Understanding the Digital Data Sidebar

When you build a chart in Alchemer Dashboard, the panel on the left is the data sidebar. It lists every piece of data in your dataset, organized into groups and color-coded by data type, so you can find and select what you want to visualize. This article explains how the sidebar is organized for Digital data, how fields are color-coded, and how they're named.

Where you'll see it

The data sidebar appears on the left when you open a dataset in the chart builder (Charts, or the search bar on the Overview page). At the top of the sidebar you can:

• Switch between the Popular and All tabs to narrow the list to commonly used fields or see everything.
• Use Find columns to search for a field by name.
• Select the checkbox next to any field to add it to your chart.
• Use + Add to create your own formulas, sets, and parameters.
• Collapse or expand the panel using the toggle in the top-right of the sidebar.

How Digital data is grouped

Fields are organized into collapsible groups. Groups are listed alphabetically by name, with Formulas, Sets, and Parameters always shown last. The groups you see depend on the interaction type, but typically include:

• [Interaction] Details: setup and metadata for the interaction (title, ID, app, created/updated dates). The group is named for the interaction, such as Rating Dialog Details, Love Dialog Details, Prompt Details, or Survey Details.
• The interaction's content or response value: varies by type. Surveys have a Survey Questions group (one field per question and answer option); prompts have a Response Actions group (one field per configured button or link); and dialogs have their core response value (for example, Love Response (Loved / Not Loved)).
• Response Details: response-level fields (one column each): response ID, submission date, local timestamp, device manufacturer and carrier, OS name and version, browser type, conversation ID, and a set of Is [action] action flags describing what the customer did. Because these are captured per response, charting them returns one row per response.
• Universal Formulas: pre-built counts you can chart without building anything, such as Count of seen and counts of specific button clicks.
• Formulas, Sets, and Parameters: empty by default and always shown last. Use + Add to build your own calculations, groupings, and filters.

Because the named groups sort alphabetically, the exact top-to-bottom order shifts with the interaction name. For a Rating Dialog dataset, for example, you'll see Rating Dialog Details, then Response Details, then Universal Formulas, followed by Formulas, Sets, and Parameters.

Example: Charting Response ID and Response Date Submitted together produces a table with one row per response:

Note: For the full list of fields available for each interaction, see What Digital Data You Can Visualize in Dashboard (link coming soon).

How fields are color-coded

Each field is shaded by its data type, so you can tell at a glance how it can be used in a chart:

• Blue (attributes): text values you group or filter by, such as OS Name or Device Manufacturer.
• Green (measures): numeric values you can aggregate, such as counts and scores. The yes/no Is [action] flags also appear green.
• Purple (dates and timestamps): time-based fields such as Response Date Submitted or Created At, useful for trends over time.

How fields are named

• Metadata and response fields use plain names like OS Name, Response Date Submitted, or Rating Dialog Title.
• Survey question fields are named with the question text followed by the answer option, such as What is your favorite feature of the app? - App in Store.
• Action fields use an Is [action] action pattern, such as Is Rate action or Is Dismiss action.
• Pre-built counts start with "Count of," such as Count of seen or Count of 'Dismiss' button clicked.

Charting by data type

A field's color (its data type) also determines how it charts. When you select fields and run a search, Dashboard generates a default chart (often a column chart or table) that you can then change, for example grouping by an attribute, aggregating a measure, or trending a date over time. For step-by-step guidance, see Building Charts from Digital Survey and Prompt Data (link coming soon) and Working with Love Dialog & Rating Dialog Data (link coming soon).

Related articles

• What Digital Data You Can Visualize in Dashboard (link coming soon) — the full list of fields for each interaction type
• Building Charts from Digital Survey and Prompt Data (link coming soon) — turn these fields into charts
• Managing Sources — create a dataset from a Survey or Prompt