Phil Banks





For the last 10 years I’ve been embedded in high performing, consumer product teams as a designer at: 


Peloton WIP
Halter
InMusic
Nura
 Serato




  •   New York, NY            



Halter Case Study
2023 | Auckland, NZ
Senior UX Designer

iOS


Increasing profit for farmers by managing the reproductive health of dairy cows

















Introduction
By using advanced data modelling & machine learning, Halter's solar-powered smart cow collars and iOS app allows farmers to remotely shift, virtually fence, optimise pasture, and proactively monitor the health of dairy cows. Watch this video to see more on how Halter works.


















Movement data
  1. Sent from the collar.
  2. Received by towers installed on the farm.
  3. Interpreted as behavioural data by Machine Learning Models (Moving, Grazing, Resting, Ruminating).
  4. Displayed as behavioural insights to the farmer in the app.















Heat Detection

By observing patterns in behavioural data, Halter is able to identify cows on heat. Traditional methods of heat detection are time consuming during the busiest time of the dairy farming calendar. Knowing each cows optimal heat window gives farmers the best chance of conception.












Opportunities
During the 2022 spring mating season, Halter successfully demonstrated that their models could accurately detect heats in dairy cows. This breakthrough provided valuable insights that were used to refine and expand the models throughout the rest of the year.

Enhance Mating Season Performance
By leveraging this improved data, we identified opportunities to introduce new features that could deliver deeper reproductive insights, such as identifying cycling vs. non-cycling animals, tracking submission rates, and monitoring non-return rates; all within the app.


Iterate on the 2022 Feature Set
Feedback gathered from the 2022 season highlighted several areas for improvement in the existing feature set. These insights presented a clear opportunity to refine and enhance the app's functionality, ensuring it better met the needs of farmers and delivered an improved user experience for the 2023 season.














Goals
Develop and release a series of features throught Spring mating season 2023 designed to provide farmers with critical reproductive insights. These include identifying cycling vs. non-cycling animals, tracking submission rates, and monitoring non-return rates—all aimed at empowering farmers to make data-driven decisions during mating season.



Increase Six-Week In-Calf Rate (6WICR)
Demonstrate the value of Halter by improving the six-week in-calf rate (6WICR) for farmers using our platform, comparing their performance to regional averages. Achieving above-average results would validate the effectiveness of Halter and its potential for higher ROI during the mating season.

Prove ROI for Farmers

Provide clear, actionable evidence of the return on investment (ROI) for farmers using Halter. By quantifying improvements in mating season performance, we aimed to build trust and showcase the tangible benefits of integrating Halter into their operations.












My Role
I led the design and UXR for the Mating product leading up to and throughout the 2023 spring mating season. I worked collaboratively in a fast paced startup environment with:

  • Data scientists to visually communicate insights from ML models. 
  • Veterinarians to validate ideas and ensure the well-being of the animals.
  • Product Managers for expert knowledge and to define, scope, and plan the roadmap.
  • Developers to implement the designs.

Tools we used:

  • Notion to centralise product definitions.
  • Linear to create stories and track progress in development.
  • Figma to visualise early concepts, create user flows, test clickable prototypes and communicate hand off to developers.

















Early Ideation
I defined interactions and user interfaces through white-boarding and user flows. There were many hours spent sitting around whiteboards with farmers and vets to under which metrics would be most useful and how best to display them.

I was leveraging an existing design system so we were able to move from initial concept to near polished designs quickly while ensuring consistency with the rest of the app.

I built functional prototypes to validate and test our designs with veterinarians and farmers.















Collaborating with Veterinarians
We collaborated closely with a board of veterinarians to deeply understand the science underpinning our designs. To gain firsthand insights, I visited rural vet clinics where I observed discussions between farmers and vets about the results from the previous mating season.

Understanding the science was crucial to ensure that the features we designed were not only user-friendly but also scientifically accurate and aligned with best practices in animal health and reproduction. This foundation helped us build trust with farmers and vets while ensuring the app provided meaningful, actionable insights.

















Contextual Inquiry
To design effectively, it’s essential to understand the user in their real-world context. I visited Halter farmers on their farms, immersing myself in their daily routines and challenges. These contextual inquiries provided valuable insights into the farmers’ needs, workflows, and pain points, helping us design features that truly addressed their requirements.


Remote Usability Testing
While on-site visits were invaluable, most of our user research was conducted remotely. Through interviews and usability testing sessions, we observed farmers interacting with clickable prototypes, allowing us to gather actionable feedback on the design. This remote approach enabled us to iterate quickly and refine the experience based on real user behavior.















Finding 1: Planning and Prioritization
Through our research, we identified which features would have the greatest impact at different stages of the mating season. This insight allowed us to prioritize our backlog and adopt a phased approach, releasing features on a two-week cadence to align with farmers' evolving needs throughout the three-month season. For example, cycling metrics were critical during pre-mating, while submission metrics became relevant later in the season.




MVP




We realized we could quickly provide value by delivering simple, actionable metrics that addressed immediate farmer needs.
V2





Building on the MVP, we introduced graphs to give farmers a clear visual overview of their data, making it easier to interpret trends and patterns.


