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Find the best possible spots & time to go fishing for any weather conditions.


The Problem
Business Risks & Opportunities
The Solution
Planning the project


Competitive Analysis
User Survey
User Interviews
Affinity Mapping
Design Goals


User Journeys & Tasks


User Testing
Design Iterations
Interface Design
‍Onboard new


The Problem

I realized me and other fishing friends are using several weather data provider and maps to manage upcoming fishing trips. To plan a fishing trip, I save my potential spots to Google Maps, check the wind conditions with windfinder, the rain forecast with and the general forecast with It is an unnecessary switching to and fro between providers. Depending on the fishing method and the preferred fish species, each angler is using different weather information. The competitors solutions are either too superficial or provide too much information.

Business Risks & Opportunities

Fishing as a sport became more popular than ever. A younger audience discovered this hobby in the last years as a challenging outdoor activity, which is not only limited to rural areas. The stereotypical angler of an old man, sitting the whole day at a lake transformed to young hipsters, roaming around in the city with their newest high-end tackle from Japan. The influencer joschinator or the YouTube channel ich-geh-angeln reach up to 250.000 followers and clicks. Rapper as Materia and Bushido showcase their catches on Instagram. Fishing is an upcoming niche market with a great potential. The primary risk of my app is not to be reliable. A weather forecast is a sensitive subject. However, it's a great opportunity to be the first mobile app, which provides all necessary weather information in direct dependence to the location and spots.

The Solution

Depending on the fishing techniques, the user receives a selection of weather data that he needs without reading through the overwhelming amount of information. The home screen will show a map, where the user can add different weather layers and other related information, that he needs to choose the right time and spot to go fishing. Weather data and location are directly related to each other. To ensure the best fitting user experience for everyone the navigation will be preset and customizable based on the users fishing method.

Planning the Project

In 18 weeks, I have developed with the mindset of a design thinker a product concept and a high fidelity prototype. I split the project into 5phases referring to the design thinking method: Understand, Observe, Point of View, Ideate, Prototype & Test (3 Iterations).

01 Research

Competitive Analysis

There are various fishing apps on the market. Most of them are using the “Beissindex” as an evaluation criterion of the fish activity e.g. Fischerei Vorhersage or Nautide. The “Beissindex “combines the information of air pressure and the current moon phase to predict a time slot, where the fish activity and eating behavior is high. Some anglers are using the index as a benchmark. For others, it is just mumbo jumbo. These anglers prefer to use different weather apps e.g., or to make their own conclusions. Websites such as, or Deutsche Wetterdienst are known to provide local reliable weather information. and Nautide are common to check the tide. Alle Angeln, Barschalarm or Anglerboard are a growing social communities. Fishroute, Alle Angeln or simply Google Maps and Google Earth are helpful tools to organize and determine possible spots.

User Survey

Male, 20 - 40 years
89.7% do check the weather before they go fishing

Conducting a user survey with google forms, I like to find out how many anglers check the weather and which kind of weather data might be interesting for my target group? Who is my target group? And how do they determine their fishing spots? 30 users participated. The results narrow my target group to males who are 20 - 40 years old. Spreading my survey in the online communities like Barschalarm I received further insights from the user:

• Fish activity forecasts as the "beissindex" are superficial
• Weather archive would be helpful to make conclusions about the weather consistency
• Personal logbook is an opportunity to learn from catches

User Interviews

As part of my User Research, I interviewed four anglers. Each of them prefers a special fishing method, and they all  live in different parts of Germany. In my interviews I like to find out how the interviewees' location influences their fishing preferences and study the detailed process of how they determine their spots and time to go fishing. Which analogous and digital tools do they use? Which information do they need for their fishing preferences?

Affinity Mapping

Which weather data are important is highly dependent on the fishing method, type of water and the preferred fish species to catch. One of my Interviewee, Arne always checks the tide  before he goes fishing for zander in Hamburg. Depending on the tide he chooses  his fishing spot. By contrast, Basti from Munich is checking the weather constancy of the last days, especially the amount of rain, which influence the current of mountain rivers. However, belly boat  angler Bohne needs information about the UV-index to protect himself from sunburning on the lake and reliable information about thunderstorms. David prefers to go fishing if the weather is good, and he does not get wet while being outside the whole day.

