How to Create a Social Media Dashboard in Looker

Building a Looker dashboard to track your social media performance centralizes all your ad spend and results in one place. This tutorial guides you through the process, from preparing your data to building effective visualizations, providing a comprehensive guide on how to create a powerful social media dashboard in Looker.

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Before You Build: Planning Your Social Media Dashboard

Jumping straight into building charts without a plan can lead to a cluttered and confusing dashboard. A few minutes of planning can save you hours of rebuilding later and ensure your final product is genuinely useful.

Start with Your Goals, Not Your Data

The most effective dashboards start by answering the question: "What business questions are we trying to answer?" The answer determines which metrics matter the most. Common social media goals and their associated metrics include:

• Brand Awareness: If your goal is to get your brand seen, focus on metrics like Impressions, Reach, and Frequency.
• Engagement: To measure how your audience interacts with your content, track Likes, Comments, Shares, and Click-Through Rate (CTR).
• Lead Generation & Sales: For performance-focused campaigns, track Website Clicks, Conversions, Cost Per Acquisition (CPA), and Return on Ad Spend (ROAS).

Define your primary goal first. This will act as your North Star as you decide which data to pull and how to visualize it.

Identify and Gather Your Data Sources

Next, list all the platforms you need to report on. This might include:

• Meta Ads (Facebook & Instagram)
• LinkedIn Ads
• Twitter/X Ads
• TikTok Ads
• Pinterest Ads
• Google Ads (for a holistic performance view)

Unlike some BI tools, Looker doesn't have "out-of-the-box" connectors for platforms like Facebook Ads. Looker connects to SQL databases, so you need a system to pull data from your social media platforms and load it into a central database first. This process is key, so let's break it down.

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Step 1: Get Your Social Media Data into a Warehouse

This is the most critical and often most challenging step for many teams. You need two components: a data warehouse to store the data and an ETL/ELT tool to automatically move the data into it.

What is a Data Warehouse?

Think of a data warehouse as a massive, analytics-optimized storage unit for all of your business data. Instead of keeping your Facebook data on Facebook and your LinkedIn data on LinkedIn, you centralize it all here. Popular choices include Google BigQuery, Amazon Redshift, and Snowflake.

What is an ETL/ELT Tool?

An ELT tool (Extract, Load, Transform) connects your social platforms to your data warehouse. It automatically extracts data through each platform's API and loads it into your warehouse on a schedule. Tools like Fivetran, Stitch, or Supermetrics are designed for this. Without one, you’d need an engineer to build and maintain these fragile data pipelines manually.

The Workflow: From Platform API to Looker

Your data journey will look like this:

Social Media Platform (e.g., Facebook Ads) → ETL Tool (e.g., Fivetran) → Data Warehouse (e.g., BigQuery) → Looker

Setting this up is foundational. For example, using Fivetran, the process would be:

1. Create a Fivetran account and set up a destination (your data warehouse like BigQuery).
2. Create new connectors for each social media source you need (e.g., "Facebook Ads connector").
3. Authenticate your accounts by logging into each platform.
4. Fivetran will then automatically create the necessary tables in your warehouse and start syncing the data.

Once this pipeline is active and data is flowing, you're ready to plug Looker in.

Step 2: Connect Looker to Your Data Warehouse

With your social media data consolidated in a warehouse, you can now give Looker access to it. We'll use Google BigQuery for this example, but the steps are similar for other warehouses.

Follow these steps:

1. In Looker, navigate to the Admin panel in the left sidebar.
2. Under the Database section, click on Connections.
3. Click the Add Connection button.
4. Now, you'll configure the connection settings:
5. Click Test to ensure all settings are correct. If you get a success message, you're good to create the connection.

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Step 3: Define Your Metrics with LookML

Now you get to the part that makes Looker so powerful: LookML. Don't be intimidated by the term. LookML isn't a complex programming language, it's more like a dictionary where you define your business logic once for everyone to use.

