Why choose Namma Yatri? 🤨

To understand why? i chose “Namma Yatri” I’d strongly urge you to go through the below page and dive deep into the market, users and other interesting insights.

Namma Yatri - Deep Dive

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Namma Yatri's appeal lies not only in its rapid growth and the immense scale of operations but also in its core mission to provide a fair and transparent platform for both drivers and users. Its zero-commission model and emphasis on community and inclusivity reflect a disruptive approach to the ride-hailing industry.

These factors, combined with my own frequent use and positive experiences with the service, decided to choose Namma Yatri, again as the focus of my E&R project. The platform stands out as a promising solution to pressing problems in the last-mile mobility space.

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The Numbers, chico, they don’t lie 🔢

Let’s take a look at some of the most important metrics that back the exclusive growth story and highlights potential dangers of blitz-scaling for Namma Yatri.

Assumptions:

1. We are considering the services of the entire family of Apps (Yatri Sathi, Mana Yatri, Namma Yatri etc ) as one
2. We are focusing on the auto ride hailing specific as NY is already offering + launching cab booking services in a few cities as well.

Engagement

Step 1 —> Understand your product

1. What is the core value prop of your product? How do users currently experience that core value prop repeatedly?
2. 1. CVP: “Namma Yatri offers a no-commission auto ride-booking platform that connects riders with drivers, prioritising transparency, speed and affordability for both ”
   2. Users experience this core value proposition by:
   3. 1. Regularly booking rides through the app due to its transparent pricing, quick booking times & low waiting times
      2. Benefiting from competitive fare rates and safety features, potentially leading to repeated use when compared to other ride-hailing services.
3. What is the natural frequency of your product?
4. • The below classification is based upon UXR & Open Data (added above).

     Action on App	Dormant	Quote Explorer	Regular	Frequent
     Open App	NA	As needed	4-5 times a week	7+ times a week
     Search Quote	NA	As needed	4-5 times a week	7+ times a week
     Book Ride	NA	Occasionally	2-3 times a week	7+ times a week
     Complete Ride	Na	Occasionally	2-3 times a week	7+ times a week

5. Do you have other sub-products? What is their natural frequency like?
6. • NY has no sub-products per say. But they so have sister apps in different states and a common driver-facing app as well. The natural frequency is similar to the above and the expectation is for the user to continue using the sister apps in the new city, when they are travelling.
7. What is the best engagement framework for your product?
8. • Frequency Selection

     Engagement Framework	Key Tracking Metric	Selected	Rationale
     Frequency	# of rides booked per week	Yes ✅	Frequency of rides booked is a direct indicator of the user realising the CVP of Namma Yatri and returning to experience the same. It is also the single most important driver of revenue
     Breadth	# of app features used	No ❌	Since NY is scaling with their PMF features, their roadmap indicates expanding on breadth-wise features over time. Right now, the book a ride feature is the north star of the app and will remain so.
     Depth	1. Avg time spent in-app per session

   • 2. No of sessions per week | No ❌ | Average time spent in the app cannot be a metric that indicates the experience of CVP by the user. |
   • Why Frequency?
   • • The core action of booking rides is the most critical engagement metric for Namma Yatri. More frequent bookings suggest that users are choosing Namma Yatri consistently over competitors, indicating strong product-market fit and effective user retention.
     • Booking confirmation under a minute and the start of the trip within 5 minutes is usually the pinnacle of Aha! moments that can be experienced by the customer. Getting an instant booking is the first positive experience (amongst the other Aha Moment) experienced by the customer
     • The major bottlenecks faced by NY team as of today is probably conversion rates, booking cancellation rates and demand-supply mapping and fulfilment. By focusing on frequency, Namma Yatri can prioritise strategies that fuel their growth. This could involve developing loyalty programs, improving the ease and speed of booking and start of trip, and offering personalised incentives based on user booking patterns etc. to drive retention.

Step 2 —> Define

1. Mention the action(s) that make someone an active user for your product:
   
   Aligning this to NY’s CVP, The core actions that make someone an active user are:
   

1. Booking a ride.

2. Opening the app to check for fare estimates or availability (Search Quote)

3. Rating a driver or a trip after completion. (ride completion)

4. Using in-app support and safety services or providing feedback during/post ride (SOS Feature)

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2. Mention the natural frequency of your product
   
   a. Dormant Users:

• Open App: NA
• Search Quote: Rarely, if no other option is available
• Book Ride: NA
• Complete Ride: NA
• Use Case: Considers NY as one of many options for a rare requirement
  
  b. Quote Explorers:
• Open App: Open the app as needed, without a regular pattern.
• Search Quote: Search for quotes on an as-needed basis.
• Book Ride: Occasionally book rides depending on the need/quote
• Complete Ride: Occasionally complete rides, typically corresponding to their booking pattern
• Use Case: NY is an alternative for their other apps to which they are more loyal
  
  c. Regular Users:

• Open App: Open the app 4-5 times a week, indicating consistent but not daily use.
• Search Quote: Actively search for quotes 4-5 times a week to compare options or plan trips.
• Book Ride: Book rides 2-3 times a week, suggesting a routine usage of the service for commuting or regular trips.
• Complete Ride: Similarly, complete rides 2-3 times a week, matching their booking behavior.
• Use Case: Short travels to supermarkets, religious events, friends and family visits
  
  d. Frequent Users:
• Open App: Open the app more than 7 times a week, demonstrating daily engagement.
• Search Quote: Search for quotes frequently, matching their high app usage rate.
• Book Ride: Book rides more than 7 times a week, indicating a heavy reliance on the service for daily transportation needs.
• Complete Ride: Consistently complete rides more than 7 times a week, confirming their active participation and dependency on the app for their transportation needs.
• Use Case: Daily commute/connection commute (first-mile/last-mile)

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Step 3 —> Segmentation

For the E&R User Research, I have spoken to 5 people of different categories. Insights from previous interviews (~15) + Survey Responses (27) + Driver Chats (~ 6) have shaped up the logic for my segmentation.

