Relocation of job
Relocation of job
A relocation occurs when you move to another city or state for a job. People relocate for jobs every day for a variety of reasons. A relocation takes a lot of thought and planning. Fortunately, you can take certain steps to evaluate whether a job-related move is right for you. And, if it is, you can begin to plan for your next home.
A relocation occurs when you move to another city or state for a job. People relocate for jobs every day for a variety of reasons. A relocation takes a lot of thought and planning. Fortunately, you can take certain steps to evaluate whether a job-related move is right for you. And, if it is, you can begin to plan for your next home.
SALEsCARE
Intelligent Assistant for Pharma Sales Representatives
A conversational AI tool empowering pharma sales reps to prepare faster, respond confidently, and engage meaningfully
OVERVIEW
SALEsCARE is your intelligent AI assistant, designed to support you at any time in preparing for and following up on your appointments. Whether you're at home, on the go, or even in the parking lot before a meeting, it is available via chat or voice, ensuring you get the insights you need quickly and efficiently for HCPs—saving you valuable time and enhancing your productivity.
MY ROLE
Researcher & UI Designer
Usability testing, User Research, Interactive Prototypes, System design, High-Fidelity Mockups
July 2024-Jan 2025
Mobile + Web (responsive)
FYI- Designed an end-to-end solution for web, iPad, and phone collaborating with product owners and stakeholders. Led usability testing across regions, refined features, and ensured seamless developer integration. Focused on conversation mapping, visual design.
STORY
In the fast-paced world of healthcare sales, Rohini a seasoned sales representative, finds herself overwhelmed by an endless stream of doctor meetings, client queries, and administrative tasks. Despite his efforts, productivity seems to stagnate, and sales targets remain out of reach. One day, during a particularly hectic week, she misses an important follow-up call, and it costs her a big sale. .
Frustrated, Rohini realises that the root of the problem isn't his skills or knowledge—it's the lack of efficient support tools.
She recognises that sales reps like her need a way to streamline their work, automate routine tasks, and access critical information quickly. With the right support, she believes, sales reps could focus more on building relationships and closing deals, ultimately driving higher sales outcomes.
To tackle this challenge, we started the project from scratch, requiring extensive research. We needed to understand how other GenAI systems function, how conversational design works, and how to track user adoption throughout the process. By diving deep into these aspects, we aimed to create a solution that seamlessly integrates into a sales rep’s workflow, ensuring efficiency, adaptability, and real impact.
THE PROBLEM
CHALLENGES TO BE SOLVED
Pharma representatives spend a significant amount of time preparing for doctor meetings — searching across multiple disconnected platforms to find:
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Previous HCP interactions
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Approved brand messaging
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Latest medical guidelines
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Competitive insights
„My territory is large and the preparation of new assigned HCPs is time-consuming“
"I feel like an investigator“
“Sometimes it‘s a challenge to find topics to talk about when you‘ve beeing seeing the doctor for years“
During a typical day, a sales rep faces inefficiencies which lead to longer working hours than required
… spends additional time at home or at the parking lot summarizing the last meetings and preparing new visits
… Needs to use many different tools to perform their daily tasks
It‘s time to change that and use state-of-the-art technology to assist the sales force in putting the customer first!
User Research
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To understand their behavior, need
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How to shape the business use case with the user needs
Requirement gathering
Insights from first Workshops
5
12
17 users
Target Customers
SalesRep/MSL
Insights from Users
Observational research
Using the observational research method, we captured farmer’s behavior in their natural environment. It helped us directly look at what farmers are actually doing, what kind of routines they could have with the application, and how the application can be used in different contexts of their lives.
This exercise helped us understand user's goals, motivations, and expectations, guiding us to address their frustrations.
RESEARCHING BOTS AND CONVERSATIONAL UI
Majority of the research for this project was to learn about conversational UI, chatbots, and how the design process fits in the system.
Have people already developed any processes?
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What are the user intents?
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What are key chatbot Output?
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What are the flows?
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What are the User feedback on friction points?
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How can we increase the engagement of the user?
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How do you write dialog?
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Chatbot platform requirements and platforms
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A peek into voice assistants and chatbots
CHATBOT PLATFORM REQUIREMENTS
Prior to trying platforms, I developed the follow criterias to grade platforms:
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Natural Language Processing (NLP): Ability to understand and process human language to enable meaningful conversations.
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User Intent Recognition: Ability to identify the purpose behind user queries to provide relevant responses.
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AI and Machine Learning: Adaptive learning from user interactions to improve responses over time.
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Customizable Flows: Ability to design and modify conversation pathways based on user needs and preferences.
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Integration Capabilities: Seamless integration with CRM, databases, APIs, and third-party tools for data access and sharing.
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Multi-language Support: Ability to support multiple languages for global reach.
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Security and Privacy: Compliance with data protection regulations (GDPR, HIPAA) and secure data handling.
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Escalation to Human Agents: Option to hand over to a live agent when the bot cannot handle complex queries.
