How to Create a Call Center Dashboard in Looker

Building a dashboard from scratch in a powerful tool like Looker can feel like a tall order, but it's one of the best ways to get clear, real-time insights into your call center's performance. This guide will walk you through exactly how to create a call center dashboard in Looker, from planning your key metrics to building the actual visualizations your team will use every day. We’ll cover what to track, why to track it, and how to put it all together.

Before You Build: Planning Your Call Center Dashboard

Jumping straight into Looker without a plan is a recipe for a cluttered, unhelpful dashboard. The goal isn't just to display data, it's to answer important business questions instantly. Before you create a single chart, ask yourself and your team:

What are the most critical questions we need to answer every day?
What problems do we need to solve? (e.g., high wait times, low resolution rates).
Who will be using this dashboard? (Team leads need different details than agents or executives).

Your answers will guide what you build. For a call center, you're likely trying to answer questions like:

How is our overall call volume trending this week?
Which agents are handling the most calls?
What is our average call wait time right now?
Are we meeting our goal for First Call Resolution (FCR)?
How do customer satisfaction scores correlate with which agent handled the call?

Choosing the Right Call Center KPIs

Once you know what questions to answer, you need to identify the specific key performance indicators (KPIs) that will give you those answers. A great call center dashboard keeps tabs on overall volume, agent efficiency, and customer experience. Here are the essential metrics to start with.

Volume & Efficiency Metrics

Total Calls Offered: The total number of incoming calls. This is your baseline for demand.
Calls Answered: The number of calls your agents actually handled.
Answer Rate: (Calls Answered / Total Calls). This tells you what percentage of calls are getting through to an agent.
Calls Abandoned: The number of callers who hang up before reaching an agent. A spike here often points to long wait times.
Average Handle Time (AHT): The total average duration of a single call interaction, from the time the agent answers until they're ready for the next call. This includes talk time, hold time, and any after-call work.
Agent Utilization: The percentage of an agent’s logged-in time that is spent on call-related activities. This KPI helps with staffing and resource planning.

Customer Experience Metrics

Average Speed of Answer (ASA): How quickly, on average, calls are answered by an agent. This is a direct measure of your team's responsiveness.
Average Wait Time (AWT): The average time a caller spends in the queue waiting for an agent. This KPI has a massive impact on customer satisfaction.
First Call Resolution (FCR): The percentage of calls where the customer's issue is resolved on the first contact, with no need for a follow-up. This is one of the strongest indicators of an efficient and effective call center.
Customer Satisfaction (CSAT): Typically measured through post-call surveys ("On a scale of 1-5, how satisfied were you?"). Tying this back to individual agents or call types can reveal powerful insights.

The Looker Data Model: Understanding the Groundwork

Looker isn’t like dragging and dropping cells in a spreadsheet. It sources its information from a structured data model built by your data team using a language called LookML. This model defines all your business metrics (known as Measures) and data attributes (known as Dimensions) and explains how they relate to one another in your database.

For a call center, your data might come from software like Talkdesk, Aircall, or a CRM like Salesforce Service Cloud. Your data team’s job is to connect those sources and create what Looker calls an “Explore” - a dedicated starting point for you to begin asking questions and building reports.

You don't need to know how to write LookML yourself, but understanding this concept is helpful. When you build a report, you’ll be pulling from a pre-built Explore, such as “Calls” or “Agent Performance.”

How to Create a Call Center Dashboard in Looker (Step-by-Step)

With a clear plan and KPIs in mind, you can finally start building your dashboard tiles (Looker’s term for individual charts or widgets).

Step 1: Create a New Dashboard

First, find the folder where you want your dashboard to live inside Looker. From there, click the New button in the top right and select Dashboard. Give it a clear name like "Call Center Daily Performance" and click Create Dashboard. You'll land on a blank canvas ready for your tiles.

Step 2: Add Your First Tile – A "Total Calls" Scorecard

Headline KPIs are best visualized as single, large numbers so you can see them at a glance. Let’s start with Total Calls.

