RED BUS

Detailed Case Analysis of RedBus: Applying Product Management Principles

1. Problem Identification and Empathy (Session 1 & 2)
• Key Issues Identified: RedBus faces a challenge in converting platform visitors,
particularly those booking short-route journeys. The issue stems from a significant
drop-off between the 'Search' and 'Seat Layout' stages, especially for routes under
250 km.
• Empathy Approach: Using design thinking and empathy mapping, the product team
needs to delve into understanding why short-route users disengage. Factors such as
the preference for flexible travel options and cost sensitivity are key. Empathy
interviews and active listening through customer feedback could help to identify
deeper insights about these drop-offs.
• Customer Personas:
o Frequent Short-Route Travelers: These users typically want quick, last-minute
options and are less concerned with convenience. Their focus is on the cost,
flexibility, and real-time information.
o Pain Points: Lack of flexibility (due to rigid booking options) and insufficient
information about real-time bus status.
o Gains: Providing flexibility through features like open ticketing and accurate
real-time data would cater directly to these users.
2. Product Vision and Roadmap (Session 3 & 4)
• Product Vision: The vision for RedBus is to make short-route travel easier and more
accessible by addressing customer pain points. The introduction of the "Open Ticket"
system can be pivotal for solving flexibility and real-time information gaps. This
system would allow users to purchase a ticket that can be redeemed on any bus
within a specific time window, offering them the flexibility they desire.
• Strategic Planning:
o OKRs:
▪ Objective: Increase the conversion rate (CR) of short-route travelers.
▪ Key Results: Implement flexible ticketing solutions, real-time bus
tracking, and cost-effective pricing options to reduce drop-offs.
• KANO Model for Feature Prioritization:
o Must-Have: Flexible booking (Open Ticket) that offers a valid ticket across
multiple buses on short routes.
o Performance Needs: Real-time bus tracking and accurate bus schedules.
 o Excitement Features: Transparency in pricing and no last-minute negotiation
hassles.
3. Product Discovery (Session 5 & 6)
• Discovery Process:
o Conduct user interviews, field research, and funnel analysis to identify what
causes drop-offs. The initial analysis identified that users drop off after
viewing bus options but before selecting seats, especially on short routes. To
tackle this, the product manager proposed conducting real-time user tests
and surveys to collect qualitative data.
o User Research and Discovery: Engage with frequent travelers on short routes
through empathy interviews and surveys to validate the hypothesis that they
prioritize flexibility over other features. The customer letter technique could
help visualize future customer expectations.
• Risk Factors Identified:
o Value Risk: Will customers find the Open Ticket valuable enough to use?
o Usability Risk: Can users easily understand and use the new flexible ticketing
system?
o Feasibility Risk: Can bus operators implement this system effectively across
routes?
• RICE Prioritization for Features:
o Reach: A large number of short-route travelers could benefit from the Open
Ticket system, providing a wide impact.
o Impact: The introduction of this system would significantly improve the user
experience by reducing booking friction.
o Confidence: Field studies suggest high confidence that the Open Ticket will
address drop-offs.
o Effort: Moderate effort to integrate with the current RedBus system but high
effort in negotiating with bus operators for uniform pricing.
4. Customer Experience and Funnel Management (Session 8 & 9)
• User Journey Map:
o RedBus needs to refine its customer journey map, particularly focusing on
improving the short-route user experience. Currently, the customer journey
for short-route bookings shows a significant drop-off at the bus selection
stage, primarily due to a lack of flexible booking options and cost clarity.
Mapping the journey from the ‘Search’ stage to final conversion will help
pinpoint the friction points.
 o Service Blueprinting: Frontstage and backstage actions need to be aligned to
ensure smooth delivery of the Open Ticket feature. This involves training bus
operators and ensuring real-time system updates.
• AARRR Funnel Analysis:
o Acquisition: Improve awareness and education about the Open Ticket feature
through targeted marketing, focusing on short-route travelers who frequently
travel for business or leisure.
o Activation: Ensure seamless activation of the Open Ticket system by making it
visible during the search process. Highlight the advantages of flexibility, cost-
effectiveness, and real-time updates.
o Retention: Encourage repeat usage by offering discounts or loyalty programs
for short-route users who regularly use the Open Ticket feature.
o Referral: Implement a referral program that rewards users for promoting the
Open Ticket system to others, particularly targeting younger, tech-savvy
travelers.
o Revenue: Monitor if the Open Ticket system improves conversion rates and
boosts overall revenue from short-route bookings. The cost-effectiveness of
this system could drive more users to book online rather than relying on walk-
ins.
