Zeelab Pharmacy is India's direct-to-consumer generic medicine platform. Founded by Rohit Mukul in 2019, the company has been partnering with 200+ pharmacies nationwide. Zeelab provides WHO-approved medications from GMP-certified plants at up to 90% lower than branded alternatives. No retail overhead. No brand markups. Just accessible healthcare.
But behind the strong value proposition was a broken ordering process. Every order meant phone calls, manual prescription collection, and address coordination - handled entirely by a small team that couldn't keep up.
The Challenge
Manual Processes That Couldn't Scale
For a pharmacy trying to scale, this was the ceiling. Every single order depended on a human being available, at the right time, with the right information, and ready to coordinate across multiple steps. Here's what that looked like:
Customer calls
or messages
Team responds
(if available)
Back-and-forth for medicine names, quantities, prescriptions
Manual address collection
Cart prep
Payment coordination
Manual tracking updates.
Customer journey experience before the implementation of chatbot automation
The Breaking Point: Every new customer added to the workload. The team was turning away orders they simply didn't have the bandwidth to handle. Growth was costing more than it was making.
THE MANUAL BOTTLENECK
Availability Gap
No after-hours service meant lost night orders
Language Barrier
English-only
excluded Hindi speakers
Inconsistent Experience
Returning
customers
repeated same info
Zero Cart Recovery
No systematic
follow-up for incomplete orders
Team Capacity Ceiling
More customers = More manual wor
Our Approach
What We Set Out To Do
Build a WhatsApp automation system that:
Eliminates manual order-taking while maintaining service quality
Creates separate optimized paths for new vs. returning customers
Operates 24/7 without requiring 24/7 staffing
Supports bilingual conversations with instant English ↔ Hindi switching
Recovers abandoned carts automatically without being pushy
Integrates seamlessly with Zeelab's existing backend systems
The goal wasn't just automation, it was creating an ordering experience that felt better than talking to a person, because it never forgot your preferences and was always available.
"
"We knew customers were dropping off. What we didn't know was how to stop it without adding more manual work to an already stretched team. The Flip Funnel team dug into where the breakdowns were happening before proposing anything."
Amit Mandal | Head of E-commerce
Zeelab Pharmacy
The Strategic Insight: Two Customer Types Need Two Different Journeys
The Key Insight: Recognize Customer
State, Don't Ask For It
The Solution
Project Timeline
Phase 1: Understanding The Process and Users
New customers needed step-by-step guidance
Returning customers wanted shortcuts remembering previous orders
Both needed transparency about next steps
Language mismatch between customer and system led to drop-offs
"
“What stood out was that they kept coming back to us at every step. We'd share how our customers actually behave, and they'd rethink the flow. By the time we saw the final system, it felt like something we had built together instead of something that was installed on us."
Vivek Khambra | Head of Product
Zeelab Pharmacy
Phase 2: Mapping Complete Order Journeys
We created parallel flows optimized for each customer type:
New Customer Path
Welcome & Language
Upload Prescription
Add Items
Enter Address
Verify Address
Cart Preparation
Review Cart
Select Payment
Track Order
9 Steps
Returning Customer Path
Welcome Back
Last Order
Repeat Order?
Same Address?
Skip to Cart
Cart Preparation
Review Cart
Select Payment
Track Order
5 Steps
Yes/No
New customers could go from first message to confirmed order without a single phone call.
Returning customers could now skip 4 steps by confirming instead of re-entering data.
"Two types of customers. One system smart enough to tell them apart."
Phase 3: Creating Conversational Messaging
Every message needed to feel personal, not robotic. We wrote English and Hindi versions for every interaction.
Example contrast:
Generic chatbot: "Please provide the medicine name"
Our approach: "Let's get your medicines sorted! You can share your prescription image, or just tell me the medicine names, whichever works for you."
We built a main menu accessible anytime by typing anything:
Main menu of the chat in two different languages allowed customers to choose as per their preference
Customers felt trapped in linear flows. Having a menu, gave them control and clear next steps with ease.
Phase 4: Building The Automation in WATI
We built the system with six core capabilities:
We used WATI's drag-and-drop chatbot builder to bring the journeys to life. The system used six node types working together:
These components orchestrated data collection, routing decisions, and backend coordination—all invisible to customers who just experienced a helpful conversation.
Send Message
Attribute Update
Set Condition
Assign Team
Free Source API
Webhook
Deliver prompts at each step
Save customer info for
future orders
Route New vs. Returning
Send order details to Zeelab's backend, pull cart pricing
Transfer complex cases
to human pharmacists
when needed
Push real-time
status
Flow of the chat created using WATI's drag-and-drop builder
Critical Features
1. Post-Order Flexibility
Three capabilities after placing orders:
Modify: Add medicines, update quantities, upload prescriptions, correct addresses before payment
Track: Automatic status updates (Confirmed → Packed → Out for Delivery → Delivered)
Cancel: One-tap cancellation with instant team alerts
2. Smart Cart Recovery
The system monitors conversation activity. After 15 minutes of inactivity:
"Hey! It's been a while since we heard from you. This chat will close soon, but you can quickly reply or pick an option above to continue without losing progress."
The system preserves the entire conversation state, customers continue exactly where they left off. No re-entering information.
One gentle nudge, then stop.
3. Language Flexibility
Customers can start in English, switch to Hindi mid-order, or switch back to English or previously selected language again. The system maintains context regardless of language.
Not just translation, the conversation flow adapts naturally to the language they're comfortable with.
The Outcome
A rule-based WhatsApp chatbot that handles complete medicine ordering journeys, from initial inquiry to delivery tracking with zero manual intervention for routine orders.
Unlike AI agents that improvise, we built predefined workflows designed specifically for Zeelab's operations. Think of it as codifying the pharmacy team's knowledge into automated conversation paths that maintain service quality while eliminating manual repetition.
What made it different:
Two optimized customer journeys (New vs. Returning) instead of one generic flow
Bilingual support with instant switching, not just translation
Smart cart recovery that nudges once without nagging
Post-order actions (Modify, Track, Cancel) built into the same conversation thread
Seamless backend integration for real-time cart pricing and order status updates
What Actually Changed For Zeelab
Both types of customers got better experience
New customers get guided clarity. Returning customers finish in under 2 minutes. Both can ask questions, modify orders, track delivery, one thread.
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