5 MIN READ

AgriTech & Accessibility

Fasal support system

Redesigned the Help Section with voice-first ticketing and a simplified 3-step flow, dropping literacy as a prerequisite for getting help.

Problem & Solution

Problem Statement: Farmers using the Fasal App struggle to effectively report issues due to a complex, text-based help system that doesn't account for language barriers or limited literacy, leaving farmers without help and the support team with incomplete information. How Might We Statement: How might we make it as easy for a farmer to report a problem as it is to make a phone call, regardless of their language or literacy level?

Impact

To bridge literacy gaps, I redesigned the Help Section with a simplified 3-step flow and Audio Ticketing. This accessibility pivot drove a 107.6% surge in support requests, with 34% of users switching to voice reporting, proving that removing language barriers is what unlocks participation.

Focus Areas

Operational EfficiencySupport AutomationService DesignCost Reduction

Tools Used

FigmaGoogle SheetsGoogle DocsUseberry

About Fasal App

Fasal leverages on-farm IoT sensors and AI to transform real-time data into actionable, vernacular insights. By guiding farmers on precise irrigation and pest management, the app empowers them to optimize crop conditions and maximize productivity through data-driven decisions.

01Introduction

Three barriers were blocking farmers from getting help: a 5-step reporting process most didn't finish, a help button buried in settings, and a text-only system that excluded anyone who didn't type fluently. This is what we set out to fix.

The Pivot

Audio First

Redesigned the help architecture to prioritize voice reporting and simplified status tracking for a 100% resolution success rate.

The Goal

Scale Support

Enable 50k+ farmers to self-diagnose hardware issues while streamlining agent workflows for complex inquiries.

The Friction

Support Overload

Legacy text-only help system failed to account for language barriers and varying literacy levels, causing user frustration.

The Limit

Constraints

The ideal solution would be to provide an upfront calling option; however, operational limitations prevented implementation.

02Current flow and issues

CLICK TO VIEW

Current 5-step help reporting flow

01
Too many steps: The 5-step process loses most farmers before they finish. Problems go unresolved, trust erodes.
02
Hard to find help: The report button is buried inside the help section, not visible until farmers already know where to look.
03
Mismatched problem categories: The preset list doesn't reflect what farmers actually experience, forcing them to pick the closest wrong answer.
04
Writing is a barrier: Farmers with low literacy or no keyboard proficiency can't explain their problems in text.
05
No multilingual support: The system only works in languages farmers can type, which excludes most of them. Issues get misreported, or not reported at all.
06
Overloaded support team: Unclear written tickets mean agents spend extra time diagnosing issues, slowing resolution and reducing satisfaction on both sides.

03Design Process

DISCOVERY

Field Visit & Define

Interviewed farmers & stakeholders to map pain points in the legacy help section.

STRATEGY

Ideate & Design

Brainstormed solutions and presented viable prototypes to Head of Product.

EXECUTION

Prototyping & Testing

Built high-fidelity interactive flows and conducted Useberry usability tests.

REFINEMENT

Feedback Implementation

Iterated on prototypes based on direct farmer interactions and data analysis.

04Field Discovery

We started inside, interviewing the sales and customer success teams to understand the support team's perspective. Then we went to the farms to see the problems firsthand.

Internal Narrative

Stakeholder Feedback

CSE

Both teams emphasized the need for a more user-friendly help system that caters to farmers' preferences and limitations.

SALE

The importance of voice-based communication was consistently highlighted across both teams.

CSE

Language and literacy barriers were identified as significant obstacles in the current text-based help system.

SALE

Both teams agreed that improving the help section could lead to more efficient problem resolution and increased user satisfaction.

Field Insights

Farmer Voice

"Mujhe pata hi nahi hai ki kahan se complaint karte hain, kabhi check nahi kiya."

I have no idea how to raise a complaint in the app. I've never checked.

"Mujhe keyboard se type karne mein problem hai. WhatsApp mein bhi sirf audio message bhejta hoon, text message sirf padhta hoon."

I have difficulty typing on the keyboard. Even on WhatsApp, I only send audio messages and just read text messages.

"Mujhe di hui categories mein mera issue nahi milta jo main face kar raha hoon."

I can't find my issue in the given categories in the help section.

