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From Nerves to Sucess: My First Client Presentation

Greetings to all my inquisitive designers and dedicated blog readers. Within this post, I’m excited to recount my first client presentation. It’s quite an amusing tale if I do say so myself.

In March, I started working on a project as a junior UI/UX designer, collaborating closely with a senior designer. Upon receiving the Business Requirements Document (BRD) from the client, its contents initially left me confused. Nonetheless, I diligently commenced work on the project following the provided instructions.

Initially, my focus was on the agent portal. However, my senior designer later reassigned me to the back office admin portal, which comprises four distinct modules. I initiated my work on the first module, specifically the back office admin segment. The senior designer informed me that, in this compact module, we would only be incorporating 2 to 3 menus on the dashboard. 

When I initially began the development of the back office module, I delved into the Business Requirements Document (BRD) and discovered a multitude of menus outlined within it. I meticulously organized these menus and set to work on them. Approximately 8 days into the project, my senior inquired, “Madhuri, how long will it take you to wrap up this module? It appears to have taken quite some time.” At that juncture, I had successfully crafted a comprehensive dashboard along with three distinct menus, complete with their respective detailed screens. When I presented my progress to him, he expressed his astonishment, remarking, “I never envisioned this module to be of such substantial scale!” What compounded the challenge was the lack of available references, with the module encompassing roughly 150 to 160 screens in total. Despite facing numerous hurdles, I finally managed to successfully complete the “Back Office Admin” module within a span of 25 days. “Back Office Admin” The name itself does have a somewhat horror ring to it for me at the time. But all jesting aside, I was genuinely relieved to have accomplished this feat.

As the moment approached for the client presentation of my module, uncertainty loomed over thinking about who would take the reins and stand before the client to present the design. I had assumed that my senior would take up this role. I vividly recall the day when my senior informed me, “Hey, you’ve worked on this module, and it’s your responsibility to make the presentation.” At that very instant, I couldn’t help but think, “Oh god, help me through this.” My hands trembled, and I felt far from prepared for the upcoming presentation.

In the wake of this revelation, I began my preparations for the design demonstration. Eventually, the moment arrived, and my senior asked me to start the presentation. Drawing in a deep breath, I began.

Initially, I presented a complete overview of the entire module with details regarding the available menus, our overarching design approach, and the step-by-step progression of our design methodology. Within this context, I explained our primary objectives and how we successfully attained them. Then I gave them a walkthrough of the design and each screen in detail with a comprehensive description of the specific module, in line with the client’s explicit requirement for a detailed design explanation.

During my initial demonstration, I showcased a grand total of 160 slides, an enriching experience in itself. Throughout the presentation, the client posed several inquiries, to which I lent keen attention and replied with utmost politeness and clarity.

Following the presentation, I gleaned valuable insights. The presentation itself has two distinct modes: the first is the online presentation, and the second, is the offline presentation. Mine was online, giving me certain advantages. Nevertheless, it is crucial to bear this point in mind to ensure the success of your own presentations.

1. Embrace Self-Assuredness: Confidence is a constant factor, even when you occasionally misspeak. Regardless of what you express, do so with unwavering confidence.

2. Begin with Confidence: As you commence your demo or presentation, initiate with a warm greeting and introduce yourself.

3. Harness the Power of Your Voice: During an online presentation, your voice takes center stage as your unique identity. Therefore, it’s crucial to employ a clear and composed tone, maintain pauses between sentences, and avoid speaking too rapidly. Allow your audience ample time to ask questions if they have any.

4. Clarify Screen Details: During any type of demo or presentation, provide a comprehensive overview of the specific screen, covering everything from the header to the footer.

5. Center Your Core Message: Concentrate on your primary message—why you’re introducing this particular design and the underlying process behind it.

6. Client Q&A Etiquette: During design discussions, clients often pose numerous questions. It’s essential to attentively listen to their queries and respond politely. If you’re unsure about a particular point, kindly express, “I’m not certain about this at the moment, but I’ll certainly follow up with you to provide a thorough response.”

These are the key points you should embrace to excel in your presentation. With these thoughts in mind, I’m signing off and will be back soon with a new, engaging blog post.

About the Author: Madhuri Vinchurkar is a passionate UI/UX designer working at Mantra Labs. With a keen eye for creating seamless and visually captivating digital experiences, she has honed her skills in crafting user-centered designs that not only look great but also offer intuitive interactions.

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Conversational UI in Healthcare: Enhancing Patient Interaction with Chatbots

As healthcare becomes more patient-centric, the demand for efficient and personalized care continues to grow. One of the key technologies that have gained traction in this domain is Conversational UI (CUI) — a user interface where interactions occur through natural language, often with the help of chatbots. For developers, building a robust CUI in healthcare requires a balance of technical proficiency, understanding of the healthcare landscape, and empathy toward patient needs. Let’s explore how CUI can improve patient interactions through chatbots and what developers should consider during implementation.

Why Conversational UI is Gaining Popularity in Healthcare

From scheduling appointments to answering medical queries, healthcare chatbots have become vital tools for enhancing patient engagement and streamlining healthcare workflows. Conversational UIs enable these chatbots to interact with patients naturally, making them accessible even to non-tech-savvy users. By incorporating AI and NLP (Natural Language Processing), chatbots can now simulate human-like conversations, ensuring patients receive timely, relevant responses. 

