Acres farmland analytics tool

01 – Project Overview


• Six months as the sole UX Designer on Acres.
• One year as a collaboration with three product owners, two other designers, and a team of over a dozen developers.


June 2021 – November 2022

Skip to the final product


AcreTrader (Acres parent company) utilizes proprietary technology to facilitate the buying and selling of farmland, one of the largest U.S. real estate sectors, exceeding $3 trillion in value. Through AcreTrader’s internal underwriting process, we realized there was a large and underserved market for farmland analysis and appraisal. Our product vision was to see a world where every farm is bought and sold at a fair price.

Problem Statement

Buying and selling farmland is often an uncommon, opaque, and difficult task. Our user needed a way to more easily and transparently discover and evaluate farmland.


Empower our customers to buy and sell land smarter with advanced technology, data, and expertise.

02 – Empathize

User research

To begin our product discovery phase, I conducted both quantitative and qualitative research in collaboration with a product manager. The primary goal of our research was to gain insight into the user journey of anyone interested in buying and selling farmland, specifically focusing on the analysis and evaluation stage of the process. Through surveys and interviews, we were able to hone in on a handful of personas, gaining clearer insights on their specific pain points.

An initial survey, sent to farmers, brokers, and farmland analysts, included the following questions—

• First, what’s your occupation? What do you do all day?
• What does your farmland valuation process look like?
• When you are analyzing your own farmland, how important is it to you to have an accurate valuation range for your property?

In addition to user surveys, we also conducted interviews with farmers, brokers, and farmland analysts. Interviews were documented and we returned to these sessions frequently during our product discovery process. These interviews included the following questions—

• Roughly how many hours a week would you say you spend using the internet, including web browsing and email, at work and at home?
• What kinds of sites do you look at when you browse the web?
• Do you have experience with mapping tools and, if yes, which have you used?

Competitor Analysis

Through our surveys, we were able to gain insight into the current marketplace for farmland analytics tools. We used this data to conduct a competitor analysis. During this process, we gained a deeper understanding into common features and patterns. We also identified potential areas for disruption.

Competitor #1Competitor #2Competitor #3
Features• Land Valuation
• Land Listings
• Comp Sales
• Parcel Ownership
• Carbon Farming
• Crop History
• Soil Survey
• Parcel Data
• Aerial Imagery
• Soil Data Reports
• Topography
• Parcel Boundaries
• Crop History
• Application Forms
• Wetlands
• NDVI Reports
• Map Annotations
• GIS Layers
• Soil Surveys
• Deed Plotting
• Parcel Data
• Sharing
• Database Builder
• Postcard Store
Land ValuationPoorNoneNone
MobileNoneNoneMobile app available on Apple and Android.


User survey statistics were explored graphically, corroborating the results from our competitor analysis.

Finally, all this data was synthesized into larger buckets–

• Speed
• Navigation
• Analysis
• Sharing

I used affinity mapping to organize key findings, which later became the feature requirements for our MVP. From here we were ready to move on to the definition stage.

03 – Define


Synthesis of user research lead to the creation of three primary personas—

• The Farm Analyst
• The Expanding Farmer
• The Farmland Broker

These personas where considered when making any further product decisions. The following content highlights some of the deliverables we were able to use our personas to create. These deliverables included creating current state journey maps, future state journey maps, and defining pain points for each user group.

Current State User Journey | Farm Analyst

After sitting through farmland underwriting sessions conducted by our internal analysts, key patterns began to emerge. These sessions included quick context switching between many platforms (Hubspot, AcreValue, PDFs, MapRight, Surety, Excel, etc) in order to provide clients timely information while they had them on the phone.

Pain Points & analysis

From these sessions, common pain points emerged, including—

• Constant context switching to access relevant data
• No way to export or share insights
• Data summaries were difficult to access, especially when working between various layers

“My top priority is to find and source undervalued farms to purchase. I don’t have time to spare, so I need to be able to analyze potential farm leads accurately and quickly.”

