Early stage product building
Laying the groundwork: 0→1 projects that became full-fledged team charters
A summary of key projects I initiated and led as an individual contributor and early design manager. These were built from scratch—often in challenging, fast-paced environments—and laid the foundation for what would later become full-fledged charters managed by new teams as the organization scaled. My work not only shaped the initial vision and execution but also set up these initiatives for long-term growth and impact.
Build a 0-1 app for restaurant partners to get insights and feedback for outlets
Time frame
Jun 2017 - Sep 2017
Business need
Currently, restaurants use a vendor app to manage orders, menus, and other tasks. They also need insights on how their outlet(s) are performing and areas to improve, so they can use this data to grow and improve their service
Goal
Build a 0-1 restaurant owner app that gives owners or managers performance metrics, customer feedback, and ratings on Swiggy. Over time, it will offer tips and nudges to help them grow at scale.
Key constraints
No prior data available except from vendor app
Hire external engineering bandwidth only
Design direction
1️⃣ Owner personas & owner app usage
Based on my conversations with the supply team, there are 4 distinct personas I need to build for. The app i build would come in handy when they are trying to analyze their outlet performance and find opportunities to grow.
Personas for the owner app
Stages of growth for restaurant
2️⃣ Build, test and iterate
I collaborated with my Product manager to define the high level information architecture, using the vendor data already existing. We decided to include 3 kinds of metrics in the MVP - Performance, Customer and Operation
I created prototypes of the screens with these metrics and did two rounds of user testing with restaurant owners from the four personas we identified.
3️⃣ Finalize v1 designs and ship
We included feedback from internal discussions and the insights from the immersion with 11 restaurants. We finalized the designs and handed them off to the React Native freelance developer.
Key design fows for owner app MVP
Launch and impact
The project took 1.5 months of design and 2.5 months of development. It launched on iOS in six cities on September 18, 2017, and was later scaled to Android and the rest of India in February 2018.
830+ iOS users
from 6 cities in first launch
5.4K+ total users
after Android rollout
2.2K owners acted
on ratings & performance
12:34:54
Gold : Silver : Bronze tier
What next?
I handed over the owner app framework to a newly formed Supply design team of four members, who expanded it with more features for owners and optimized it for franchises and national chains. After this, I went on to build more 0–1 products, eventually becoming the leader of the New Initiatives charter for B2C experiences.
Scale delivery partner app from food orders to multiple order types
Time frame
May 2018 - Oct 2018
Business need
In early 2018, Swiggy decided to go beyond food delivery by launching Swiggy Stores (groceries) and Swiggy Go (pickup and drop services). This meant delivery partners would also start handling non-food orders in the future.
Goal
Understand the current delivery app and its pain points. Help the delivery app designer create a new, scalable “Super Delivery app” that can support any future Swiggy service.
Key constraints
Working on this in parallel with consumer projects
Tight timelines and no prior domain knowledge
Design direction
While juggling work on Stores consumer app and two other projects, I had to quickly get familiar with the delivery partner domain to be able to drive design decisions. I managed the sole designer working on the delivery platform, working closely with him to understand the delivery ecosystem, pain points, and moving parts he had already mapped out.
1️⃣ Grasping the entire delivery ecosystem
I asked the designer to print out all the screens from the current delivery partner app and put them on the wall. We went through the entire flow step by step in detail, and also made notes on gaps to fix and ways to improve in the future.
Existing delivery app flows shared by delivery designer
I also spent a full day shadowing a senior delivery partner, observing his entire routine—from the fleet manager’s office to restaurants, customer drop-offs, and even socializing with other delivery partners. It gave me new insights into how they do their job and what they need from Swiggy to be satisfied with their day.
Some pictures from my shadowing exercise
2️⃣ Extract key insights and define design principles
Unlike consumer apps that shape user behavior, the new delivery app needed to fit into the daily habits of delivery partners—used almost unconsciously as part of their routine. Here, humans shape the app’s behavior, not the other way around.
3️⃣ Finalize designs and visual language
I wanted the delivery partner app to feel not just functional, but welcoming and transparent. To bring this vision to life, I secured a budget to hire a visual designer who could help refine the flows and create an experience on par with consumer apps, while still keeping it highly functional
Manager (Me)
Create a scalable framework that meets both current needs and future scenarios.
Product designer
Use his domain expertise to apply framework to all end-to-end flows and do rigorous user testing
Visual designer
Churn out the visual language and bring emotion to designs, assist in some UX flows.
Super App in action
Food order
Stores order
Go order
Launch and impact
After a month of controlled releases, feedback enhancements and iterations with select delivery partners, the Delivery partner super app was rolled out in Dec 2018 to all cities to unlock Stores and Go delivery for customers.
Below are the numbers of the initial launch for 3 months:
5K+ delivery partners
on the new app
14% reduction
in delivery partner issues
5% less dropoffs
updates on battery life & order zones
73 NPS score
after 3 months of launch
What early adopters say
Issues encountered with Super App
Delivery partners found Stores orders challenging since they had to shop for items themselves instead of just picking up ready-made packages. To address this, we set up extra training and chose only experienced partners to handle these orders first.
What next?
We brought on a design manager to lead the Delivery team as I transitioned to the New Initiatives consumer charter full time. The framework I created is still in use; 2 years later, the 4-member design team has adapted the UI to better match Swiggy’s DLS and look more cohesive with our other products.
Automate help center flows to reduce agent intervention for issues
Time frame
Sep 2017 - Dec 2017
Business need
In 2017, Swiggy’s help center was generic and didn’t offer contextual resolutions like real-time order status. As a result, customers had to contact agents even for minor issues, driving up costs and hurting Swiggy’s efficiency.
Goal
Identify gaps in the help and support experience to offer contextual assistance for customers’ queries. Build a chatbot experience for the most common issues, reducing agent interventions and speeding up resolution.
Success metrics
Average resolution time (in mins)
Reduction in cost per call with automation
Design direction
1️⃣ Identify gaps & opportunities for automation
I teamed up with the product manager to gather data and insights from the customer care team, and I also did a usability study of the current help center.
2️⃣ Map customer chat flows & craft response copies
I worked with the product manager to map out flows for every issue, reviewing and refining them carefully. The product manager shared all decision tree flows in LucidChart. We also crafted chatbot copy to make interactions feel more natural and human, and kept iterating on it with feedback from the head of customer care team.
A preview of decision tree on LucidChart, to map out chatbot flows
3️⃣ Design clear entry points & easy-to-follow chats
A key design intervention was to make help easier to find across all touchpoints, so users wouldn’t waste time searching for it. I also solved for in-app and push notifications to alert users to new chat replies
4️⃣ Flesh out all final flows with copies
I made flows for the most frequently raised issues which could be resolved automatically without requiring agent interviews. I converted these into prototypes and shared with engineering for implementation
Order cancellation
Missing items in order
Packaging issues
Launch and impact
The improved help center experience was launched to 10% users on Dec 30, 2017 and later scaled up to 100% on Feb 16, 2018.
50% less issues
handled by agents
83% bot cancellation
in first 30 secs
6 min → 1.3s
average time to resolve issues
Rs 2.8 → Rs 2.1
cost of calls per order
What next?
The help center framework is built to scale to any context and handle different types of issues. It’s been adopted by multiple teams and adapted for needs across restaurant partners, delivery partners, Instamart, Genie, and Dineout.
Key takeaways
I feel fortunate to have architected and launched 0–1 products from scratch that remain relevant today. Seeing these products grow and evolve under full-fledged teams year after year is incredibly rewarding. It makes me proud of my ability to design frameworks that stand the test of time.
