We utilized the design thinking methodology to find opportunities for innovation within this product niche. The Discover | Define | Develop | Deliver model of the double diamond strategy was also utilized to improve my designs.
Lean UX principles were applied with rapid wireframing, prototyping, and continuous user feedback at each phase. Educated assumptions drove design decisions and were validated/disregarded based on research and direct user feedback. User personas, user flows, and a well-defined problem statement remained our compass while guerilla testing recalibrated true north.
While I was the design lead on this project, open discussion with my fellow designers and mentors at Careerfoundry created a valuable feedback loop which significantly improved the product.
More specifically, they need relevant, near term weather data to inform their decision process in addition to historical trends to improve their potential for success.
I wanted to go deeper into this problem statement to better understand the specific pain points of potential users in order to develop targeted solutions.
Simple weather reports do not provide enough information, specifically location dependent information, to be useful for fly fishers. An app that presents all of the weather/ environmental factors is necessary to bring value to users. These factors include: precipitation, wind, tide, water clarity, water temperature, water salinity (coastal), cloud coverage, flow rate (river), wave height, insect activity (rivers), prey species activity (coastal)
An app that uses predictive data from highly esteemed, scientifically validated models, as well as historical records and up-to-date observations from trusted, local sources.
Capture weather, location, and incident data to create a historical record. Users can analyze this information or use of AI to discover meaningful patterns
Our app will present weather and environmental information, including predictive metrics on fishing activity in an easy to read, visual interface. We will also provide fly recommendations based on the correlation of historical data with the current information provided to increase our user’s chance of success
During my initial competitive analysis, I focused on fishing apps that ranked well within search and ratings results. I used this to benchmark common features and interface design. As the project progressed and more insights came from direct user research, I conducted a more focused second round analysis to ensure that my designs were continuing to improve on current products.
Key Areas of Opportunity
The fly fishing community is not well served with existing products. Distinct cultural, equipment, and tactical differences exist that noticeably reduce the utility of current apps for fly anglers.
Most apps are duplicating the prevailing social media model under the assumption that the fishing community would rather use an angling focused product to fill that need. My hypothesis was that the majority of experienced, recreational anglers needed an app that facilitated their success on the water, instead of filling a space already occupied by larger, more prominent digital communities.
Furthermore, my hypothesis included an assumption that the majority of fly anglers maintained small, trusted friend groups within the context of fishing, a design that not only mimicked a traditional cognitive model of social interaction, but one in which cultural norms like “secret spots” and mild xenophobia are common.
In existing products, checking weather involved a distinct interruption of user flow. When users were exploring maps, checking on known and unknown fishing locations, they were required to navigate away from their exploratory behavior to assess weather data. An opportunity exists to create a seamless experience in which users can see important information without an interruption to these interactions.
With a better understanding of the current market landscape, I dove into research involving angler's motivations, needs, and behaviors to answer some lingering questions
1. What weather and environmental information is important to fly fishers?
2. What are the typical routines of users in planning fly fishing outings?
3. How do users typically use technology in their routines before and during fishing activities and what tasks would they like to accomplish?
4. How do users leverage weather data in their decision making process?
16 Questions
65 Responses
75% Primarily Fly Fish
7 Questions
3 Interviews
100% Fly Anglers
40+ Hours
4 waterways
100% Fly Anglers
After reviewing survey responses and recordings from the discovery interviews, I noted key points of interest, pain points, and potential opportunities. An affinity map helped to organize these bits of data into meaningful trends that would better inform our product design.
• Weather wasn't a significant deciding factor regarding IF an angler went fishing, but did influence location choice.
• 73.9% agreed that understanding insect or prey species activity was important to them.
• Understanding success patterns was critical to decisions on where to fish.
• Drive time was important in regards to location choice.
• Weather ranked as the number one influencer of destination choice.
• 83.1% always checked weather before going fishing.
• The perceived credibility of a source was very important.
• 50% spent more than 6 days on the water in the past two months.
• 72.3% were DIY fishermen, meaning they plan trips themselves.
• 64.6% researched types of flies before going outLocal fly shops . ranked as number one source of information.
• 63.1% anglers want to keep a fishing journal
• The majority of anglers used their mobile phones to check weather.
• Desktop functionality is still important, especially in regards to trip planning.
• The majority of users did not look to fishing apps for weather. Why?
It was no surprise that weather is important to fly anglers. The real value of this analysis was in conceptualizing how environmental information was being used within common behavior patterns and how I could improve on the efficiency and effectiveness of this process. With this goal in mind, I proceeded to put a face and story behind our users.
This information allowed me to refine my targeting strategy during the initial project phase. The first round of development focused on meeting the needs of Jacob and Thomas, our primary personas. User personas were critical to my process as they functioned like empathy yard sticks, measuring how close, and sometimes how far, I had strayed from a user-centric model.
I used journey mapping to visualize how our user personas would accomplish specific goals in line with their needs, motivations, and technology usage. This allowed me to better understand actual pain-points within the context of user stories. Formulating user stories allowed me to synthesize better, goal-oriented tasks based on what user’s wanted to accomplish, their likely emotional response, and what information they need to succeed. A task analysis was used to determine the specific requirements associated with particular features of the app.
