Qualitative signals groups your customer feedback into themed signals so that product teams can quickly see what matters most, without reading every individual item.
Note: This offering is currently in closed beta, available to select Pendo customers for testing. The information that follows isn't a commitment, promise, or legal obligation. The development, release, and timing of any features or functionality described here are subject to change at the discretion of Pendo, which can occur without notice. If you're interested in getting early access and providing feedback, contact your Pendo account representative.
Overview
Qualitative signals uses AI to read your Listen feedback and organize it into signals: clusters of related feedback that represent a common theme. Each signal is shown as a card that summarizes what customers are saying, so that you can spot trends and prioritize work based on evidence rather than reading feedback item by item.
Signals are grouped into four tabs that categorize feedback by type:
- Feature Requests: Feedback asking for new or expanded functionality.
- Pain Points: Feedback describing friction, frustration, or unmet needs.
- Bugs: Feedback reporting things that appear broken or aren't working as expected.
- All: Signals clustered across all your feedback. This tab is marked with an AI sparkle icon.
Each tab is clustered separately, so All is not a combined view of the other three tabs. A theme might appear as a single signal in All but split into two signals in Bugs, or be too small to appear in a category tab at all. The feedback shown in Feature Requests, Pain Points, and Bugs is a subset of the feedback in All.
Note: Feedback is categorized automatically. You can't change the category a signal is assigned to. Signals are refreshed daily.
How signals are categorized
Use the Sort by control to change the order of the signal cards on any tab:
- Volume: Orders signals by the number of pieces of feedback in each signal (the Members figure), so the themes with the most feedback appear first.
- ARR: Orders signals by the annual recurring revenue associated with the accounts behind the feedback, so the themes tied to the most revenue appear first.
- Time: Orders signals by most recent activity, so the themes with the newest feedback appear first.
Use cases
Qualitative signals helps you:
- See the themes emerging across large volumes of feedback without manual tagging or reading each item.
- Focus first on the feedback tied to the most customers or the most revenue.
- Separate feature requests, pain points, and bug reports so that the right team can act on the right feedback.
Prerequisites
To use qualitative signals, you need:
- Listen as part of your Pendo subscription.
- Qualitative Signals enabled for your subscription. The closed beta is opt-in: there is no self-serve setting, so Pendo enables it for you on request. When it's enabled, Pendo uses Google Generative AI to process feedback content and identify themes.
- A subscription in a supported operational region: US, EU, JPN, or AU.
View signals
To open a qualitative signal:
- In the main navigation, go to Listen > Signals.
- Select a tab to filter the signals by type: Feature Requests, Pain Points, Bugs, or All.
- Use the Sort by control to order the signal cards by Volume, ARR, or Time.
- Select Investigate on a signal to open its Signal detail. See View signal detail.
View signal detail
Select Investigate on any signal to open the Signal detail view. This view shows:
- The signal title and a description. The description states the theme itself, generated from all the feedback in the signal.
- A representative quote: one real example from the feedback in the signal, so that you can see how a customer actually put it.
- High-level figures for the signal:
- Members: the number of pieces of feedback in the signal. This is also the figure used for the Volume sort.
- Accounts: the number of different accounts the feedback came from.
- ARR: the total annual recurring revenue of those accounts, shown in your subscription's currency.
- A table listing every piece of feedback in the signal.