Monicat Data provides data consulting for creative organizations and businesses. They asked our team to explore translating their in-person services to a SaaS model.
High Fidelity Wireframes
As a data consultancy focused on helping creative organizations and businesses leverage their date, Monicat Data identified an opportunity to bring its services to a wider audience with a SaaS platform. The challenge lay in replicating their current approach, which involves in-person engagement to customize the approach for each client.
Translating Monicat’s services to an automated approach was the most challenging aspect of the project. After a first round of discovery research, concepting, and testing, my team identified the need to offer users education and friendly guidance about how to use their data at a variety of touchpoint within the site. The result is approachable, modular, and meets users wherever they are at.
• Concepted features that translated the in-person consulting process into digital services.
• Synthesized information from interviews and discovery research to develop design and content strategy for initial user testing.
• Designed high fidelity wireframes to communicate concepts for user testing.
The challenges in this project presented themselves immediately: Monicat had externalized ideas for prompts that echoed their current intake process.
But beyond that, there was no clear direction as to how this in-person service would translate to a digital experience, what that might look like, or if it would even resonate with or be useful to users.
Quickly getting concepts in front of users
Because this would most likely be the first time our primary users had used such a product, we needed to high fidelity mockups to bring to our first round of user interviews.
I worked with another team member to interview an expert in creative entrepreneurship and conduct a competitive analysis of other data driven services to begin designing mockups that could help us gauge what resonated with users in terms of value, what would excite them and get them to sign up for and use the service.
My designs incorporated visual design, content strategy, and possible feature sets that helped us gain an initial assessment of how creatives felt about working with data and what would or would not be useful to them.
What we learned
The results from our first round of interviews revealed a number of insights including:
• A need to be reassured that Monicat can be trusted with user data
• Users were curious and open to working with their data, but were at different levels of comfort doing so—education needed to be embedded in the service at a variety of levels
• The visual design and language was an important part of translating the in-person experience into a digital one
Bright colors and playful imagery make data approachable for all types of users.
1. Language is clear and conversational
2. Abstract images evoke creativity and possibility
3. A short video demonstrates core functionality
4. Feature cards are modular—users can customize tools for their needs
5. Calling out past clients builds trust when asking users to upload data
6. Multiple case studies speak to a variety of users
Customizable dashboard allows users to easily view multiple data inputs, as well as access core features.
1. Learn feature supports ongoing data education for all users
2. Add New adds features designed to echo Monicat’s one-on-one services
3. Suggestions highlight new Recipes to show what is possible
4. Customize feature lets users emphasize what is important to them
Feature: Project Builder
Replaces Monicat’s current intake process. Users indicated that they were overwhelmed by the original prompts—the Project Builder addresses this by asking questions targeted only at the project at hand.
1. A progress indicator breaks the intake process into less overwhelming sections
2. Users are guided through the process of setting up a project with visual prompts
3. A Chat Bot is always available to answer user questions
While most users we spoke with were comfortable setting goals for their business, they expressed significant interest in roadmap-type features that help measure progress towards those goals.
We suggest a goal setting feature that helps users access data-informed guideposts and measure their progress against similar organizations.
Recipes deliver custom insights by combining two or more data sets. Created and shared by Monicat staff or users, they give all users ongoing inspiration for what is possible to do with their data.
The ability to access and share user-generated Recipes can foster community and ensure that there is always something new on the dashboard.
Feature: Data Uploader
Users were very positive about having a central location for storing their data. The data module in the dashboard allows user to have a quick overview of all uploaded data.
The Data Uploader lets them link accounts that use an API for realtime updating. This will provide real value to users, who do not have the bandwidth to perform manual updates.