With a better understanding of high level tasks, I began developing the organizational structure and design foundations needed to capitalize on the insights from our user research. I considered common user behaviors as benchmarks for building out the initial site map, which was then tested via a cart sort to validate my assumptions.
When it came time to sketch, I continued to focus on specific tasks to ensure the user flow aligned with research findings. Guerrilla testing was used to quickly direct the initial, lo fidelity sketches toward a medium fidelity prototype that would ensure more accurate assessments during user testing.
With the first iteration of a clickable prototype ready to hit the water, I was excited to put it in the hands of users to see how it functioned. The goals of our study centered around an assessment of learnability by new users when completing a series of core, functional tasks as well as an evaluation of user opinions regarding the utility of these features
We conducted three remote and three in-person evaluations using an iOS based prototype. Four of the individuals were recruited from the local fly fishing community and took at least three fishing trips per month. Two individuals with minimal fishing experience were recruited to provide a diversity of perspective within the test results. Data was organized via a Rainbow Diagram into feature specific feedback.
While the purpose of the initial round of user testing was focused on evaluating higher level functions, and the results generally confirmed my assumptions, many of the difficulties users experienced demonstrated a need to make fundamental changes to my UI approach.
Test participants repeatedly asked where they could access a map and reported they relied heavily on apps like Google Earth. There was a distinct tone among the more experienced anglers identifying a desire to explore as a primary element of their fishing experience.
Five of six testers moved past the onboarding screens without reading them and could not recount that information. All users inquired about setup of a user profile with preferences in order to tailor the interface to their needs.
Based on our research, a critical metric for the adoption of our app by experienced anglers will be the accuracy and reliability of our weather data. Communicating this visually within our interface will be necessary to meet this requirement. Participants who reported using a weather app stated their number one reason was “it is more accurate than other apps”
Users misinterpreted main navigation icons, despite the industry standard icons that were used. The icon for the catch record was accurately interpreted by only tw of the 6 participants initially. All users were unable to find the trips functions initially. In order to maintain a simpler home screen while still having a feature rich app, the hamburger menu will provide a shallower, yet broader information architecture.
With the final phase of user research complete, as well as a major round of design changes to the interface, the driving question behind our progress became; "How do we move beyond a simply functional product and into an impactful one?" A contiguous visual language and brand voice were as important to capturing and retaining users as matching food sources are to feeding fish.
The driving principle behind the logo was a reflection of the aesthetic that influenced the functionality of the app, and on a broader scale, has directed design throughout the fly fishing industry. This clean, iconic, and versatile design clearly reflected the mission of Angler Outlook.
Branding focused on reflecting tones that were not only indicative of the natural environment, but also facilitated compliance with the WCAG AA accessibility rating for contrast.
SF Symbols were utilized for all available icons to conform with existing mental models. For custom icons, Materials and Apple Human Interface Guidelines were consulted to ensure continuity of the user experience.
As a brand, we’re not only interested in giving anglers the tools they need to catch fish. This is about taking hold of the match that ignites as soon as the rod bends and fanning it into a flame that burns for a lifetime.
Satellite imagery was a critical feature for all of the experienced anglers. They reported a sense of self-guided exploration as they were searching through maps to find fishing spots. So, I designed an interface that empowered anglers to find new water without getting in their way. I reduced the clutter of top level navigation by giving users the ability to hide those assets until they are needed. Both menu icons were placed on the right side of the interface to facilitate one handed operation, like when you are holding a fishing rod or taking a hero shot with the biggest catch of your life.
Users were interested in a simple, intuitive interface that prioritized utility over luxury. Therefore, unneccesary features were eliminated while still giving users control and visibility over information depth. Consistent topography was applied through the app so users could easily create mental models around navigation, content hierarchy, and information depth. I also gave users access to location information, fly recommendations and additional information so they don't have to use multiple resources to plan a trip.
They say a picture is worth a thousand words, but when you are learning how to be a better angler, a camera roll of photos just doesn't cut it. Angler Outlook utilizes image and voice recognition technology to automatically capture critical data about users' catches. It logs location, time, and weather information as well, creating a data point that is analyzed by AI to create predictive models that anglers can use to increase their success on the water.
Anglers can also opt in to share geographically generalized catch data with state and federal wildlife management organizations, as well as NGOs like Trout Unlimited and the Coastal Conservation Association, to facilitate research and management goals.
Accuracy and reliability of data were critical for adoption. From a UI perspective, users associated extraneous features and cluttered layouts as misaligned with their core needs. They interpreted these observations as reasons to discontinue use of an app. Therefore, I built trust through consistency of design elements, a trusted network of sources, and the ability to give feedback for continuous improvement of prediction models.
Accessibility is a right, not a privilege, so we blocked in features that would accommodate as many users as possible. I added visual cues, increased color contrast, and build in a dedicated menu for the visually impaired. I also designed an easy feature that allowed users to download maps via a wifi connection in the instances that cellular data is not available or too expensive for use.