5. Solution Design and Execution
• JTBD Framework: Using the Jobs-to-be-Done (JTBD) framework, RedBus has
identified key customer needs such as real-time information, flexibility, and cost-
effectiveness. These are being addressed by the Open Ticket solution.
o Information: Real-time bus occupancy, schedules, and ETA updates will help
users make informed decisions.
o Flexibility: The Open Ticket system allows users to book tickets without
committing to a specific bus, providing the flexibility to board any bus on the
route.
o Cost Effectiveness: A fixed price across buses removes the need for last-
minute negotiations and enhances transparency.
• Product Roadmap: Based on the RICE scores, features such as real-time information
and Open Ticket implementation will be prioritized. A Minimum Viable Product
(MVP) will be launched to test the core functionalities.
• Scrum Implementation: The Open Ticket feature will be developed using the Scrum
methodology with sprints to ensure rapid development and feedback integration.
Daily standups and sprint reviews will help align cross-functional teams.
6. Monitoring and Optimization
 • A/B Testing: The Open Ticket MVP will initially be launched to 10% of the user base,
using A/B testing to compare the conversion rates of users with and without access
to the new feature. This will help gauge its effectiveness without risking overall CR.
• Data Analysis: RedBus will continuously monitor user behavior post-launch,
identifying whether the Open Ticket feature improves funnel conversion rates.
Metrics such as time spent on each stage of the funnel, drop-off rates, and user
satisfaction will be closely watched.
• Iteration: Based on feedback from A/B testing, the product team will iterate on the
Open Ticket system to refine its usability, improve its appeal, and address any
unforeseen issues (e.g., users’ confusion about how the ticket works).
Conclusion
RedBus is positioned to solve the critical issue of conversion drop-offs in short-route
bookings by using a blend of empathy, data-driven discovery, and agile product management
techniques. The introduction of the Open Ticket system could significantly enhance
customer experience by offering flexibility and transparency. Continuous monitoring and
iteration will ensure the solution aligns with both user needs and business goals.
Uber Case
Detailed Case Analysis of Uber: Applying Product Management Principles
1. Problem Identification and Empathy (Session 1 & 2)
• Key Issues Identified: Uber faced a challenge in balancing cost reduction with rider
experience in the launch of Express POOL. The new service offered cheaper rides by
asking riders to wait and walk to a designated pick-up point, but longer wait times led
to higher cancellation rates.
• Empathy Approach: Understand why customers cancel when wait times are longer.
Riders on UberExpress tolerate waiting for reduced costs but have limits on how
much time they are willing to wait.
• Customer Personas:
o Price-Sensitive Riders: These users are willing to wait longer for a cheaper
ride but do not want significant delays.
o Pain Points: Excessive waiting and uncertainty in matching lead to
cancellations.
o Gains: Offering a balanced solution between cost and waiting time is crucial.
2. Product Vision and Roadmap (Session 3 & 4)
• Product Vision: Create an affordable, efficient shared ride option that maximizes
carpooling while maintaining a positive rider experience. Express POOL aimed to
reduce costs by increasing seat utilization, but it needed to maintain user satisfaction
by balancing wait times.
• Strategic Planning:
o OKRs:
▪ Objective: Improve profitability of shared rides while minimizing
cancellations.
▪ Key Results: Optimize waiting times, increase seat utilization, and
maintain rider satisfaction.
• KANO Model for Feature Prioritization:
o Must-Have: Quick and cost-effective matches for users willing to walk a short
distance.
o Performance Needs: Reduced cancellation rates by limiting wait times to 2
minutes.
o Excitement Features: Predictable and dynamic pricing that adjusts based on
demand and route popularity.
3. Product Discovery (Session 5 & 6)
• Discovery Process: Uber used A/B testing, surveys, and customer feedback to
validate hypotheses on wait times and rider behavior. They ran switchback
experiments in Boston to compare different wait times (2 vs. 5 minutes) and analyzed
the results to refine the service offering.
• User Research and Discovery: Surveys and focus groups were conducted to
understand rider willingness to wait for reduced fares. Empathy interviews helped
discover that many riders did not want to walk long distances in poor weather
conditions.
• Risk Factors Identified:
o Value Risk: Would the longer wait times affect the perceived value of the
lower-cost service?
o Usability Risk: Can users navigate the pick-up points easily and without
confusion?
o Feasibility Risk: Will drivers be able to manage the dynamic nature of shared
rides efficiently?
