INTERSTATE DAIRY APP

Enabling Interstate Dairy Buyers to Trust and Buy Online

COMPANY

Animall

ROLE

Product Designer

EXPERTISE

Research · Strategy · UI Design · Testing

YEAR

2020

INTERSTATE DAIRY APP

Enabling Interstate Dairy Buyers to Trust and Buy Online

COMPANY

Animall

ROLE

Product Designer

EXPERTISE

Research · Strategy · UI Design · Testing

YEAR

2020

Project description

Animall wanted to increase online sales of high-quality Murrah buffaloes by targeting a high-value but reluctant audience: interstate dairy farm owners. These buyers, though purchasing 12–30 cattle annually, avoided the app due to poor trust, lack of personal touch, and an offline-first mindset.

Project description

Animall wanted to increase online sales of high-quality Murrah buffaloes by targeting a high-value but reluctant audience: interstate dairy farm owners. These buyers, though purchasing 12–30 cattle annually, avoided the app due to poor trust, lack of personal touch, and an offline-first mindset.

Key Challenge:
How might we help these high-value buyers feel confident enough to complete purchases through the app?

🎯 Goals

  • Build trust through clear verification

  • Help users assess cattle as they do offline

  • Reduce decision fatigue caused by volume

  • Align experience with behavioral cues like video and WhatsApp

  • Improve conversion and perceived credibility

Project description

Animall wanted to increase online sales of high-quality Murrah buffaloes by targeting a high-value but reluctant audience: interstate dairy farm owners. These buyers, though purchasing 12–30 cattle annually, avoided the app due to poor trust, lack of personal touch, and an offline-first mindset.

Key Challenge:
How might we help these high-value buyers feel confident enough to complete purchases through the app?

🎯 Goals

  • Build trust through clear verification

  • Help users assess cattle as they do offline

  • Reduce decision fatigue caused by volume

  • Align experience with behavioral cues like video and WhatsApp

  • Improve conversion and perceived credibility

Research

Research

🔹 Buyer Interviews

We interviewed 10+ professional dairy farmers across states who previously purchased offline or via brokers. Key insights:

🕵🏻 Observation

⚛️ Why It Matters

Users don't trust seller uploaded data

They rely on physical cues, not just specs

Milking and walking videos are key decision makers

Video reveals gait, udder structure, and milk flow

Listings feel unverified and random

Users need assurance before engaging

PDF's prefer buying in bulk

App lacked this behavioural alignment

WhatsApp is their current platform

They're used to human-led video sharing & negotiation


🧠 Behavioral Patterns

There are multiple steps which enables a user to take an informed decision.

  • 🥛 Users watch morning and evening milking for two consecutive days.

  • 🐮 Look for calving history, age, height, horn, nails, gait and udder to gauge an animal

  • ☎️ Prefer calling a trusted merchant or seller contact

  • 🚚 Rely on reputation and delivery reliability


🐄 Key Needs Identified

Need

Why It Matters

Verified cattle

Eliminates fraud and doubt

Bulk-friendly pricing

Aligns with real world buying behavior

Fast decisions

Time sensitive purchases

Simple interface

Low digital literacy

Solution

✍ Design Process

We focused on designing an experience that reflects how users actually buy cattle; not how traditional e-commerce works.

Key Decisions:

  • Show fewer, high quality listings instead of a number of inconsistent listings

  • Mirror real-life decision sequence: see > verify > shortlist > talk

  • Push offline tasks like delivery and grievances outside MVP scope

♟ Design Strategy

Based on user research, we realigned the product with the users's mental models and reduced friction:

📽 Video-First Listings

All animals were presented with verified, consistent-format videos showing:

  • Walking posture

  • Udder position

  • Milk yield context

  • Overall build

✅ Verified by Animall ("Pramanit")

A new “Pramanit” tag was introduced to indicate that a listing was authenticated by Animall’s field team or partner farm. It appeared at the start of each video, not buried in metadata.

🕉 Language Localization

The product supported 4 regional languages, ensuring comprehension of every label, action, and filter.

✍ Design Process

We focused on designing an experience that reflects how users actually buy cattle; not how traditional e-commerce works.

Key Decisions:

  • Show fewer, high quality listings instead of a number of inconsistent listings

  • Mirror real-life decision sequence: see > verify > shortlist > talk

  • Push offline tasks like delivery and grievances outside MVP scope

♟ Design Strategy

Based on user research, we realigned the product with the users's mental models and reduced friction:

📽 Video-First Listings

All animals were presented with verified, consistent-format videos showing:

  • Walking posture

  • Udder position

  • Milk yield context

  • Overall build

✅ Verified by Animall ("Pramanit")

A new “Pramanit” tag was introduced to indicate that a listing was authenticated by Animall’s field team or partner farm. It appeared at the start of each video, not buried in metadata.

🕉 Language Localization

The product supported 4 regional languages, ensuring comprehension of every label, action, and filter.

Video first listing

Video first listing

Nudge for next video

Options for video listing

Detail page

Usability testing

🎯 Goals

  • Can users complete key tasks on their own?

  • Do they understand verification and cattle info?

  • Can they find "their type" of animal easily?

👤 Participants

  • 10 dairy farm buyers from Maharashtra and Haryana

  • Screened for past Animall or broker assisted purchases

📊 Key Results

Task

Success Rate

Notes

Understood concept of online Murrah buying

100%

Clearly communicated on splash & homepage

Navigated swipe-up reel interface

85%

Resembled YouTube Shorts & Instagram Reels

Understood “Pramanit” stamp

0%

Users didn’t get it — redesigned using a blue stamp + tooltip

Liked marks better than stars

100%

Users didn’t relate to stars, understood "10/10" marks immediately

Able to view full cattle info

100%

Preferred when everything was in one scroll

Final Design

✅ Listing Screen

  • Reels-style interaction

  • One-click “Book this animal”

  • Verified stamp, simplified UI, rating via marks

✅ Details Page

  • All videos grouped at top

  • Structured, scrollable data with icons and supporting visuals

  • Calving history, age, height, and milk production shown transparently

Full app experience

Full app experience

Full app experience

Before

Before

Before

After

After

After

Redesigned video listing page

Redesigned video listing page

Feedback screen

Feedback screen

Redesigned nudge

Redesigned nudge

Redesigned details page

Redesigned details page

Impact and Learnings

Within just 3 months of launching the redesigned flow for verified, video-first listings:

  • 💰 Generated ₹38 lakh in revenue, validating trust-based, video-first listings among interstate buyers.

  • 🚀 Estimated 20–25% uplift in buyer conversions from targeted PDF/MDF segment

  • 🐄 Buyers made faster decisions, with fewer drop-offs post-listing

  • 🧠 100% of tested users trusted video-first listings and marks over previous formats

  • 🔁 Reduced dependency on brokers; More margin retained in-platform

This validated not just the UX direction but also Animall’s ability to digitize high-trust, high-value cattle sales at scale.

🧠 Reflection

This project reminded me that design must mirror behavior, not force patterns. Interstate dairy farmers didn’t need "fancy UX" — they needed clarity, familiarity, and trust.

What I learned:

  • Language and culture shape trust — visuals must adapt

  • Verification needs active, in-your-face presence, not passive tags

  • What we consider “standard UI” (like stars) can confuse non-digital-native users


5% reduction

in overall churn rate in Rajasthan.

10% increase

in seller posts over a period of 1 week

13% fewer

Onboarding support queries

~6-8% increase

in granting locationpermissions