Building Charts from Digital Survey and Prompt Data

This guide shows how to turn your Digital Survey and Prompt data into charts and add them to a dashboard.

Before you start: This guide assumes you've already created a dataset from your Digital Survey or Prompt. To create one, see Managing Sources; to refresh or manage it, see Managing Digital Datasets (link coming soon). (Love Dialog and Rating Dialog data comes as pre-built models, and you can find information on how to create charts from Love Dialog and Rating Dialog data here.)

To build any chart, click the Create button and select Chart. This opens the Chart Builder. Once in the Chart Builder, select your dataset by clicking the dataset selector, searching for the dataset, and clicking Select.

The panel on the left in the Chart Builder is the data sidebar; it lists your data fields grouped by type, and you add a field to a chart by checking it or typing its name into the search bar and clicking Go. For a full tour of how the data sidebar is organized, see Understanding the Digital Data Sidebar (link coming soon).

Building a chart from Survey or Prompt data follows the same general flow. This guide outlines how to create charts and tables for different question types that appear in Digital Surveys and Prompts.

Build charts from Digital Survey data

When you open a Digital Survey dataset, the data sidebar groups your fields into Response Details, Survey Details, Survey Questions, Universal Formulas, Formulas, and Sets. The examples below show how to chart each of the types of questions available in a Digital Survey.

Free form (open text) questions

Open-text answers are best viewed as a table of verbatim responses rather than a chart.

1. In the search bar, add [your free form question] and Response ID.
2. Click Go.

The result is a table listing each open-text response next to its Response ID.

Range questions

1. In the search bar, type count Response ID.
2. Add [your range question].
3. Click Go.

The result is a column chart showing how many responses fell at each value across the range.

Tip: To hide blank responses, add your range question != {Null} to the search bar and click Go again.

Single select questions

Each answer option is stored as its own column, so you will add each column option individually. The data is stored as "1" if the respondent selected that answer option and "0" if they did not; the following sum formulas count the number of "1" responses.

1. In the search bar, type sum and select sum [your question - answer option 1].
2. Repeat for each answer option (for example, sum [your question - answer option 2]).
3. Click Go.

The result is a table showing the number of respondents who selected each answer option.

1. Optionally, add Survey Title to group the results along the x-axis.
2. Click Go.

The result is a column chart with one column per answer option. You may prefer to switch to a stacked column chart.

Multi select questions

Multi select works the same way as single select: each option is its own column, summed individually.

1. In the search bar, add sum [your question - answer option 1], then sum [your question - answer option 2], and so on for each option.
2. Optionally, add Survey Title to group the results.
3. Click Go.

The result is a column chart with one column per answer option. You may prefer to switch to a stacked column chart.

NPS questions

You can visualize NPS (Net Promotor Score) question data in many ways.

Option A: Score distribution (histogram)

1. In the search bar, type count and select count Response ID.
2. Add [your NPS question].
3. Click Go.

The result is a histogram showing how many responses landed on each score from 0 to 10.

Option B: Promoters, Passives, and Detractors (column set)

To group scores into the standard NPS categories, create a column set:

1. At the top of the data sidebar, click + Add and choose Column set.
2. In the Create set dialog, under Select a base column, choose [your NPS question].
3. Under Define groups, keep the toggle on Conditions and define three groups:
   • Name one Promoter, operator Greater than or equal to, value 9.
   • Name one Passive, operator Between, values 7 and 8.
   • Name one Detractor, operator Less than or equal to, value 6.
4. Give the set a name (for example, NPS categories) and click Create. It appears in the Sets section of the data sidebar.
5. In the search bar, add count Response ID and [your new set], then click Go.

The result is a column chart of response counts by Promoter, Passive, and Detractor.

Option C: NPS Score (formula)

To visualize the overall NPS Score, add an NPS formula, as outlined in Commonly Used Formulas in Alchemer Dashboard.

Build charts from Prompt data

Prompt data works a little differently from survey data. Instead of individual questions, a Prompt records the action a customer took in response to it, such as tapping a button, opening a linked survey, following a link, or dismissing the Prompt.

How a Prompt is displayed and reported in Alchemer Digital

In Alchemer Digital, a Prompt appears to your customers as a message with one or more buttons or links. On the Prompt's Reporting tab, Digital summarizes total views, the overall action rate, and a breakdown of customer actions, showing how many people chose each response option. Dashboard lets you build your own charts from that same response data, and combine it with everything else in your dashboards.

To build charts from prompt data, open the Chart Builder and select your Prompt dataset. For Prompt data, the data sidebar groups fields into Prompt Details (setup and metadata), Response Actions (the buttons and links configured on the Prompt), Response Details (response-level fields), Universal Formulas, Formulas, and Sets. There are two common ways to chart Prompt data.

Method 1: Use the Prompt's response options

Use the fields in the Response Actions group to see how customers responded to your Prompt.

1. In the search bar, add Response title and Response type.
2. Type unique count and select unique count Response ID. This counts the number of unique responses for each option.
3. Click Go.

The result is a table listing each response option, its type, and how many unique responses it received.

To focus on specific actions, right-click a value in the table and choose Exclude or Only include (for example, exclude the launch action to see only the actions customers actively took). This adds a filter to the search bar, such as Response type != 'launch'.

To change how the data looks, open the Type panel from the chart toolbar and choose a visualization such as Donut. The chart updates to show the share of responses by option.

Method 2: Use Universal Formulas

Every dataset created from a Prompt includes a set of pre-built Universal Formulas, ready-made counts you can chart without building anything. They are generated automatically from the Prompt's configured actions and typically include a Count of seen plus a Count of clicks for each button or link (for example, Count of clicks on [your option] and Count of clicks on link).

1. In the data sidebar, open the Universal Formulas group.
2. Check the counts you want to compare (for example, the click counts for two or three response options).
3. Click Go.

The result is a table (or KPI) showing the total for each count. Open the Type panel to switch to a column chart or another visualization if you prefer.

Tip: Universal Formulas are the quickest way to chart Prompt engagement, since the counts are pre-calculated for every Prompt dataset. Use Method 1 when you want to break responses down by option, type, or another field.

Pin your chart to a dashboard

Once your chart looks right, add it to a dashboard:

1. Click Pin in the chart toolbar.
2. Choose the dashboard you'd like to add it to.
3. If you don't have a dashboard yet, you'll be prompted to create one.

Your chart now appears on the dashboard and stays up to date as new responses arrive.

Related articles

• Managing Sources - create a dataset from a Survey or Prompt
• Managing Digital Datasets (link coming soon) - refresh and manage a dataset after you create it
• What Digital Data You Can Visualize in Dashboard - the fields available for each interaction type
• Understanding the Digital Data Sidebar (link coming soon) - how fields are grouped, color-coded, and named
• Commonly Used Formulas in Alchemer Dashboard - build your own calculations