I sorted the findings of the interviews to the following categories:

  • Reliability of Forecasts
  • Weather Data (Sub-categories: Structure, Wind, Rain, Spots, UV-Index, Clouds, Air Pressure, Tide, Water Temperature, Temperature, Water Level, Lunar Calendar, Salinity, Pollination, Water Suspension)
  • Spot Search (Sub-categories: General, Using Maps, Using Depth Charts, Using Recommendation)

In summary, it can be said that the interviewees often use several weather forecast resources to higher the reliability and compare. Especially the unreliable "Beissindex" is often a reason why they do not use weather apps tailored for anglers.

Problems Statements
& Design Goals

One tool to identify spots in dependence of the weather conditions because the user dislikes switching between several sources.
Enable easy access to reliable weather data because the user does not want to read through information, which are not relevant for his fishing preferences.
A way to find reliable spot recommendations because he wants to enjoy a successful fishing trip.
An Angler needs to memorize spots.
Possibility to make own conclusions about data because the user might be upset about unfulfilled catch prognosis (beissindex)
Possibility to save his catch and current weather conditions because he can learn from them for future fishing trips.

The Personas

With the goal to design a human centered product, I have summed up all my findings and insights to three User Personas, which I can refer to in the ongoing process of designing FishCast: Sebastian, a fly fisher from Munich, Diddi, who is hunting for pikes with his boat, and Tim, the young street-fisher from Hamburg looking for zander.

02 Design

User Journeys & Taskflow

To make conclusions about the information architecture I’ve sent Sebastian, Diddi & Tim through several journeys and tasks.


The core feature is a map with a layering system, to show the wind conditions and hourly rain forecast. The second is a weather feature, where the user can check all weather data as the review & long-term forecast or the tide.

From Wireframes to High Fidelity Prototype

I scribbled the first ideas as low fidelity wireframes and developed on this base a high fidelity prototype, which is ready for the first user testing. The first navigation level can be controlled over the bottom menu tab bar.

03 Testing

User Testing

I tested this high fidelity prototype by conducting a guerilla testing with six anglers during their fishing sessions. This test method helped me to observe and verify, if the users understand the app and how they behave exploring the core features map & weather.

  • In general: Is it easy to navigate through?
  • Do they understand the layering system on the map?
  • Do they know how to read the weather data?
  • How would they save a new spot?

User Testing Report

During my testing I interviewed six participants. They gave me a great input. In particular Konrad & Max were very open and had many good approaches, that I consider in my prototype. The affinity mapping and the rainbow spreadsheet helped me to sort the findings and make conclusions on my prototype. Four issues need to be solved:

  • Issue 1:  User could not find his saved spots.
  • Issue 2: User tried to find information about the general weather details on the map. (Clicking on the timescale)
  • Issue 3: User likes to name his saved spot.
  • Issue 4: User likes to have a logbook feature.

Solutions 1-2-3

I implemented the solution step by step, and I revised and validated my prototype in two more test iterations. For an efficient workflow, I started to work on the interface design at this stage of the process. Here by, I improved the navigation, type of menu and how to save a spot.

By revising the navigation I solved the issues (1+2). The tester could not find his saved spots and tried to find information about the general weather details on the map. To make the user experience as easy as possible, I added the adjustable quick button navigation. My user can directly access the weather data they need.

Changing to a hamburger menu.
Revising the navigation.
Restructuring the weather data.
Add details to save your spot.

How to onboard new user?

Interface Design

Fishing is a sportive possibility to enjoy the nature and city from a different perspective than usually. The Logo adapts a street art style. It can be used as a character communicating with FishCasts users. The color concept reflects the outdoor character of FishCast. The main font is DIN PRO - bold & medium. It’s a classy, readable font with a functional character.

Polished Prototype

Add weather layers.
Manage your spots.
Check the weather forecast.