🛠️ Self-Service Dashboards

Build insights visually — no coding, no formulas, just logic.

With self-service dashboards, you don’t need to be a data expert to uncover valuable insights from any of the connected data sources to your CDP account. Everything is done through a clean, visual interface — no SQL, no formulas. Just pick what you want to see, decide how to break it down, and drag it into view.

Let’s walk through how it all works.

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🏁 Getting Started

When you land in the Analytics Framework, you’ll see a home base for all your dashboards. Dashboards with the dashboard icon under Description are the out-of-the-box dashboards, while the other dashboards are custom made.

Here’s what you can do from the overview:

• Create a new dashboard — just give it a name (e.g. Fan Loyalty Tracker)

• Search or browse dashboards you’ve made before

• Preview dashboards with thumbnail previews, authors, and last edited times

• Edit, delete, or duplicate dashboards from the menu

• Get a public link to any of your dashboards to share it with non-CDP users, e.g. your management team

• Click into any dashboard to start building or reviewing

Once you create a new dashboard, you’ll enter the dashboard editor. 

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🧱 The Dashboard Builder

Think of the builder as your workspace with a canvas. It's split into two parts:

• On the left, you’ll drag in blocks onto your canvas — things like charts, text, images, or filters.

• On the right, you’ll tell each block what it should display using a simple step-by-step menu.

This is where you shape your story: what data to show, how it should be grouped, filtered, or visualized.

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🗂️ What Data Can You Use?

Before you dive too deep, it’s helpful to understand what kinds of information are available behind the scenes.

Here’s a quick mental model:

• Schemas → Big categories of data, like Profiles, Events, Inventory, Analytics Framework

• Tables → More specific collections inside those categories, like Ticket Purchases or Supporter Records, typically each data source is a table itself. For example: your merchandise system's orders you will find under the Events schema, Merhcandise_system_name table.

• Columns → Individual details you can use (e.g. Event Date, Ticket Price, Country)

• Relationships → Hidden links that let you pull related data across tables

All this you can find when you click on "Customize Analytics View" and on the Data Sources tab. These are the readily configured sources (tables) for analytics purposes. 

 

The different sources (tables) are joined with other sources by the definitions set under Relationships.

Example relationship:

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🎛️ The Right Panel: Tell the Chart What to Show

You can edit your chart's data set, by clicking on the chart and under Tile data, on "Add new data source". Every block you add — whether it’s a chart, table, or number — comes with a little checklist on the right side.

Let’s break it down:

• Measure by  → What number are you showing?
  (Example: Total ticket sales, number of fans, average spend)

• Analyze by → How do you want to break it down?
  (Example: By month, by region, by age group)

• Filter by → What should be included or excluded?
  (Example: Only VIP members, events after January 1st)

• Order by → How should it be sorted?
  (Example: Highest to lowest, newest to oldest)

You don’t need to know any data terms — the platform will guide you with dropdowns, labels, and suggestions. Just think in plain language: “I want to see total fans, grouped by city, only for this season.” 

 

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🧩 What You Can Add to Your Dashboard

Dashboards are made up of building blocks — and you have a rich set of controls to choose from. These aren't just charts — they're tools to help you tell a visual story with your data, cleanly and clearly.

Here’s what you can add:

Basic controls:

• Text blocks to introduce sections, explain data, or label charts

• Images for logos, icons, or banners

• Empty areas to add spacing or improve layout flow (great for esthetics)

Dashlets:

• Single tiles to highlight key metrics like totals or KPIs, e.g. number of orders
  Example tile data set configuration:
  

• Chart tiles which combine a key number with a small inline chart, e.g.: total number of profiles & database growth per day. This chart type has two data sets.
  Example chart tile settings

  

• Tables for showing detailed, row-by-row data: e.g.: number of tickets sold, number of buyers and revenue per event
  Example table data set configuration showing the number of tickets sold (measure by), per ticket price category and event (analyze by), but including only non-free tickets (filter by), and ordering the values by the highest price category (order by)
  

• Advanced charts including multi-series columns and bars, spline and spline area charts, stacked charts, pie and doughnut charts, combo charts, bubble charts, heatmaps, time series, Sankey diagrams, and box-and-whisker plots. These charts types serve more advanced and more visual insight generation. 
  
  Example multi-series chart data set showing the days in 2025 with the highest number of orders and customers. 
  

  Example data set configuration for stacked charts:
  

Example data set configuration for pie and doughnut charts:

Example data set configuration for time series charts (ability to zoom-in and out of chart):

Example data set configuration for bubble charts (note that this chart type requires 3 measure by-s):

Example data set configuration for Heatmap charts:

• Growth tiles to compare values over time and highlight increases or drops, or compare the performance of events, e.g.: season ticket sales this vs. last year, and even sales targets vs. actual performance. 
  The CDP supports two types of Growth tiles: 

  • Period-based: ideal to show the growth of something over time, e.g. database, number of tickets, revenue (single data set required)
  • Event-based: ideal to compare two different things, e.g.: ticket sales for Game 1 vs. Game 2, season tickets for year 1 vs year 2, or sales targets vs. actual performance. (two data set required
  
  

  Example of a Period based Growth tile showing database growth in the last quarter:

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🌐 Dashboard vs. Chart Filters

As you build, you’ll come across two kinds of filters. They both help you zoom in on the right information — they just work at different levels.

• Dashboard Filters
  These apply to everything on the page. Great for things like Date Range or Country.
  

• Chart Filters
  These only apply to one chart. Perfect for focusing that chart on a single campaign, type, or segment.
  Example filtering of a single chart by values for Price only higher than 100.
  

✨ Pro tip: If you don’t want a chart to respond to global filters, just turn off “Apply global filters” in the chart’s settings under the Options tab.

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• Dashboard Filters
  These apply to everything on the page. Great for things like Date Range or Country. The additional options on a Global filter are:

  • Persist filter values: if ticked, the next time you visit the dashboard, the latest selected values will be auto-loaded, not the entire data set

  • Disable Selection for Public Dashboards: if ticked and if your dashboard is shared with a public URL, you can disable certain filters so the users of the public dashboard always see the reports you want to present to them

  • Result set limit: fields with many values can be selected as a filter which could cause performance issues and difficulty to navigate. This setting allows how many values are shown in the filter. If there are more values then the limit, search for the selected value.

• Chart Filters
  These only apply to one chart. Perfect for focusing that chart on a single campaign, type, or segment. You can set these under the FILTER BY section of single chart's configuration. You can add multiple filters to a chart and decide whether those all should apply (AND) or any of them should apply (OR)
  

As you build, you’ll come across two kinds of filters. They both help you zoom in on the right information — they just work at different levels.

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⚙️ Dashboard Settings & Sharing

In the Settings tab, you can control the big-picture stuff:

✨ Pro tip: If you don’t want a chart to respond to global filters, just turn off “Apply global filters” in the chart’s settings under the Options tab.

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• Rename your dashboard

• Add a description for context

• Pin it to your sidebar for quick access

• Make it public, private, or password-protected

• Export the whole dashboard as a PDF or image (great for reporting)
  
  

Once you’re done building, you can easily make changes anytime:

✏️ Updating or Changing Dashboards

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• Click on the Customize Analytics View (available only for non-out-the-of-box dashboards)

• Edit a block by clicking on it

• Delete or duplicate blocks from the ⋮ menu

• Rearrange blocks by dragging them around on the grid system

• Go back to view mode once you're happy with the layout

Nothing is locked in — dashboards are living, breathing tools. Come back anytime to adjust, improve, or reuse.