Click Add Tile on your blank dashboard canvas.
You'll be prompted to choose an Explore. Find the one prepared by your data team related to calls (e.g., "Call Data").
In the Explore interface, you’ll see Dimensions (attributes) on the left and Measures (calculations) on the right. Find a measure like “Total Call Count” and click on it.
Add a date filter. Find a date dimension like "Call Date" and click the filter icon next to it. Set the filter to “is in the last 7 days.” Click Run.
The data will appear in a simple table. In the Visualization panel, select the Single Value option.
Click the gear icon to bring up the Edit panel to fine-tune its appearance. You can edit the title here. Give it a clear name like "Total Calls (Last 7 Days)".
Finally, click Save. Looker will take you back to your dashboard with your first tile in place.

Step 3: Create a "Call Volume Over Time" Line Chart

Seeing trends is just as important as seeing totals. Let’s show how call volume changes day by day.

From your dashboard, click Edit Dashboard in the top right, then click Add Tile and select the same "Call Data" Explore.
Select your "Total Call Count" measure again.
This time, from the Dimensions list, also select a date dimension like “Call Date.” This tells Looker to group the call count by day.
Add a date filter again for your desired time frame (e.g., "is in the last 30 days") and click Run.
In the Visualization panel, select the Line Chart option.
Click the Edit cog to name your chart axes and give the tile a clean title like "Daily Call Volume."
Save the tile to your dashboard. You can now resize and rearrange it next to your total calls scorecard.

Step 4: Build an "Agent Leaderboard" Table

Now, let's track agent performance to see who is handling what. A simple table is perfect for this.

Add another new tile and navigate to your Explore.
From your Dimensions, select a field like “Agent Name."
From your Measures, select the KPIs you want to compare, such as “Calls Answered,” “Average Handle Time,” and "First Call Resolution Rate".
Apply a date filter for the last week or month and click Run.
Looker will generate a table automatically. You can click on the column headers to sort by a specific metric, for example, to see which agent has answered the most calls.
Give the tile a descriptive title like “Agent Performance Leaderboard” and save it to your dashboard.

Repeat this process for all your key metrics. You can create trend lines for Average Wait Time, bar charts to compare resolution rates across different issue types, and pie charts to show the breakdown of incoming call topics.

Best Practices for an Effective Looker Dashboard

Building the tiles is half the battle. Presenting them in a clear, intuitive way is just as important.

Put Key Numbers on Top: Arrange your dashboard with the most important, high-level KPIs (like Total Calls and Average Wait Time) in single-value visualizations at the very top. Viewers should see the most critical information without scrolling.
Add Dashboard-Wide Filters: In the dashboard's edit mode, click Filters in the toolbar. You can add a filter (e.g., for Date or Agent Team) that applies to all the tiles on the dashboard at once. This makes the entire report interactive, allowing managers to drill down and compare performance over different time periods or for specific teams.
Don’t Overwhelm the User: Avoid clogging a single dashboard with 20 different charts. If you have a lot of data, consider creating separate dashboards for different purposes, like one for a real-time overview and another for deeper weekly agent performance analysis.
Use Color Meaningfully: In the "Edit" settings for your tiles, use conditional formatting to make things stand out. For example, you can set your Average Wait Time tile to turn red if the value goes above a certain threshold, making it easy to spot problems immediately.

Final Thoughts

Creating an effective call center dashboard in Looker is about starting with clear questions, focusing on the handful of KPIs that matter most, and then visualizing that data in a clean, interactive way. By following these steps, you can move from raw call data to actionable insights that help you improve efficiency and keep customers happy.

While powerful, tools like Looker involve a steep learning curve and rely on a significant setup process from a technical data team. Building something that feels simple often requires hours of backend configuration. This is precisely why we created Graphed. We connect to your data sources like Salesforce, Shopify, and Google Analytics and let you build real-time dashboards just by asking questions in plain English. Instead of learning a complex new tool, you describe the chart you want to see - "show me first call resolution by agent last month" - and we instantly build the visualization for you, streamlining the entire journey from data to decision.