Image credit: https://www.analytixlabs.co.in/blog/ai-chatbots-in-healthcare/ 

Key Areas Where Chatbots Are Revolutionizing Healthcare

  1. Appointment Scheduling and Reminders – Chatbots can automatically schedule appointments based on patient availability and send reminders before the visit, reducing no-show rates. For developers, this feature requires integration with hospital management systems (HMS) and calendar APIs. The challenge lies in ensuring secure and real-time data transfer while adhering to healthcare compliance standards like HIPAA.
  1. Medical Query Resolution– Chatbots equipped with NLP can answer common patient questions related to symptoms, medications, and treatment plans. This reduces the burden on healthcare providers, allowing them to focus on more critical tasks. Developers working on this feature need to consider integrating medical databases, such as SNOMED CT or ICD-10, for accurate and up-to-date information.
  1. Patient Monitoring and Follow-ups – Post-discharge, chatbots can monitor a patient’s condition by regularly asking for health updates (e.g., vital signs or medication adherence). Developers can integrate IoT devices, such as wearable health monitors, with chatbot platforms to collect real-time data, providing healthcare professionals with actionable insights.
  1. Mental Health Support – Chatbots have shown promise in offering mental health support by providing patients with an outlet to discuss their feelings and receive advice. Building these chatbots involves training them on therapeutic conversational frameworks like Cognitive Behavioral Therapy (CBT), ensuring they offer relevant advice while recognizing when a human intervention is required.

Key Considerations for Developers

1. Natural Language Processing (NLP) and AI Training

NLP plays a pivotal role in enabling chatbots to understand and process patient queries effectively. Developers must focus on the following:

Training Data: Start by gathering extensive datasets that include real-life medical queries and patient conversations. This ensures that the chatbot can recognize various intents and respond appropriately.

Multi-language Support: Healthcare is global, so building multi-lingual capabilities is critical. Using tools like Google’s BERT or Microsoft’s Turing-NLG models can help chatbots understand context in different languages.

Contextual Understanding: The chatbot must not just respond to individual queries but also maintain the context across the conversation. Developers can use contextual models that preserve the state of the conversation, ensuring personalized patient interactions.

2. Security and Compliance

Healthcare chatbots handle sensitive patient information, making security a top priority. Developers must ensure compliance with regulations such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S. and GDPR (General Data Protection Regulation) in Europe. Key practices include:

  • Data Encryption: All communication between the chatbot and the server must be encrypted using protocols like TLS (Transport Layer Security).
  • Authentication Mechanisms: Implement two-factor authentication (2FA) to verify patient identity, especially for sensitive tasks like accessing medical records.
  • Anonymization: To avoid accidental data breaches, ensure that the chatbot anonymizes data where possible.

3. Seamless Integration with EHR Systems

For chatbots to be truly effective in healthcare, they must integrate seamlessly with Electronic Health Record (EHR) systems. This requires a deep understanding of healthcare APIs like FHIR (Fast Healthcare Interoperability Resources) or HL7. Developers should aim to:

  • Enable Real-time Updates: Ensure that chatbot interactions (e.g., new appointment schedules, and symptom checks) are instantly reflected in the patient’s EHR.
  • Avoid Data Silos: Ensure that all systems (EHR, chatbot, scheduling system) can communicate with each other, eliminating data silos that can lead to fragmented patient information.

4. Scalability and Performance Optimization

In healthcare, downtime can be critical. Developers need to ensure that chatbots are scalable and capable of handling thousands of patient interactions simultaneously. Using cloud-based platforms (AWS, Google Cloud) that offer auto-scaling capabilities can help. Additionally, performance optimization can be achieved by:

  • Caching Responses: Store frequently used responses (such as FAQs) in memory to speed up interaction times.
  • Load Balancing: Implement load balancers to distribute incoming queries across servers, ensuring no single server is overwhelmed.

Tools and Platforms for Building Healthcare Chatbots

Several tools and platforms can aid developers in building healthcare chatbots with conversational UIs:

  1. Dialogflow (Google): Offers pre-built healthcare intents and integrates with Google Cloud’s healthcare APIs.
  2. Microsoft Bot Framework: A scalable platform that integrates with Azure services and offers AI-driven insights.
  3. Rasa: An open-source NLP tool that provides flexibility in creating highly customized healthcare bots.

Conclusion

Conversational UI in healthcare is transforming patient care by offering real-time, scalable, and personalized interactions through chatbots. However, for developers, building these systems goes beyond programming chatbots — it involves understanding the unique challenges of healthcare, from regulatory compliance to seamless integration with hospital systems. By focusing on NLP capabilities, ensuring security and privacy, and integrating with existing healthcare infrastructure, developers can create chatbots that not only enhance patient interaction but also alleviate the burden on healthcare providers.

References

  1. NLP in Healthcare: Opportunities and Challenges
  2. HIPAA Compliance for Chatbots

About the Author:

Shristi is a creative professional with a passion for visual storytelling. She recently transitioned from the world of video and motion graphics to the exciting field of product design at Mantra Labs. When she’s not designing, she enjoys watching movies, traveling, and sharing her experiences through vlogs.

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