"Sales wale bande ko call karna mere liye easy hai."

It's easier for me to call the sales person. I can just pick up my phone and call them.

App Submissions

42%

Only 42% of tickets were raised via the app; the majority remained offline or via direct calls.

Abandonment Rate

22.5%

Users abandoned the ticket-raising process mid-way, highlighting high cognitive friction.

05Ideation & Goals

Farm visits confirmed what the support data suggested: farmers were abandoning the help flow before it could help them. These sessions shaped our design goals directly.

01
Work for farmers regardless of literacy, voice-first, not text-first.
02
Surface help with one tap, not buried two levels deep.
03
Improve ticket quality so the support team can resolve issues faster.
04
It should look and feel consistent with the rest of the app.

06Design exploration & finalization

We built on the discovery with a clear question: should Help live separately from Articles, or on the same page? We designed one option for each to put it to the test.

Design Options

01 / 02

CLICK TO EXPAND

Design Option 1

01Separated the Help CTA from articles and made it impossible to miss.
02Reduced the number of steps from 5 to 3.
03Introduced a voice recording option alongside text input, removing the language barrier.
04Removed predefined categories so farmers describe issues in their own words.
05Separated Articles from Help to reduce confusion when looking for support.

07Prototyping & User Testing

We built interactive prototypes for both options and ran structured usability tests in Useberry with 12 farmers.

GOAL

Usability & Intuition

Evaluate the usability and intuitiveness of the new help section design

GOAL

User Preference

Assess user preference between the two design options

GOAL

Audio Effectiveness

Measure the effectiveness of the audio recording feature for issue reporting

GOAL

Experience Feedback

Identify any confusion points or friction in the flow

GOAL

Problem Validation

Determine if the new design effectively addresses the barriers identified in the current flow

Heat maps

01 / 02

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Key Findings

01All 12 users completed the flow and raised an issue successfully.
02Users described the process as very simple and easy to use.
03Users felt that the call-to-action (CTA) was prominently displayed and easily visible.
04Four farmers with low tech literacy initially struggled to find resolved issues, but eventually located them.
05Three farmers found terminology like 'Issues resolved' challenging to understand.

08Conclusion

FINDING

Preference for Design Option 1

100% of users found the separate Help CTA in Option 1 more intuitive and easier to access.

FINDING

Voice recording changed everything

Users appreciated being able to record issues verbally, especially those with limited literacy or typing skills.

"Users liked the audio recording feature because they could speak in their own languages."

FINDING

Fewer steps made a real difference

Farmers described the new 3-step flow as fast and stress-free. No one needed to be shown how to use it.

FINDING

Improved discoverability

Users reported finding the help section easier to locate in both new designs compared to the current flow.

FINDING

Freedom to describe in their own words

Without preset categories, farmers reported issues more accurately.

FINDING

Areas for improvement

Some terminology requires simplification and users initially struggled to locate resolved issues.

FINDING

Key Finding

Option 1 resolved every key barrier: fewer steps, one-tap discoverability, and voice input that works regardless of language or literacy level.

09Feedback implementation

CLICK TO VIEW

Final refined interface incorporating user testing feedback

01
Simplified terminology throughout the help section: Changed Resolved issues to Closed issues for clarity. Changed Attach images to Add images, shorter and more natural.
02
Combined closed and active issues on a single page so farmers can find both without switching views.
03
Made Tap to record the primary call-to-action on the page, more prominent than the secondary options I want to talk and I want to write.

10Impact

107.6%

Increase in tickets raised

Showing massively improved accessibility.

34.28%

Audio feature adoption

Confirmed language barriers as a primary friction point.

24.9%

Mobile submission growth

Better optimization for handheld field reporting.

80%

Ticket resolution efficiency

Diagnostic automation reduced manual agent intervention.

Data based on 6 months post-deployment tracking and stakeholder interviews.

11Way Forward

01
Keep listening: Schedule quarterly field visits and in-app feedback reviews to catch new pain points early.
02
Refine the language: Keep testing label clarity with farmers, especially for technical states like ticket pending or escalated.
03
Smart triage: Explore AI voice recognition to auto-categorize tickets by issue type, reducing manual sorting for the support team.
04
Grow the self-help library: Map common ticket types to new guides, with a target to resolve 20% of issues without agent contact.