Feedback analytics

Streamline feedback triaging by unifying fragmented tools into a single, scalable platform—designed to adapt to evolving org priorities without breaking the user journey.

Streamline feedback triaging by unifying fragmented tools into a single, scalable platform—designed to adapt to evolving org priorities without breaking the user journey.

Focus areas

Navigating ambiguity

Resolving conflicts

Context

As part of the feedback team at Google, I led the design of a new feedback triaging experience aimed at replacing a legacy tool that was obsolete, inefficient, and misaligned with user needs. The project spanned ambiguous problem spaces, shifting organizational priorities, and cross-functional conflict — and ultimately led to a strategic, adoptable solution built with both users and systems in mind.

Orientation - the feedback journey

Challenges & opportunities

Solutions

➡️

Product teams set up feedback as per their requirements

😔

Limited customizations

😔

Heavy reliance on engineers

➡️

Product teams analyze feedback to improve their products

😔

Overwhelmed by junk - difficult to spot useful feedback

[you are here]

😔

Lack the means to circle back to the users with updates

Configure

Collect

Consume

?

➡️

Users give feedback with various intents - express dissatisfaction, seek help, report issues

😔

Difficulties in articulating issues

😔

Feedback often the only (ineffective) way to seek help

➡️

Users expect a response

😔

Instead they are left wondering what happened to their feedback - leading to distrust & apathy

Challenges & opportunities

Solutions

➡️

Users give feedback with various intents - express dissatisfaction, seek help, report issues

😔

Difficulties in articulating issues

😔

Feedback often the only (ineffective) way to seek help

Collect

➡️

Users expect a response

😔

Instead they are left wondering what happened to their feedback - leading to distrust & apathy

?

Product teams analyze feedback to improve their products

➡️

Overwhelmed by junk - difficult to spot useful feedback [you are here]

😔

😔

Lack means to circle back to the users with updates

Consume

Product teams set up feedback as per their requirements

➡️

Limited customizations

😔

Heavy reliance on engineers

😔

Configure

Challenges & opportunities

Solutions

➡️

Users give feedback with various intents - express dissatisfaction, seek help, report issues

😔

Difficulties in articulating issues

😔

Feedback often the only (ineffective) way to seek help

Collect

➡️

Users expect a response

😔

Instead they are left wondering what happened to their feedback - leading to distrust & apathy

?

Product teams analyze feedback to improve their products

➡️

Overwhelmed by junk - difficult to spot useful feedback

[you are here]

😔

😔

Lack means to circle back to the users with updates

Consume

Product teams set up feedback as per their requirements

➡️

😔

Limited customizations

Heavy reliance on engineers

😔

Configure

Listnr

➡️ The existing tool

Listnr is used by multiple product teams at Google to triage and analyze incoming feedback, create bugs, and take action.

It also acted as an entry point for other feedback tools such as the feedback form configurator, close-the-loop email responder and the happiness tracking survey.

However, the tool had several limitations that hindered efficiency and usability.

⚠️ Problems

Built on a soon-to-be-deprecated engineering framework, blocking future upgrades.

Lacked meaningful filters to segment and analyze feedback.

ML tagged issues, but insights still had to be manually uncovered.

Sentiment analysis was misleading, as most feedback was inherently negative.

Fragmented tooling — related features (feedback configurator, ML monitoring, responder email tool) existed in silos, built on modern frameworks.

My role

Navigating ambiguity

As the UX designer on the team, I worked closely with the PM, engineers, and ML researchers to:

  • Identify user pain points.

  • Align tool capabilities with stakeholder goals.

  • Propose a scalable and cohesive information architecture.

  • Drive the design of a new, unified feedback configuration and triaging platform.

Design brief

Redesign Google’s internal feedback triage tool to unify fragmented workflows, surface actionable insights from ML-tagged reports, and streamline decision-making through a scalable, end-to-end experience.

Guiding principles:

🔸

Scalable so that it can accommodate future capabilities.

Scalable so that it can accommodate future capabilities.

🔸

Consistent so that users have a seamless experience.

Consistent so that users have a seamless experience.

🔸

Actionable so that users are enabled to take the next best action.

Actionable so that users are enabled to take the next best action.

🔸

Feature parity so that users did not miss the existing functionalities.

Feature parity so that users did not miss the existing functionalities.

The new information architecture

ℹ️ Explanation

I designed a new information architecture focused on consolidation and seamless navigation. This involved redefining primary and secondary navigation across existing tools to fit within a unified framework, while introducing new layers of functionality. The approach was well received by cross-functional partners as we moved toward realizing the vision of an integrated feedback platform.

❓ Rationale

Tools like the feedback form configurator, close-the-loop email responder, and happiness tracking survey all existed in silos—each built on a modern tech stack, but disconnected from one another and from Listnr. Product teams frequently had to switch between these surfaces, resulting in friction, context loss, and a fragmented workflow. I saw this as an opportunity to propose a unified experience that would streamline these interactions and reduce fragmentation.

Listnr 2.0

1️⃣ Landing page

The new landing page presented overall feedback volume within a selected date range, categorizing it into actionable vs. junk feedback. Historical data was layered in to help teams identify spikes and anomalies over time.

Actionable reports could then be further explored using filters such as ML-generated themes, platform, locale, and user segments—enabling more targeted analysis and prioritization.

2️⃣ Issues page

The new Issues page could be accessed either through the primary navigation or by drilling down directly from a chart on the landing page. It introduced advanced filtering, improved visualizations, and AI-generated themes to support deeper exploration and faster prioritization.

⚠️

⚠️

Midway through the project, an org-wide reprioritization hit. The full redesign was at risk of being scrapped.

Midway through the project, an org-wide reprioritization hit. The full redesign was at risk of being scrapped.

Engineering recommendation

ℹ️ Explanation

Engineering proposed linking the new landing page to the legacy dashboard, allowing users to see high-level metrics in the new UI before switching to the old system for deeper exploration—aiming to reuse completed work without expanding scope.

❓ Rationale

Given the org-wide reprioritization, this was a practical compromise—allowing the team to ship partial value, preserve completed work, and minimize engineering effort without committing to a full migration.

PM recommendation

ℹ️ Explanation

The PM proposed supporting limited drill-down functionality by including the newly designed Issues List page. In this approach, users could begin with the new landing page, drill into categorized issue lists, and then transition to the legacy system for deeper report-level actions.

❓ Rationale

This approach preserved a key part of the new experience while enabling granular filters for targeted analysis—aimed at improving usability and encouraging adoption within limited scope and resources.

My role - user advocacy

Resolving conflicts

ℹ️ Explanation

I highlighted that both fallback options would result in a disjointed experience—starting with a modern UI but dropping users into the outdated system. To avoid this, I proposed a lightweight Reports page to complete the triage flow within the new interface.

❓ Rationale

This preserved continuity without adding major tech overhead and made the experience feel complete. It increased the likelihood of adoption and was ultimately agreed upon after several rounds of stakeholder alignment.

Outcome

  • The final product included all three views — Landing Page → Issues List → Lightweight Reports — allowing a smooth, self-contained user journey.

  • Adopted by 2+ product teams.

  • Sparked interest in broader adoption and future iterations.

Thanks for the read!

Thanks for the read!