• RICE Prioritization for Features:
o Reach: Express POOL had the potential to capture a large portion of price-
sensitive users.
o Impact: A successful balance between waiting time and cost could
significantly improve profitability.
o Confidence: Moderate confidence based on pilot data and experiments.
o Effort: Moderate effort required to adjust algorithms and coordinate between
riders and drivers.
4. Customer Experience and Funnel Management (Session 8 & 9)
• User Journey Map:
o The Express POOL user journey involves several touchpoints, from app use to
pick-up and ride experience. Riders who value cost savings may be willing to
wait a little longer, but there is a threshold where waiting becomes a deal-
breaker.
o Service Blueprinting: Focus on improving the back-end matching algorithms
and the user interface to ensure that riders are well informed about the wait
and walking times.
• AARRR Funnel Analysis:
 o Acquisition: Target price-sensitive users with promotional campaigns
highlighting the savings.
o Activation: Simplify onboarding by ensuring that riders understand how
walking and waiting work in the Express POOL context.
o Retention: Encourage users to repeatedly use the service by offering loyalty
points or discounts for future rides.
o Referral: Use incentives to get satisfied riders to refer others, especially in
busy urban areas where price-sensitive travelers are abundant.
o Revenue: Dynamic pricing, coupled with better seat utilization, could increase
profitability while ensuring low costs for riders.
5. Solution Design and Execution
• JTBD Framework: The Jobs-to-be-Done (JTBD) framework helped Uber identify that
price-sensitive riders wanted an efficient, cost-effective, and reliable service. Key user
needs included clear instructions, shorter wait times, and consistent pricing.
o Information: Riders needed transparency on waiting times and the exact
location of the pick-up points.
o Flexibility: Offering a 2-minute waiting time made the service more attractive
and prevented cancellations.
o Cost Effectiveness: By keeping prices 20% lower than UberPOOL, the service
became a valuable option for budget-conscious users.
• Product Roadmap: Uber used A/B testing and continuous data collection to iterate
on the Express POOL product. After refining the matching algorithm and adjusting
waiting times, the roadmap included a wider rollout of the product in new markets.
• Scrum Implementation: Uber’s development of Express POOL followed agile
methodology, with engineers and product managers collaborating to build and
iterate the feature through regular sprint reviews and updates.
6. Monitoring and Optimization
• A/B Testing: The product was launched in selected cities (Boston and San Francisco)
using a synthetic control experiment. Uber compared the performance of Express
POOL with its control cities to measure the impact of waiting times on cancellation
rates and overall profitability.
• Data Analysis: The team continuously monitored key metrics, such as seat utilization,
ride completions, and customer satisfaction. Adjustments to the algorithm were
made in response to rider behavior and feedback.
• Iteration: The synthetic control experiment helped the team determine optimal wait
times and pricing strategies, leading to further refinements before a larger-scale
 rollout. Continuous monitoring ensured that the product evolved based on real-time
data.
Conclusion
The Express POOL initiative exemplifies how Uber applied product management principles to
balance cost efficiency with user satisfaction. By understanding user needs through
empathy, conducting extensive testing, and iterating on their findings, Uber was able to
improve shared ride services without sacrificing rider experience. Continuous data analysis
and funnel management ensured that Express POOL was positioned to grow sustainably
across various markets.
DIvami Labs

Detailed Case Analysis of Divami Design Labs: Applying Product Management Principles

1. Problem Identification and Empathy (Session 1 & 2)

• Key Issues Identified: Divami faced resistance from Paysoft's internal team, especially
from Gupta, who was unhappy about outsourcing the redesign of a product his team
had developed. The project required addressing Paysoft’s challenges with user
experience and slow adoption of the new digital platform.
• Empathy Approach: To succeed, Divami needed to empathize with both Paysoft’s
internal team and end users. Gupta’s concerns stemmed from a fear of losing control
over the product, while end users struggled with a cumbersome interface.
• Customer Personas:
o Internal Stakeholders: Gupta and his team, who needed reassurance that the
design process was collaborative.
o End Users: Employees who found the Paysoft platform challenging to
navigate, particularly with slow load times and complex workflows.
o Pain Points: Confusing interface, slow response time, lack of intuitive design.
o Gains: Creating a user-friendly, responsive product would lead to greater user
satisfaction and adoption.
2. Product Vision and Roadmap (Session 3 & 4)
• Product Vision: Redesign Paysoft’s employee life cycle management software with a
user-centric focus. By improving user experience (UX) and user interface (UI), the
product would become more intuitive and efficient, improving satisfaction and
reducing churn.
