AgMRI

Redesigning a crop & soil insights app for field-centered usability and enterprise-scale effectiveness

CLIENT

IntelinAir, a startup founded on using AI-analysis of aerial imagery to provide realtime field and crop insights to farmers.

IMPACT

  • Improvement in product usage amongst existing users, with 4x increase in DAU/MAU

  • 3x increase in new customer adoption vs prior growing season

  • MVP Customer feedback:

    • “I like that I’m able to navigate it quick and that you cut all the other mumbo jumbo out of it. 2 clicks and I’m able to get the info I need…no other tool will give you this info this quick.”

    • “This design is 9/10 while previous AgMRI was 4/10”

    • “I rely on the alerts to highlight what I should look at (I have too many fields to monitor them all) - then I look at the images to verify if I need to go in person or wait until the next flight

TEAM/ROLE

UX+UI Lead (myself) + Product Owner, 2x Business Analysts, User Research Lead, Tech Lead, Offshore Engineering team

RESPONSIBILITIES

As UX+UI Lead, the scope of my work covered:

  • Workstream scoping, planning and management

  • Supporting initial user discovery, insights generation, feature backlog building and MVP prioritization

  • Defining user flows & wireframes for MVP features

  • Leading concept and usability testing with target users

  • Collaborating with client SMEs to refine MVP feature set and usability

  • UI development across iOS and iPadOS

  • Building a design system that retained the client’s existing visual language while making improvements in usability and performance

  • Design documentation (redlines, prototypes, annotated files) & support for F/E development

Context

IntelinAir’s proprietary M/L model provides information about crop health, growth progression, weed presence, soil quality and disease from aerial imagery alone. Their initial business model and product targeted individual farmers, charging them a subscription fee for local flyovers and access to a desktop app that provided the core information generated from the imagery.

Problem/Brief

IntelinAir found that their initial B2C business model was unsustainable due to low customer uptake and high customer acquisition costs. The desktop app also faced issues, with difficult navigation, confusing UI and poor overall usability being key user complaints.

The intial brief called for:

  • New feature set that supported IntelinAir’s pivot from a B2C (farmers with 1-2 properties) to a B2B approach (enterprise farm managers with 5+ properties from different farmers, and seed & fertilizer salespeople)

  • A mobile-first app with UX tailored for in-field use by target users

User discovery and building the feature backlog

With the User Research Lead, we conducted hours of field visits and virtual interviews with client SMEs, current users and potential new users within the target profile to understand usage environments, use cases, needs and pain points. We then worked with the client to translate these findings into potential features, before collaborating with PO and Tech Lead to build out and prioritize the feature backlog.

My role throughout this process was to bridge the gap between the different phases of design and ensure that the initial user insights continued to resonate throughout (e.g. translating insights into potential features; planning and leading client cocreation workshops; sizing UX impact of product features).

Collaborative MVP design and build

With MVP features defined, I then set about defining the user experience - using user flow diagrams, wireframes and clickable prototypes to routinely test with client SMEs and target users. I also held weekly sessions with the tech lead and offshore dev team to keep them in the loop of new developments and encourage early discussions around technical feasibility.

As high-fidelity designs progressed, I also built a library of UI components and patterns that continues to be used by the client for new UI development.

Revamped navigation and information hierarchy allows users to quickly find growers, farms and fields from map and list views. iOS modal sheets are used to display different levels of information, so users can choose how deep they would like to drill down into a particular field.

Users receive in-app and text alerts when their fields are experiencing critical issues. Alerted fields are also prioritized in order of acreage at risk, helping users triage which fields need attention first.

Intuitive field-level navigation enables users to view current issues, past events, make annotations and measurements, and toggle between different visual analysis filters.

Users can quickly create and log content-rich reports while they are out scouting the fields.

Field managers can quickly share issues with their farmers via text or email, with a deep link to the issue details page.