Product Manager Ground Transport-Cabs

Role: Product Manager

Level: RL4

Location: Bangalore

Reporting to: Director - Product Management

About The Business

Go-MMT Cabs is a leading player in India's organized cab-hailing industry, setting new benchmarks in service reliability and quality for both business and leisure travel. Our commitment to excellence makes us the preferred choice for planned journeys, across three core products:

Outstation Cab Hires: Intercity cab bookings across 80,000+ routes, with flexible multi-day ride options.

Transfers: Seamless airport transfers across 75+ Indian cities and 700+ international airports, backed by industry-leading fulfilment and NPS.

Local Cab Rentals: Hourly rental services offering dedicated availability for local travel, errands, and business needs.

At Go-MMT Cabs, we are redefining the cab booking experience through data and technology — with reliability, convenience, and customer satisfaction at every step.

About The Role

This role owns the post-booking experience for cab customers across MakeMyTrip and Goibibo — spanning the entire journey from booking confirmation to trip completion or cancellation. The mandate is to build a GenAI-led transformation of post-sales servicing: using large language models, conversational AI, and intelligent automation to proactively resolve issues, personalize communication, and reduce human intervention, while using strong data aptitude to diagnose consumer pain points at their root cause.

You will sit at the intersection of product, data, and applied AI — translating messy, high-volume customer signals (calls, chats, reviews, cancellations) into a prioritized roadmap of GenAI-powered and traditional product interventions that measurably improve customer experience and operational efficiency.

Key Goals

GenAI-Powered CX Transformation: Deploy Generative AI models and conversational tools to proactively resolve queries, streamline post-booking support, improve NPS, and significantly reduce contact ratios.

Data-Driven Issue Prevention: Analyze user behavior and post-booking funnels to eliminate friction, reducing cancellations and increasing net served bookings.

Retention & LTV Growth: Create a friction-free post-sales journey that builds trust, maximizes repeat bookings, and improves long-term customer retention.

Detailed Job Description

Pain Point Identification & Sizing

Deep-Dive Problem Diagnosis: Analyze NPS detractor feedback, call transcripts, cancellation logs, and behavioral funnels to pinpoint root causes across product, operational, and supply dimensions.

Data-Backed Prioritization: Quantify friction points using ROI frameworks to prioritize high-impact product and GenAI initiatives.

Metrics Driven & GenAI Innovation

Core Metrics Optimization: Track and improve NPS, contact ratios, cancellation rates, and repeat rates.

GenAI Integration: Champion applications like conversational AI, automated contextual support, and predictive issue resolution to eliminate post-sales friction.

Funnel Analytics: Utilize tools such as Omniture and Sql dashboards to monitor user post-booking journeys, drop-offs, and GenAI interaction performance.

Execution & Cross-Functional Collaboration

Scrum & Delivery Management: Facilitate daily stand-ups, manage sprint execution, and author structured PRDs, wireframes, and GenAI prompt/flow specs.

Stakeholder Engagement: Partner across Product, Engineering, GenAI core teams, Supply/Demand, Operations, Finance, and Customer Contact Center teams to feed user insights into continuous platform enhancements.

Key Responsibilities

• Consumer Pain Point Discovery & Prioritization
  
  

Analyze the root causes of NPS detractors, driver/customer calls, chat transcripts, and user cancellations — separating technical/product issues from supply-side and operational issues.

Use GenAI-based text and voice analytics (call/chat summarization, topic clustering, sentiment tagging) to surface emerging issues faster and at greater depth than manual review allows, and to identify underlying behavioral and journey-level patterns rather than surface-level tickets.

Quantify problems and prioritize use cases based on ROI — building a structured, data-backed framework that balances quick wins with larger transformation bets and keeps effort focused on high-impact issues rather than anecdotal noise.

• GenAI-Led Product & Experience Transformation
  
  

Own the product vision for applying GenAI across the post-sales journey — including conversational assistants, automated issue resolution, intelligent driver-customer communication, and predictive proactive care.

Partner with data science/AI engineering teams to scope, prioritize, and ship GenAI use cases, defining success metrics upfront (containment rate, resolution time, CSAT/NPS uplift, cost-to-serve).

Continuously evaluate emerging LLM/GenAI capabilities and assess where they can responsibly replace or augment manual servicing workflows.

• Metrics, Tracking & Instrumentation
  
  

Stay closely informed on key metrics and trends — NPS, call ratios, cancellation rates, repeat rates — to guide roadmap decisions, and build dashboards that keep this visible to stakeholders on an ongoing basis.

Utilize front-end analytics tools such as Omniture, sql dashboards to track user experience, and define instrumentation requirements for new GenAI features so impact can be measured rigorously post-launch.

• Execution & Delivery
  
  

Lead key post-sales initiatives across both brands (MakeMyTrip and Goibibo), ensuring timely, high-quality delivery.

Facilitate daily stand-ups to keep the team accountable and aligned to the delivery plan; plan detailed sprints and align closely with engineering and data science leads for effective execution.

Maintain rigorous documentation — PRDs, BRDs, designs — including clear articulation of data/AI model requirements.

• Cross-Functional Collaboration
  
  

Collaborate across product, engineering, data science, cab demand & supply, post-sales common product, Mydesk, finance, and post-sales engineering teams to align and drive projects across functions.

Partner closely with the Customer Contact Centre team to stay on top of emerging issues and escalations, ensuring feedback loops directly inform the GenAI and product roadmap.

Preferred Qualifications

Education: MBA, preferably from Tier-I institutes (engineering background a plus).

Experience: 3-6 years total experience, with 2-3 years as a Product Manager in an e-commerce/consumer internet setting; 2+ years in B2C product management, ideally within e-commerce or ride-hailing. Post-sales customer experience exposure is a plus.

GenAI & Data Aptitude: Hands-on exposure to GenAI/LLM-based products (chatbots, summarization, automation) and comfort working with large, unstructured datasets using standard data analysis techniques.

Analytics Proficiency: Experience with analytics tools such as Google Analytics and Omniture; proficiency in Excel, SQL querying, and PowerPoint for data storytelling.

Project Execution: Strong skills in detailed project planning and multi-team collaboration to ensure successful execution.

Communication: Excellent verbal and written communication skills; able to interact confidently with both business and technical stakeholders, and to influence without direct authority.

Ownership & Accountability: High ownership, self-driven approach to delivering projects on time.

Structured Thinking: Ability to think critically, organize thoughts clearly, and produce high-quality documentation for both technical and non-technical audiences.

Product Lifecycle Management: Experience launching consumer internet products and managing the full product lifecycle using agile methodologies — PRDs, BRDs, wireframing, UX design, and metric tracking.

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