. Add the date range control.

Hour 3: Page 2 build. Create the Platform Breakdown page. Build the comparison table with data bars. Add the three trend charts (CPA, ROAS, spend over time). Add the funnel stage filter.

Hour 4: Page 3 build. Create the Campaign Drill-Down page. Build the filterable campaign table. Add the scatter plot. Add the daily trend chart. Test all three filters.

Hour 5: Page 4 build. Create the Creative Performance page. Build the ad-level table with the fatigue status column. Add the format performance chart. Add creative theme grouping if your data supports it.

Hour 6: Polish and automate. Apply consistent colors, fonts, and layout across all pages. Test at 1920x1080 resolution. Set up scheduled email delivery. Share the link with stakeholders. Write a one-page "How to Use This Dashboard" guide and pin it to your team's Slack channel.

A cross-platform dashboard is not a reporting tool. It is a decision-making tool. The difference is that a reporting tool shows you what happened, while a decision-making tool shows you what to do next. When your dashboard surfaces that Meta's CPA is rising while LinkedIn's is falling, the decision is obvious: investigate Meta's audience saturation and consider shifting budget to LinkedIn. When the creative performance page shows that video ads are outperforming static by 2x, the decision is obvious: produce more video. The dashboard does not make decisions for you, but it makes the right decisions obvious. Build it once, automate it completely, and spend your time acting on insights instead of assembling spreadsheets.