V3




In the next iteration, we added automatically generated insights. These insights further simplified decision-making by highlighting key takeaways and actionable recommendations for farmers.








Finding: Heat Graph Improvements
Our research revealed significant opportunities to enhance the heat graph for individual cows, making it more intuitive and actionable for farmers. The following improvements were identified:

  • Clearer Labelling: Adding labels to the X and Y axes to improve clarity and usability.
  • Enhanced Visual Contrast: Making the difference between heat activity and normal activity more pronounced, increasing farmers’ confidence in interpreting the data.
  • Heat Event Timeline: Introducing a timeline above the graph to visually summarize heat events. Selecting a specific heat event would scroll the graph to the corresponding data point for detailed review.
  • Editable Data: Providing the ability to edit or remove heat activity if the farmer determined the cow was not actually on heat upon examination.
  • Flexible Zoom Levels: Adding month, week, and day zoom levels to allow farmers to analyze trends over different timeframes.

These changes aimed to make the heat graph more user-friendly while empowering farmers with better control and insight into their herd’s reproductive data.




Before






After

















Real-time visibility into key metrics



Pre-mating cycling and fertility insights are critical to ensuring a successful mating season.

These metrics ensure that every opportunity to optimize herd fertility is captured. Farmers can make informed decisions that improve reproductive outcomes, increase efficiency, and ultimately drive a higher return on investment during the mating season.













Easily identify cows on heat



Farmers can quickly and easily see which cows are on heat through a clear and intuitive interface.

This streamlined process saves time and effort, allowing farmers to act quickly on heat detection insights. Knowing which cows are currently on heat or reviewing their history enables timely insemination, reducing missed opportunities and improving overall mating season outcomes.








Ensure your herd is rested, healthy, and cycling early



Set your herd up for success by giving them the best chance to get in-calf early. Customize feeding plans based on calving dates or body condition scores, and monitor individual and mob rumination levels to ensure every animal is recovering and thriving.

This proactive approach minimizes stress on animals, optimizes milk production, and increases the likelihood of achieving higher six-week in-calf rates, leading to improved farm efficiency and profitability.











Filter, Sort, and Take Action




Farmers have the flexibility to filter, sort, and act on their herd’s data, tailoring the insights to align with their specific mating strategies.

The ability to take immediate action based on real time data saves time and ensures a more strategic approach to herd management.













Pete & Ann lifted their 6-week in-calf rate by 13%, a $90,000 profit



“We have just got our PD results back and have had our best result in 20 years, there were a number of factors that led to this but right at the heart is Halter’s Mating tool, and Pasture Pro”


See Pete’s story











Challenge: 

Navigating a Complex Industry
As someone without a background in farming or animal health, I faced the challenge of designing for an industry with highly specialized knowledge, unique workflows, and deeply ingrained practices. Understanding the complexities of livestock management, reproductive health, and the daily realities of farmers was essential to creating impactful solutions.

Solution: 

Immersive Research
To bridge this knowledge gap, I adopted a hands-on approach:

  • Farm Visits: I visited multiple farms to observe firsthand how farmers interact with their herds, manage their workflows, and make decisions. These visits provided invaluable context and real-world insights that could not be captured through secondary research alone.
  • Proactive Planning: Given the limited time available during farm visits, I ensured that every session was highly structured and goal-oriented. I arrived with well-prepared prototypes and clear plans to test specific features or validate design ideas. This approach maximized the value of the time spent with farmers.
  • Building Empathy: By immersing myself in the farming environment, I gained a deeper appreciation for the challenges farmers face, allowing me to design with their specific needs and constraints in mind.

Outcome:
This strategy not only helped me overcome the steep learning curve but also ensured that the solutions we developed were grounded in the realities of the farming industry. Farmers appreciated the practical and well-tailored designs, which addressed their pain points while respecting their time and expertise.








Challenge: 

Conceptually complex designs for non-technical users
Farmhands, who often handle day-to-day tasks, may have less experience with digital tools compared to farm owners who manage operations. This disparity can create challenges in adoption and effective use of the app, as all users need to interact seamlessly with the product to achieve the desired outcomes.


Solution: 

Intuitive and Inclusive Design
To address this challenge, we focused on making the app intuitive and accessible for users with varying levels of tech familiarity:

  • Simple, Clear Interfaces: We designed the app with a focus on simplicity, using clear labels, intuitive navigation, and minimal steps to complete key tasks.
  • Role-Appropriate Features: Features were tailored to suit different users’ responsibilities. Farmhands needed quick, actionable insights, while farm owners required more comprehensive data for planning and oversight.
  • Device Flexibility: The app worked seamlessly across devices, from personal smartphones to shared tablets, ensuring all users could access the tools they needed without technical barriers.
  • Onboarding and Guidance: Built-in onboarding and contextual tips helped new users get started quickly, reducing the learning curve for those less familiar with technology.

Outcome:
By prioritizing ease of use, we ensured the app could be effectively used by everyone on the farm, regardless of their tech background. This inclusivity not only boosted adoption but also fostered collaboration between farm owners and their teams, leading to better outcomes during the mating season.