Important: Classic Feedback will be retired on August 1, 2026. If you haven’t already, contact your Pendo representative to update your contract to Pendo Listen. After your contract is updated, you must request a data migration if you want to keep your existing classic Feedback data. We recommend completing your migration by May 1, 2026 to ensure a smooth transition. For more information, see Migrate from classic Feedback to Pendo Listen.
This article explains how to manage the process and organizational change involved in migrating from classic Feedback to Pendo Listen.
For information on the technical aspect of the migration, see Request the migration from classic Feedback to Pendo Listen.
Why move from classic Feedback to Listen
Listen reframes feedback as a source of insight, not a ticketing system. It aggregates raw feedback, connects it to user behavior, and uses AI to highlight what matters most. This helps you:
- Identify trends across multiple channels.
- Prioritize based on customer behavior and impact.
- Communicate back to customers at scale.
Key changes from classic Feedback
Hierarchy change
Classic Feedback treated all inputs as individual requests to be triaged and addressed promptly. In Listen:
- Feedback items are raw qualitative data submissions—your library of inputs.
- Ideas are themes that group related items for discovery, validation, and analysis.
For more information on Listen’s architecture, see Listen workflow.
Unified feedback sources
Classic Feedback relied on a visitor-facing portal to capture feedback. Listen pulls in feedback from the ideas portal, Pendo Guides and NPS, and external tools such as Salesforce, Zendesk, APIs, and more. This gives you a broader, multi-channel view of customer needs.
Curated portals
Instead of a public inbox, Listen offers a curated experience where product teams communicate the ideas that are under consideration, in progress, or recently delivered. This reduces moderation overhead and improves customer alignment.
Behavioral context
Because Listen is built on the Pendo platform, every piece of feedback in Listen is tied to user behavior, segments, and account metadata. You can analyze qualitative insights alongside usage trends in dashboards and prioritize based on actual usage.
Automation and AI
Manual triage is no longer required. Automation rules and Listen Explore surface relevant items and answer product team questions instantly. For more information, see Manage feedback with automation rules and Explore feedback with AI in Listen.
Process changes and what to expect
The migration to Listen changes how teams work with feedback. Here's what changed:
| Process item | Before (classic Feedback) | After (Listen) | Why it matters | Suggested process or governance |
| Managing incoming feedback | Teams tried to review and triage every item manually, struggling to keep up with the high volume. | Automation rules route the right feedback (by product area, high-frustration items, recent NPS responses) into saved views for the right PMs. | The most important feedback is surfaced automatically. |
Each product team has a custom saved view with all of their relevant feedback (based on product areas or labels). Each product team has an automation rule to funnel the right feedback into their saved view. Product teams review the summary of their saved view on a regular cadence, for example, monthly. |
| Accessing insights | PMs searched through lists of requests or waited for process owners to share summaries. | Saved views give PMs a personalized library of data. Explore AI gives them instant access to the top themes, and any other questions they want to answer with their data. | PMs can self-serve insights whenever they need them, across discovery, validation, build, and beyond. |
Each product team maintains one or two saved views that act as a library of insights, organized by Product Area or segment, for example. Each product team uses Explore on these saved viewed or with new topics to investigate themes and highlights. |
| Organizing evidence | Requests were merged or tagged manually. | Ideas capture key pain points, strategic initiatives, and in-progress work, with feedback items linked as supporting evidence. AI helps you find the right ideas to track and organize. | Ideas build context organically over time, making it easier to prioritize confidently. |
PMs create ideas for in-progress work, pain points, and and strategic initiatives. While reviewing insights in Explore, PMs can use Listen's AI features to link relevant feedback items to those ideas over time. Product teams routinely perform light idea maintenance, such as archiving outdated ideas. |
| Communicating with customers | Process owners closed the loop item by item, or portals displayed every submission. | Curated portal shows what’s under consideration, in progress, or recently released, with status update emails sent to the relevant customers. | Customers stay engaged and informed at scale, without adding workload for teams. |
Product teams decide on portal strategy. For example, add any ideas that are under consideration or in development to gather ongoing customer feedback. As ideas progress, product teams update the status, which can be updated automatically in the portal, and send an email to all interested users. |
| Prioritization | PMs could filter or segment feedback by customer metadata, but it was difficult to spot themes or connect related requests at scale. | Listen surfaces top themes which can then be analyzed by segment, ARR, votes, or impact vs. effort. | Roadmaps reflect both customer value and business impact. |
Each product team uses ideas (with links to supporting feedback items) as the input to prioritization conversations. Each product team analyzes ideas by ARR/votes/impact versus effort. As ideas gather evidence organically, PMs can quickly analyze and gather data for discussion and review. |
| Triage | Success meant “inbox zero” — reviewing and clearing every submission. | Teams no longer triage individual submissions. Instead, they focus on themes and key insights. | Feedback becomes fuel for strategy, not an endless queue. |
Each product team or department has a dedicated saved view for exceptions, for example, high frustration, bugs, or key account escalations. Each team has an automation rule that routes exceptions into that saved view. The DRI reviews the exception view on a regular cadence. Everything else is handled through ongoing theme and insights reviews. If manual triage is required by product teams, set clear expectations. For example, set aside 30 minutes each week to review feedback views. The goal isn't to get to "zero inbox". |
Potential trade-offs to prepare for:
- Not all feedback receives a response. Focus your communication at the idea level, not individual submissions.
- Feedback statuses are not the central focus. Use statuses to track idea progress, not feedback items. We strongly recommend avoiding a workflow that forces updates on each feedback item, which doesn’t scale well.
- Portal transparency is different. The curated experience reduces noise but may feel less open. Consider updating your Product Feedback Policy or relaunching your Voice of Customer (VoC) program.
How to manage the transition from classic Feedback to Listen
Getting started with Listen is about two things: setting up the workflows that'll power your product teams every day, and easing into the new way of working without overwhelming your organization. Below is an outline of the recommended process for migrating from classic Feedback to Listen.
Step 1. Run a pilot
Before running the full migration, run a proof-of-concept with a subset of data (for example, importing NPS responses) and assemble a tiger team to pilot new workflows in Listen. This helps you test, learn, and adjust before rolling it out more broadly.
Step 2. Add ideas to your workspace
Add ideas for in-progress work, top pain points, and strategic initiatives. Link feedback you already have to build evidence.
Step 3. Configure your portal and communication loop
Publish a portal that reflects current investment areas for development or discovery. Consider setting up Listen emails to notify your users when an idea status changes.
Step 4. Set up automation
Use automation rules to route feedback into saved views by product area or signal strength (e.g. frustration, recent NPS). This helps PMs focus on what matters most.
Step 5. Train your product teams
Help PMs to use Listen for:
- Discovery: Use Explore to search for insights.
- Validation: Run idea tests, open-door tests, publish concepts to the portal.
- Building and iterating: In-app feedback badges capture targeted feedback on beta functionality.
Step 6. Scale intentionally
Decide which sources use which workflows. For example, portal feedback may warrant updates, while support ticket data likely won’t. Update your internal training and customer-facing experience accordingly.
Once you’ve adjusted your processes and you’re ready to roll them out further, request your migration.