Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(9)

Customer Journey(17)

Design(45)

Solar Industry(8)

User Experience(68)

Edtech(10)

Events(34)

HR Tech(3)

Interviews(10)

Life@mantra(11)

Logistics(5)

Manufacturing(1)

Strategy(18)

Testing(9)

Android(48)

Backend(32)

Dev Ops(11)

Enterprise Solution(31)

Technology Modernization(8)

Frontend(29)

iOS(43)

Javascript(15)

AI in Insurance(38)

Insurtech(66)

Product Innovation(58)

Solutions(22)

E-health(12)

HealthTech(24)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(149)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(23)

FinTech(51)

Banking(7)

Intelligent Automation(27)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

Improving CX for Shared Mobility Services in India

Shared mobility is an umbrella term for companies that enable individuals to access a vehicle as and when they require it.

Shared mobility services like Uber and Ola ushered in a new era of public transportation, which needed to be more active with the use of autos, buses, and metros in urban areas. Dealing with a heavily unionized industry, these companies helped open the ride-sharing provider market.

Before the pandemic, these companies saw enormous markets for their services. However, things hit a slump during 2020, with the back-to-back lockdowns in India and public concerns around health and hygiene. 

Most of these companies offered carpooling services, such as Ola Share or Uber Pool, discontinued due to changing consumer behavior.

As we look at revitalizing the sector post-pandemic, there is a need for improved customer experience (CX) to ensure sales hit higher levels than in the pre-2019 era. This article explores the challenges of CX for shared mobility services in India and potential solutions for improvement through digital initiatives.

Understanding Shared Mobility in an Indian Context

Shared mobility services include ride-hailing, bike-sharing, car-sharing, and other shared mobility services which typically rely on technology, such as digital platforms, to connect users and provide vehicle access. Some examples of shared mobility services are:

E-hailing: A service that allows users to book a ride with a driver using an app or website. The ride can be private or shared with other passengers. Examples: Uber, Ola, BluSmart, etc.

Car sharing: A service that allows users to rent a car for a short time, usually by the hour or day. Users can pick up and drop off the vehicle at designated locations or anywhere within a specific area. Examples: Zipcar, Zoom Car, Revv, etc.

Bike and scooter sharing: A service that allows users to rent a bike or scooter for a short time, usually by the minute or hour. Examples: Bounce, Yulu, Lime, Bird, etc.

Carpooling and ride-sharing: A service allowing users to share a ride with other users traveling the same route. Users can arrange the ride in advance or on demand. Examples: Blablacar, Quick Ride, Waze Carpool, etc.

How do these services benefit the customer?

In several ways, shared mobility services benefit the end users in India. Be it reducing traffic congestion and pollution by decreasing the number of private vehicles on the road. Providing affordable and convenient transportation options for urban commuters who do not own a vehicle or cannot afford other modes of transport. 

And enhancing accessibility and connectivity for rural areas and underserved regions that lack adequate public transport infrastructure or services, which could be highlighted as some of the key benefits. 

What are the concerns plaguing consumers today?

  • Safety and hygiene: India’s shared mobility services face challenges in ensuring the safety and hygiene of vehicles and drivers, especially during the COVID-19 pandemic. This raises user concerns about the risk of infection, theft, harassment, or accidents.
  • Data and technology: India’s shared mobility services rely on data and technology to provide efficient and seamless user services. However, there are challenges in collecting, analyzing, and sharing data across different platforms and stakeholders. There are also issues of data privacy, security, and quality.
  • Cost efficiency: Rising input costs and attempts from service providers to jack up prices through cases like surge pricing, night charges, etc., add to the overall costs that trickle down to the end consumers.

Mantra Labs recently surveyed whether consumers would want to use carpooling services such as Uber Pool and Ola, where 60% of respondents replied with a firm YES. 

  • Poor customer service: In India, the reliability of such transportation options could be better. Customers often deal with long waiting periods, last-minute cancellations, poor driver behavior, and inefficient customer complaints management.

Improving customer service through CX solutions

  • Education and Awareness

Education and awareness initiatives are needed to improve the customer experience for shared mobility services in India. These initiatives should emphasize the importance of safe, reliable, and efficient transportation services and the need to adhere to safety regulations.

Options to provide your tracking details to another mobile number, immediate notification if the driver deviates from a marked route, road safety assistance in case of an accident or encounter, etc., should be provided and highlighted upfront on the mobile app.

Through these initiatives, stakeholders will be able to use the services in a comfortable and mentally peaceful manner, likely improving both the usage and the experience.

Mantra Labs helped build the mobile app for India’s #1 shared mobility services provider from scratch. Discover how we created a seamless platform that works at scale.

  • Lower Prices

Most ride-sharing apps provide promotional codes, discounts through third-party apps, or even weekly/monthly passes to help combat high prices and surge pricing. However, users must be aware of these benefits and avoid a high price barrier.

Microsoft Edge provides a pop-up when a user is at the payment stage of their cart for any shopping website – with information on the discount coupons available. Having a similar setup while a user completes payment will ensure that consumers can utilize the benefits.

  • Loyalty Programmes 

Cashback and loyalty points are also efficient ways to reduce a consumer’s financial burden. They are improving customer retention and boosting customer satisfaction. Companies can use gamification tools to improve user engagement and the time consumers spend on their apps. 

Mantra Labs created a rewards program for Myntra’s End of Reason Sale, which allowed users to collect coins and rewards redeemable during their purchases. Similarly, offering premium services such as free upgrades, in-transit entertainment, and partner offers as rewards would increase user stickiness. 

Conclusion

Shared mobility services have great potential to reduce congestion, air pollution and increase connectivity in India. However, there are still many improvements in customer experience to ensure these services are utilized to their full potential. By implementing lower prices, pop-up notifications, cashback, and loyalty points, these services can become more accessible and attractive to consumers. These changes will improve customer experience and make shared mobility services a viable option for many people.

Cancel

Knowledge thats worth delivered in your inbox

Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot