PRD: Increasing Zomato Text Reviews

Product Requirements Document

Overview

This project tackles the challenge of boosting quality text reviews within Zomato's Food Delivery segment. Although a large portion of users rate orders, few leave descriptive text feedback—often because the process is lengthy and its value unclear.

Goals

  • Drive revenue via credible reviews: Increase review frequency from loyal users, and convert occasional reviewers by removing friction.
  • Improve review quality: Specifically focus on relevance, recency, and depth.

Approach

User Segmentation

Target frequent orderers (≥12 orders/3 months) who have previously left ratings/reviews.

Problem Validation

Surveys and interviews identified key blockers:

  • Time consumption
  • Lack of perceived value
  • Poor recall
  • Inconvenience

Solution Ideation

Three main ideas emerged:

1. Lean Review with Speech-to-Text

Users submit reviews via voice, aided by speech recognition. Eases friction and shortens review time.

2. Keyword-Based AI Reviews

Auto-generates category-specific keywords; users edit or approve AI-generated reviews.

3. AI Review Assistant

Populates editable default reviews using AI and previous feedback.

Recommended Solution

Speech-to-text reviews scored highest on reach, impact, confidence, and effort. The flow includes quick mic-based review input, tag selection for food aspects, and instant "thank you" feedback.

Metrics & Outcomes

  • Monthly review volume
  • Active text reviewers
  • Orders featuring text reviews
  • Menu conversion rates

Future Directions

Plan to automate moderation, support local dialects, AI summarization, and create top reviewer incentives.

PRD Product Strategy User Research UX Design
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