How to Analyze Marketing Campaigns with Looker

You've launched your marketing campaign, poured budget into ads, and traffic is flowing. Now comes the hard part: proving it all worked. Analyzing your marketing campaign performance is essential for understanding what's driving results, what's falling flat, and how to optimize your budget for better returns. This guide will walk you through how to use Looker, a powerful business intelligence tool, to connect your data and build a clear view of your campaign's impact.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Before You Begin: Connecting Your Data Sources

The first step in any meaningful analysis is getting all your data in one place. Your campaign's story is likely spread across several platforms - Google Ads, Facebook Ads Manager, Google Analytics, your CRM like Salesforce, and your e-commerce platform like Shopify. Looker helps you centralize this information, but you need to connect these sources first.

Most organizations that use Looker have a data team that helps prepare and model the data. They connect to a centralized data warehouse (like BigQuery, Snowflake, or Redshift) where all your raw data from different platforms is collected. They then use Looker's modeling language, LookML, to define the relationships between your data, create standard metric definitions, and build reusable data models. This upfront work is what makes the self-service analysis we'll discuss below possible.

If you're a marketer, you might not be writing LookML yourself, but it's important to understand that this step happens in the background. It ensures that when you see a metric like "Revenue," everyone in the company is looking at the exact same number, calculated the exact same way.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Building a Campaign Performance Dashboard in Looker

With your data connected and modeled, you can start building reports. In Looker, the primary way you'll do this is by starting from an "Explore." An Explore is a curated starting point for a query, designed by your data team to expose a specific area of your business data, like "Marketing Spend" or "Website Sessions."

Step 1: Choose Your Key Performance Indicators (KPIs)

Before you jump into Looker, decide what you actually want to measure. A cluttered dashboard is an ignored dashboard. Focus on the metrics that directly relate to your campaign goals. Common marketing KPIs include:

• Impressions & Reach: How many people saw your ads?
• Clicks & Click-Through Rate (CTR): How many people engaged with your ads?
• Cost Per Click (CPC) / Cost Per Mille (CPM): How efficiently are you spending your budget?
• Conversions: How many users completed a desired action (e.g., made a purchase, filled out a form, signed up for a trial)?
• Cost Per Acquisition (CPA): How much does it cost to acquire one new customer?
• Return on Ad Spend (ROAS): How much revenue is generated for every dollar spent on advertising?
• Sessions & New Users: How much traffic did the campaign drive to your website (from Google Analytics)?

Step 2: Use an Explore to Select Dimensions and Measures

Once you are in a Looker Explore, you'll see a panel with available data fields, usually categorized into "Dimensions" and "Measures."

• Dimensions: These are the attributes you want to group your data by. Think of them as the "by what" in your question. For a campaign analysis, useful dimensions would be Campaign Name, Ad Set Name, Channel (e.g., Facebook, Google), Date, or Country.
• Measures: These are the quantifiable numbers you want to analyze. They are the actual metrics or KPIs, like Clicks, Spend, Conversions, or Total Revenue.

To build your analysis, you simply click on the dimensions and measures you want to see. For example, you might select the Campaign Name dimension and the Spend, Clicks, and Conversions measures. Looker will automatically generate a data table with the results.

Step 3: Add Filters for Granularity

Your initial query might pull in every campaign you've ever run. That's not very helpful. Use Filters to narrow down your results. The most common filter for campaign analysis is the date range. You can set the filter to "is in the last 30 days" or select a custom range that matches your campaign's flight dates. You can also filter by specific campaign names, channels, or any other dimension to focus your analysis.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Step 4: Visualize Your Data

A table of numbers is useful, but a chart is often easier to interpret. Looker gives you a wide range of visualization options. With your data table generated, you can select a chart type:

• Line Chart: Perfect for showing trends over time (e.g., daily conversions for a specific campaign).
• Bar Chart: Great for comparing performance across different campaigns or channels.
• Pie Chart: Useful for showing the composition of something (e.g., the percentage of spend by channel).
• Single Value: Excellent for displaying a single, important KPI like total ROAS or total conversions for the period.

After creating a visualization you like, you can save it as a "Look" (a saved report) or add it directly to a new or existing "Dashboard." A dashboard is simply a collection of these saved Looks, giving you a full overview of performance in one place.

Advanced Campaign Analysis Techniques

Once you've mastered the basics, you can start asking more sophisticated questions of your data in Looker.

1. Analyzing Cross-Channel Performance

The goal is to answer: "How are Facebook Ads and Google Ads performing relative to each other?" Looker can do this by using a unified data model that combines cost and performance data from different ad platforms.

In your Explore, you would select your primary performance metrics (like Spend and Conversions) and then add Channel or Source / Medium as a dimension. This allows you to create a single bar chart that compares the CPA or ROAS for each platform, helping you decide where to allocate your budget more effectively.

2. Calculating Return on Ad Spend (ROAS)

ROAS is a critical but often tricky metric to calculate because it requires linking ad spend data with revenue data. Your company's LookML model likely includes a pre-built measure for ROAS. If not, Looker allows users to create custom calculations on the fly without changing the underlying LookML.

You can create a custom field using a formula like:

${total_revenue} / ${total_spend}

Visualizing this by campaign name will instantly show you which of your efforts are successful and which are a drain on your budget.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

3. Funnel Analysis: From Ad Click to Conversion

Understanding where users drop off in the conversion process is key to optimization. You can build a funnel report in Looker by pulling together different data points that represent each step of your user journey. For example:

• Step 1: Ad Impressions (from ads data)
• Step 2: Ad Clicks (from ads data)
• Step 3: Website Sessions (from Google Analytics)
• Step 4: Added to Cart (from Shopify or other e-commerce data)
• Step 5: Purchase Completed (from Shopify data)

Visualizing this sequence in Looker's funnel chart gives you a clear picture of your conversion rates at each stage, highlighting leaky buckets that need attention.

Tips for Effective Campaign Reporting in Looker

• Start with a question. Don't just pull random metrics. Begin with a clear business question like, "Which of our Q3 campaigns had the best return on investment?" This focuses your analysis and prevents you from getting lost in the data.
• Schedule and share your dashboards. Once you've built a useful dashboard, put it on a schedule. Looker can automatically email a PDF of the dashboard to key stakeholders every Monday morning, keeping everyone informed without any extra manual work.
• Keep it simple. Resist the temptation to put every possible metric on your dashboard. A good dashboard tells a clear story and guides the viewer to the right insights. Focus on 3-5 core KPIs and use color and layout to draw attention to what matters most.

Final Thoughts

Looker is a powerful enterprise-level tool that gives marketers the ability to perform deep, sophisticated analyses on their campaign performance. By connecting all your data sources and learning how to navigate Explores, Dimensions, Measures, and Visualizations, you can move beyond surface-level reporting and uncover the insights needed to truly optimize your marketing efforts.

Of course, the setup process for traditional BI tools can be time-consuming, and there's often a significant learning curve just to build a simple chart. That's precisely why we built Graphed. We wanted to provide the power of cross-platform analysis without the complexity. You connect your data sources like Google Analytics, Facebook Ads, and Shopify in a few clicks, and then you can create entire dashboards just by describing what you want to see in simple, natural language. Instead of clicking through menus and learning a new interface, you just ask, "Show me a comparison of Facebook Ads ROAS vs. Google Ads ROAS for last month," and we instantly build the dashboard for you, powered by live data.