—Farm Analyst

After compiling interview data and looking through user sessions, we discovered that our biggest problems to solve for included minimizing navigation between tools to evaluate data sets, providing a way to quickly export a data report or summary, and a lack of robust searching or selection interfaces, especially when working between various layers. These findings mapped well with the affinity mapping buckets from our empathizing stage (speed, navigation, analysis, sharing).

04 – Ideate

User Flows

Task analysis was performed and user flows were created to help understand essential screens needed for the application. The following user flows represent two major features Acres had to try to solve for—

The ability to quickly select and analyze land. (navigation, speed)

The ability to share a report. (sharing)

05 – Wireframing & Prototyping

Low-Fidelity Wireframes

I built screens, tested them, and vetted them with business stakeholders and representatives from our persona groups. These were built in whimsical before moving on to mid and high fidelity wireframes in Figma.

Interaction Design

Many user flows benefited from prototyping—I discovered very quickly that designing for a mapping interface necessitated a lot of complex interaction.

Elements for higher fidelity wireframes were primarily built in Adobe Illustrator and Adobe Photoshop, while screens and interactions were built out in Figma.

06 – Testing

Usability Testing | Navigation

I conducted usability testing for Acres on a feature-by-feature basis.

One of the first major usability tests I performed was around navigation. For this test, I wanted to make sure we had representation from our user groups, so I gathered a sample of three farm analysts, three farmland brokers, and one expanding farmer. Users were assigned situational tasks and their behavior was observed. I presented four high fidelity prototypes to these individuals, collecting qualitative data through recording and documenting these sessions.


The goal of this usability test was to identify the learnability of the application for new users on desktop. These tests aimed to highlight any issues while observing the user completing basic navigational tasks.


User testing sessions were varied based off the hypotheses and KPIs we were trying to solve for. The specific sessions around navigation included the following tasks—

• Selecting a piece of land (navigation)
• Deselecting a piece of land (navigation)
• Selecting a data layer (navigation, analysis)
• Analyzing a selection (navigation, analysis)

“It’s great to be able to deselect from anywhere and not have to be able to go back to the beginning.”

“I don’t like that you have to be in a certain place in order to select a parcel.”


In this specific navigational test, users overwhelmingly preferred the option which gave them the most freedom to select parcels and layers simultaneously. This was at odds with my hypothesis, and so proved to be a very valuable insight.

Each feature on Acres was designed within a similar framework. Our discovery process began with user interviews. Feedback was then analyzed, and used to make decisions on both new feature work and refining existing elements. Read about the draw polygon feature for an Acres case study focused on another facet of the tool.

07 – Develop

Developer Handoff

With limited product manager resources on many Acres sprints, one of my responsibilities for every new feature developed was to create a seamless handoff file for our developers. Additionally, I wrote JIRA tickets with relevant Acceptance Criteria in order for the development team to understand, create, and QA test any feature work.

Early on in working with the Acres team, in order to make sure this process continued to run smoothly, I developed the following workflow for our team. This was our resource for assessing the right order to complete feature work. It was also its own reward in the organizational benefits we gained.

08 – Final Product


Mobile | Figma Prototype

Landing Page | Figma Prototype

10 – Outcomes

One Year Later

Through continual user interviews, we confirmed our original hypothesis and helped to make buying and selling farmland more common, more transparent, and easier.

The following is a recording of one of our farm analysts showcasing all the ways he currently utilizes the tool.

Business Outcomes

During this process, we quickly understood that further development would require a strong business case to raise a large enough investment to gain momentum. In January 2022, the Acres BETA was able to help in securing $60 million in VC capital for AcreTrader’s Series B funding round. Acres launched to the public in June 2022.

Current state user interviews indicate a strong preference for Acres against our competitors. We heard frequent positive feedback on our data quality and ease of use.