Shared rides promise lower fares and higher efficiency, but why did giants like Uber/Ola shut them down? Discover the hidden challenges ?

As a Product Manager, evaluating a feature like ride-sharing (shared rides) requires balancing user experience, business impact, and operational feasibility. Let’s analyze the feature through a PM lens, considering key aspects such as market needs, feasibility, financial viability, and long-term strategy.

1. User Value Proposition:

Pros for Users (Customers and Drivers):

? Cost Savings: Riders pay less by splitting fares, making shared rides an attractive alternative to personal trips.

? Convenience (in theory): Regular commuters traveling along similar routes can save money with minimal route deviation.

? Sustainability Impact: Fewer cars on the road contribute to lower emissions and align with environmentally conscious user expectations.

Challenges for Users:

? Longer Travel Times: Additional pickups and drop-offs add delays, leading to potential dissatisfaction.

? Privacy & Safety Concerns: Sharing a ride with strangers can cause discomfort and increase the risk of unpleasant incidents.

? Flexibility Trade-offs: Riders lose the ability to modify their journey as easily as they would with a personal ride.

Key PM Takeaway:

The product should focus on specific user segments (e.g., regular office commuters or university students) where the trade-offs are acceptable. Understanding the target personas is crucial to ensure adoption.

2. Business Viability (Revenue & Growth Impact):

Why Aggregators Struggle Financially with Shared Rides:

? Revenue Per Trip Declines: Instead of three separate bookings, the company earns from just one ride with lower commissions per passenger.

? Decreased Ride Frequency: Users consolidating into fewer rides means fewer overall transactions, reducing platform engagement.

? Cost of Optimization: Dynamic ride-matching algorithms require expensive infrastructure (AI/ML models for route optimization), increasing operational costs.

? Market Behavior: If shared rides lead to a perception of longer waits and unpredictable travel times, it could reduce app stickiness and daily active users (DAUs).

Key PM Takeaway:

A robust business case is necessary before scaling. Running pilot experiments to understand if the lower margins can be offset by higher volume and if additional revenue models (e.g., in-app ads, premium services) could compensate.

3. Operational Feasibility & Scalability:

Challenges Faced by Operations Teams:

? Route Optimization Complexity: Matching riders dynamically in real-time with minimal detours requires heavy computation and data analysis.

? Driver Resistance: Drivers may prefer direct trips for faster turnover instead of waiting for additional pickups.

? Unpredictability: Traffic, last-minute cancellations, and user delays make the system inefficient.

? City-Specific Constraints: Urban areas with high demand clusters might work, but suburban or rural regions struggle with low density.

Key PM Takeaway:

Pilot the feature in dense urban zones where the likelihood of matching users on similar routes is high, and iteratively optimize based on real-world data.

4. Competitive Benchmarking:

? Uber’s Shared Ride Shut Down: Lessons learned from Uber show the importance of balancing operational costs with user expectations.

? Rapido’s Low Contribution from Shared Rides: If competitors aren’t seeing strong traction, it signals a challenging market fit.

? Carpooling Apps: Alternative models (e.g., BlaBlaCar) focusing on long-distance ride-sharing might provide better use cases.

Key PM Takeaway:

Instead of fully replicating competitors, explore differentiators such as subscription models, exclusive corporate tie-ups, or loyalty programs to make shared rides more appealing.

5. Future Scalability and Product Strategy:

Potential Strategic Directions:

? AI-Driven Enhancements: Utilize machine learning to optimize routes based on historical demand patterns and predictive analytics.

? Corporate Partnerships: Collaborate with businesses to offer shared rides as part of employee benefits for daily commutes.

? Gamification & Rewards: Introduce incentives like ride credits or premium ride upgrades to encourage adoption despite trade-offs.

? Bundled Services: Consider offering shared ride subscriptions with additional perks like discounted food delivery or loyalty rewards.

Key PM Takeaway:

Focus on features that can drive engagement beyond cost savings—building loyalty and habit formation around shared rides.

6. Metrics to Track (KPIs for Shared Rides):

As a PM, tracking success goes beyond ride volume. Key metrics include:

? User Adoption: % of total rides using shared options over time.

? Match Rate: How often users get successfully matched in real-time.

? Cancellation Rate: Higher cancellations might indicate dissatisfaction.

? Ride Completion Time: Measure the deviation from estimated time vs. actual trip duration.

? Net Promoter Score (NPS): User sentiment about shared ride experiences.

? Driver Feedback: Driver satisfaction and earnings comparison with private rides.

Key PM Takeaway:

Monitor early warning signs like rising cancellations or lower match rates to iterate quickly on user concerns.

Final Thoughts Should a PM Invest in Shared Rides?

? If positioned for the right audience (e.g., commuters with predictable schedules), shared rides can enhance customer loyalty.

? However, the feature should not cannibalize core business metrics a balance of volume and profitability is critical.

? PMs should experiment with shared ride models at a smaller scale, focusing on learnings and phased rollouts rather than aggressive expansion.

In short, as a PM, success lies in understanding the trade-offs shared rides are great in theory but pose significant business and operational challenges that must be carefully navigated.