ICP/Persona Based Segmentation

*Note: ICP 1 & 2 prioritise time over money, but the inverse is true for ICP 3

Natural frequency based segmentation

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​Step 4 → Engagement for Namma Yatri

Here are six proposed engagement campaigns for Namma Yatri, tailored to different user segments, leveraging insights from their behavior patterns:

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Retention 📊

Step 1 → Understand

1. Current Retention Rate: For Namma Yatri out of the total installed user base, only 20-25% is active in a given week. The app also suffers from high uninstall rates of 40-50% within the first 3 days of installation (Source: Namma Yatri Hackathon Page. With the above data we can draw a guess on the retention rates)
   
2. • Day 0 (D0): 100% (All users who installed the app are considered retained on day 0)
   • Day 3 (D3): 55% (Assuming a 45% uninstall rate within the first 3 days)
   • Day 7 (D7): Given the high uninstall rate early, we expect a slight decrease from D3 to D7, estimating 50%
   • Month 1 (D30): Projecting further attrition, we might see about 35% retention as users who find immediate value stay longer.
   • Month 3 (D90): Retention could decrease to about 25%, considering ongoing usage and value recognition by the core user base.
   • Month 6 (M6): Assuming further natural drop-off, retention might be around 20%.
   • Month 12 (M12): By the one-year mark, retention might stabilize around 15% for those who integrate the app deeply into their routines or find consistent value in the service.
     
3. Retention Curve Analysis: The retention curve for Namma Yatri is as follows:
4. • Day 0 (D0): 100%
   • Day 7 (D7): 50%
   • Month 1 (D30): 35%
   • Month 3 (D90): 25%
   • Month 6 (M6): 20%
   • Month 12 (M12): 15%
     

The retention curve tends to flatten around Month 3 (D90), where it shows a slower decline from 25% at Month 3 to 20% at Month 6, and then to 15% by Month 12. This suggests that after the initial three months, the rate of user drop-off decreases significantly, indicating a stabilisation in user retention. This pattern is typical for apps where users who continue to engage past the early critical period are likely to remain relatively steady users.

The critical period for user retention is the initial engagement (acquisition+onboarding) phase. Users who find immediate value in the service, such as ease of booking and reliable rides, are more likely to become long-term users. The first few interactions are vital in setting the retention trajectory.

1. ICPs Driving Best Retention:
2. 1. The '9-5' Machas:
   2. • Retention Drivers: Seeks efficient and economical commutes to fit a busy work schedule. Values the app's ability to provide timely and cost-effective transportation solutions, ensuring a smooth daily commute without the hassle of traditional transport methods.
   3. Ms Early Career:
   4. • Retention Drivers: Looks for a reliable service that offers a balance of affordability and dependability, especially important for managing both professional and personal life. Appreciates Namma Yatri’s quick booking and safety features
        
3. Channels Driving Best Retention:
4. • Notifications - Instant dopamine hit, catchy (low-key click baity) content
   • In-app Banners - Ensures engagement at the right place and right time in the user journey, the experience is very controllable
   • PR (News & Media) - PR as a channel about the massive growth story, open data and social angles, driver and user testimonial drives trust and reliability on the service. The PR drives discussion at social gatherings which also drives a crazy WOM flywheel
     
5. Sub-features or Products Driving Best Retention:
6. • Features such as ‘local languages’, accurate fare estimates, auto-book, trusted driver matching from self-created pool, and SOS are widely adopted and loved.【Namma Yatri Hackathon + UXR】. Frequency of the above mentioned features are dependant to each scenario.

Step 2 → Define

Common Reasons for User Churn:

80% of the interviewed candidates still had not uninstalled Namma Yatri, which is a remarkable retention for this sample size (considering bias). The others however gave a few reasons they felt Namma Yatri isn’t the right fit for them.

Users deleting the app shortly after installation, infrequent usage, and low engagement with promotional communications are strong indicators of potential churn. (Source: Namma Yatri Hackathon)

Step 3 → Resurrection Campaigns for Namma Yatri

Conclusion 🧠

1. Effective engagement strategies, such as regular notifications and personalized promotions, keep users actively using the app and ensure it remains their preferred transportation choice.
2. Strategies to improve retention focus on enhancing the initial user experience to reduce early uninstall rates, such as streamlining onboarding and educating users about key features.
3. Resurrection campaigns aim to reactivate dormant users and convert occasional users with targeted communications that address specific user issues, increasing the overall user base.

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Note:
I really could not do a good job formatting here due to several technical glitches. I would love for you to experience the content through this notion website

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