• Strategic Planning:
o OKRs:
▪ Objective: Improve user satisfaction by addressing pain points in the
interface and increasing platform adoption.
▪ Key Results: Achieve a measurable increase in user satisfaction and
platform usage within six months.
• KANO Model for Feature Prioritization:
o Must-Have: Easy-to-use interface with quick load times and simple
navigation.
o Performance Needs: Streamlined self-service modules for users, including
document uploads and expense reports.
 o Excitement Features: Integration with third-party applications and inbuilt
assistants for smoother workflows.
3. Product Discovery (Session 5 & 6)
• Discovery Process: The team needed to validate their design ideas by conducting
user research, empathy interviews, and usability testing. The initial feedback from
Paysoft users revealed frustration with the complexity of the interface and lack of
mobile responsiveness.
• User Research and Discovery: Divami engaged with key stakeholders and end users
through customer journey mapping, shadowing, and interviews to identify pain
points.
• Risk Factors Identified:
o Value Risk: Will the redesigned product deliver enough value to satisfy both
internal and external stakeholders?
o Usability Risk: Can the redesigned product ensure ease of use for a diverse
group of users with varying technical proficiency?
o Feasibility Risk: Is it technically feasible to integrate third-party apps and
advanced features within the budget and timeline?
• RICE Prioritization for Features:
o Reach: The improved UI/UX would impact thousands of users in India and
South Asia.
o Impact: A better user interface would significantly reduce churn and improve
user satisfaction.
o Confidence: High confidence, as user feedback strongly indicated a need for
change.
o Effort: Moderate effort required for redesigning the interface and improving
backend systems.
4. Customer Experience and Funnel Management (Session 8 & 9)
• User Journey Map:
o The user journey focused on improving the experience at critical touchpoints:
onboarding, payroll, and expense management. Users needed a streamlined,
mobile-friendly experience that was responsive and intuitive.
o Service Blueprinting: Divami needed to address both the front-end UX and
back-end processes to ensure that the platform was not only visually
appealing but also technically efficient.
• AARRR Funnel Analysis:
 o Acquisition: Focus on marketing the redesigned platform to both existing
clients and new prospects, emphasizing user-friendliness and advanced
features.
o Activation: Simplify onboarding and provide clear instructions and tutorials to
help users understand new features.
o Retention: Encourage users to continue using the platform through features
like personalized dashboards and loyalty programs.
o Referral: Promote word-of-mouth through satisfied users, especially by
targeting CIOs and HR teams who could act as advocates for the new system.
o Revenue: The new design would attract more clients, especially medium-
sized enterprises, increasing overall revenue for Paysoft.
5. Solution Design and Execution
• JTBD Framework: The Jobs-to-be-Done (JTBD) framework was essential for
understanding the needs of Paysoft’s end users. The product needed to solve key
user tasks, such as easy document upload, managing payroll efficiently, and
generating reports.
o Information: Users needed clear, concise instructions, easily accessible
through mobile or web platforms.
o Flexibility: A modular design that allowed users to customize their experience
according to their specific role.
o Cost Effectiveness: The new design had to justify its investment by reducing
support costs through improved usability and fewer user complaints.
• Product Roadmap: Divami employed design thinking, starting with low-fidelity
prototypes and gradually refining them based on user feedback. This iterative
approach ensured that the final product met both user and business needs.
• Scrum Implementation: Divami used agile methodology to develop the redesign,
working closely with Paysoft in iterative sprints, with constant feedback loops from
both end users and Paysoft’s internal team.
6. Monitoring and Optimization
• A/B Testing: Prototypes were tested with small user groups to identify potential
issues and gather feedback. Divami used iterative testing to fine-tune both UI and UX
elements, ensuring maximum usability.
• Data Analysis: User interaction data was continuously monitored to assess the
success of the redesign. Metrics such as user satisfaction scores, task completion
times, and feedback on ease of use were critical in evaluating the effectiveness of the
new design.
 • Iteration: Based on the feedback from testing, Divami refined the product further
before its final launch. Continuous improvement was emphasized as the product
evolved, ensuring that it adapted to changing user needs and industry trends.
Conclusion
Divami’s engagement with Paysoft demonstrated how a user-centric design approach could
address key pain points in a complex software product. By applying empathy, iterative
testing, and a focus on both UX and UI, Divami was able to redesign Paysoft’s platform to
improve user satisfaction and retention. The case illustrates the importance of collaboration
between design teams and internal stakeholders, as well as the value of continuous
improvement in product development.