You tell Looker what a metric like "CPC" means (spend / clicks) one time in the LookML model, and from then on, any user can drag-and-drop "CPC" into a report without writing any SQL.

Create a New LookML Project

First, you need a project to house your LookML code:

1. Click on Develop in the navigation bar and select Projects.
2. Click New LookML Project.
3. Give your project a name (e.g., social_media_analytics).
4. Under "Starting Point," choose Generate Model from Database Schema and select the connection you just created.
5. Click Create Project. Looker will inspect your warehouse tables and auto-generate starter LookML files for you.

Define Dimensions and Measures

Looker will create "view" files for the tables Fivetran synced, like facebook_ads_insights. Inside this view file, you’ll define your metrics. The two main components are:

• Dimensions: These are fields you use to group or filter your data, like Campaign Name, Date, or Ad Set Name.
• Measures: These are the numbers you want to calculate - aggregations like a sum, count, or average. Examples include Total Spend or Total Impressions.

Here’s an example code snippet you might add to a LookML view file for your Facebook Ads data. Looker’s initial autogenerated files will have a good start, but you’ll want to customize them to make them user-friendly:

view: facebook_ads_insights {
  sql_table_name: `your_warehouse.facebook_ads.basic_understanding` ,,

  dimension: date {
    type: date
    sql: ${TABLE}.start_date ,,
  }

  dimension: campaign_name {
    type: string
    sql: ${TABLE}.campaign_name ,,
    label: "Campaign Name"
  }

  measure: total_spend {
    type: sum
    sql: ${TABLE}.amount_spent ,,
    value_format_name: usd
    label: "Total Spend"
  }

  measure: goal_impressions {
    type: sum
    sql: ${TABLE}.impressions ,,
    label: "Goal Impressions"
  }

  measure: ctr_percentage {
    type: number
    sql: SAFE_DIVIDE(${clicks}, ${impressions}) * 100 ,,
    value_format: "##.0'%'"
    label: "CTR Percentage"
  }
}

By building these definitions, you create a self-service layer that allows your entire team to explore data without every report becoming a request for an analyst.

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Step 4: Build Your Social Media Dashboard Tiles

With the backstage work done, it's time for the fun part: visualizing the data!

Start Building in an "Explore"

An "Explore" is the interface in Looker where you build queries using the dimensions and measures from your LookML model.

Navigate to an Explore based on your social data. From the left-hand field picker, select the metrics you want to analyze. For instance, to see spend per campaign, expand your Ad Insights view, select the "Campaign Name" dimension and the "Total Spend" measure, and click Run.

Looker writes the SQL for you and displays the results in a table.

Choose The Right Visualizations

Now, click the Visualization tab to turn that raw data table into a chart. Here are some essential chart types for a social media dashboard:

• KPI Scorecards: For high-level metrics, use the Single Value visualization. Show your Total Spend, Total Impressions, and Overall ROAS at the top of your dashboard for an at-a-glance summary.
• Performance Over Time: Use a Line Chart to answer questions like, "How has spending trended over time?" Update the X-axis and metrics like spending and impressions on the Y-axis.
• Spend by Platform: Use a Column Chart or Bar Chart to compare performance across different platforms. Group by Source Name and show metrics like Cost per Conversion or ROAS.
• Campaign Breakdown: Use tables to dig into specifics for each campaign. Add columns for Campaign Name, Impressions, CTR, etc.

Once you configure a tile (visualization), click Save to add it to your dashboard.

Step 5: Add Filters to Make Your Dashboard Interactive

Filters make your dashboard more interactive and allow users to customize the view to their needs. Consider adding filters for dimensions like Date Range, Campaign Name, and more to give users a way to slice and dice the data.

Final Thoughts

Creating a social media dashboard in Looker allows you to amplify your social media strategy by providing visual insights into your data. This pipeline of LookML definitions and custom visualizations gives you and your team the ability to make data-driven decisions with ease.