AI Marketing Innovations
AIMI is a start-up company specializing in incorporating AI-driven conversational chatbots in text, form, and voice capabilities in multiple languages to automate customer interactions.
Their vision is to improve patients' customer experience in Ophthalmology Practices by including engagement through Chatbot integration. Their intent is to minimize high-volume queries, increase customer satisfaction and brand loyalty, simplify operations & and increase productivity, and amplify overall business value.
Context
Team
Roles
Thea Marie
Jillyn Johnson
Jay Martin
Noimat
UX/UI Design & Research
Chief Strategy Officer
System Development
Project Manager
AI Chatbot AskMi
01. Understanding the Audience
Problem Statement
Ophthalmology centers are missing patients. They do not provide self service options for customers and have no adequate tools to track metrics. The sheer magnitude of incoming calls and lack of access to customer information leads to low first call resolution, high average handling times, and customer frustration. Some supporting stats, 13% missed calls, 29% inquiries after hours, 50% on-hold patients hang up, 68% of the web form leads are not obtained, etc. This lowers customer and employee experience and reduces revenue.
Hypothesis
If we train the conversational chatbot “AskMi”, in all potential areas of customer inquiries through the process of document ingestion, categorizing customer queries, creating a data set, user testing, etc. Then the business can make informed, data driven decisions to lead business growth by providing self service options and 24 X7 human-like support significantly improving first call resolution, generating leads, and improving customer retention and satisfaction.
Personas
02. Creating the System
Painpoints
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Frustrated by language barrier as English isn't her first language, feeling misunderstood.
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Wants to avoid phone queues but can't call during the practice's operating hours due to family and work commitments.
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Fearful of LASIK surgery, seeks more information about the procedure.
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Uncertain about the LASIK specialist at the practice and prefers brief interactions due to a busy schedule.
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Lacks understanding of his eyesight condition, leading to uncertainty.
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Fearful of diagnosis and potential vision loss, struggling with the appointment booking process at the practice.
After reviewing competitor chatbots from an aesthetic standpoint, my goal was to design a chatbot that was simple and effective with an engaging conversational flow specific to customers and their use cases. Using well defined design principles I wanted to give the chatbot a unique personality in keeping with brand standards while considering the functionality and the intended audience. Applying effective layering techniques, skillful use of color theory, etc led me to design an intuitive chatbot with a distinct identity that enhances the user experience.
Inspiration
Style Guide
We developed our design system based on our inspiration and competitor analysis.
We went with our specific color palette because it is versatile and each color combination works well together. We tried a couple of options for our typography such as Poppins and Open Sans but ended up going with Rubik because of its simplicity and rounded edges. We found that using this typeface gave us a warmer, more friendly tone based on the research and testing we conducted. For our illustrations, we wanted to go with something that didn’t have a very defined outline. We chose illustrations that could be dynamic without the use of line work but instead featured our selected color palette.
03. Creating the System
Logo Redesign
I designed this logo with the idea of symbolizing unity between the chatbot and healthcare professionals. I'm fully aware that there can be concerns about technology, especially AI, potentially taking over human jobs. However, the primary purpose of this logo is to highlight integration and working together. AskMi is here to handle routine tasks efficiently, which in turn, gives healthcare professionals more time and space to concentrate on the more intricate and vital aspects of their work. This collaboration ensures a more balanced and productive approach to healthcare vs one of competition and hostility.
Sketching
Mid-Fidelity Wireframes
These wireframes provide a clear layout of the interface, showcasing the placement and relative size of different UI components like buttons, menus, and input fields. Incorporating placeholders for images and text, they facilitate a better understanding of the content structure and user flow.
Jenny Ta's SOU through AskMi
Lisa Roberts's SOU through AskMi
Charles Berry's SOU through AskMi
Testing
User Testing by Age and Usage Groups:
As part of our comprehensive user experience assessment, we conducted targeted testing with various groups categorized by age and specific usage scenarios. This approach allowed us to gather nuanced insights tailored to distinct user needs and preferences.
Demographic Segmentation and Tasks
1. Elderly Group (65+): Focused on Cataract-related functionalities. This group was crucial in understanding the accessibility and ease of use for an older demographic, typically more prone to cataracts.
2. Middle-Aged Group (25-45): Concentrated on LASIK-related features. This demographic is most likely to opt for LASIK procedures, providing valuable feedback on relevant functionalities.
3. Mixed Age Group: This group was diversified across various age brackets, focusing on general eye examination features. The mixed demographic offered a broader perspective on the application's universal appeal and usability.
Testing Methodology
Each group consisted of seven carefully selected individuals. The testing procedure was structured in three distinct phases:
1. Open Exploration: Participants were first allowed to freely navigate the interface, simulating a natural interaction with the application. This phase was essential for observing user behavior in an unrestricted environment.
2. Task-Specific Evaluation: Subsequently, participants were assigned specific tasks to complete. This approach enabled us to assess the interface’s effectiveness and intuitiveness in accomplishing particular objectives.
3. Feedback Collection: The final phase involved gathering comprehensive feedback from each participant. This encompassed their overall experience, ease of use, and any difficulties encountered during the interaction.
Conclusion:
This multi-faceted approach yielded in-depth insights into the user experience across different age groups and usage scenarios. The findings from this study are instrumental in guiding further refinements to ensure the interface is intuitive, accessible, and meets the diverse needs of our users.
High Fidelity Wireframes
In these wireframes, you'll see exactly what our final product is shaping up to be. From the color schemes to the crisp images and UI elements, we've nailed down the details. They're designed to give you a real feel of our vision and an almost replica of our final product.