DEFINING THE EXPEREINCE
BOT PERSONAILITY
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Tone: Friendly, professional, and context-aware (empathetic when needed, upbeat when appropriate).
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Language: Clear, concise, and jargon-free. Conversational with polite humor.
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Empathy: Acknowledge concerns, show patience, and offer reassurance in tough moments.
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Proactive: Suggest helpful actions based on context without being pushy.
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Adaptable: Tailor responses to the user’s tone, role, and familiarity.
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Authentic: Be transparent about being a bot—e.g., “I’m here to help as your assistant.”
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Error Handling: Apologize gracefully, guide toward solutions, and offer alternatives.
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Brand-Aligned: Reflect brand values—empathetic in healthcare, engaging in tech.
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Inclusive: Use culturally sensitive and inclusive language.
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Consistent: Ensure a uniform voice for trust and reliability.
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Context in which the bot operates: Sales representatives use the bot in various settings—at home, while parked in their cars, or even during commutes. The bot helps them prepare for upcoming doctor appointments, document notes after meetings, and organize those notes within the corresponding doctor’s profile.
Insights
Medical sales reps spend only 28% of their time selling, with the rest spent on admin tasks, research, and CRM updates. Personalized engagement and timely follow-ups improve doctor interactions and conversion rates. AI-driven tools help reps access medical data instantly, enhancing efficiency and compliance.
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Instant Information Access: Sales reps need quick answers on product details, compliance, and customer history. A well-designed chatbot with natural language processing (NLP) reduces search friction and improves response time.
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Seamless Workflow Integration – Context switching between CRMs, emails, and notes disrupts productivity. A chatbot that integrates smoothly with existing tools can automate admin tasks and suggest relevant next steps.
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Adaptive Learning & Personalization – Sales reps have different expertise levels and selling styles. An AI-driven chatbot that learns from interactions and provides tailored suggestions enhances efficiency and confidence over time.
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Onboarding
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Customization
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Key features
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Self -serve features
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In app flows to show new or used features
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User feedback on friction points
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A/b testing
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Re-engage with inactive users
User Adoption
Execute
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To understand their behavior, need
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How to shape the business use case with the user needs
MAPPING THE CONVERSATION
Before adding the conversation to Motion.ai, I first wrote it in Google Docs to spell-check the dialogue and ensure I had a backup of my work.
FROM MARKET (STRUCTRURE HCPs)
New HCPs
Primary Goal:
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Establish mutual trust and respect as a foundation for partnership
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Adopt a CES mindset to position as a valuable partner.
CONVERSATION GUIDELINE FOR BOT
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Here’s a concise set of conversation rules and guidelines for a bot:
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Clarity: Use simple, jargon-free language. Avoid ambiguity.
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Relevance: Respond to queries accurately and stay on topic.
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Tone: Maintain a friendly, professional, and empathetic tone.
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Conciseness: Keep responses brief but informative.
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Adaptability: Adjust tone and detail based on user needs.
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Consistency: Use uniform language and behavior across interactions.
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Transparency: Acknowledge limitations and provide alternatives if unable to assist.
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Proactivity: Anticipate needs and offer helpful suggestions when appropriate.
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Privacy: Avoid requesting or storing sensitive information unnecessarily.
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Feedback: Encourage user feedback to improve performance.
Key Information to Gather:
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General Details: Location, specialty, and visit preferences (when and how).
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Behavioural Style: Openness, patient-focus, or scientific-focused.
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Professional Insights: Early adopter behavior, potential, and topics of mutual interest.
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Treatment Preferences: Existing preferences and familiarity with our product.
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Decision Triggers: Key criteria for prescribing.
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Network Connections: Relationships with other HCPs and influence within the medical community (e.g., mentoring younger specialists, speaking at congresses).
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Public Engagement: Congress participation and speaker reputation (e.g., check congress agendas).
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Competitor Activity: Interactions with competitors (via discussions with HCPs or CES colleagues).
QUESTIONNAIRE SUMMARIZED FOR HCPs in CHATBOT
KEY FEATURES DEVELOPED
Conversation history
In a chatbot, conversation history helps maintain context, enabling personalized responses, continuity, and reducing repetitive inputs for a smoother user experience.
Key UX considerations include:
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Persistence & Recall: Retaining relevant past interactions for a smoother experience.
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Privacy & Compliance: Ensuring sensitive data is handled securely, especially in regulated industries like pharma.
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User Control: Allowing reps to review, edit, or delete history when needed.
Recommendations
Recommendation questions in a chatbot should be context-aware, concise, and action-driven, guiding users toward relevant insights with minimal effort. They should adapt based on user input, offering personalized and intuitive responses while ensuring clarity and efficiency.
Feedback
- user feedback on friction points and what they plan to accomplish with your tool
Collecting customer feedback from users is the most accurate way your team can identify growth and adoption tactics for your product.
We can use digital adoption platforms, chatbots, or survey tools to consistently gather insight from users regarding their experience with your product and what we can do to improve it. With these tools, we can also target your feedback collection at points in the product journey where you’ve noticed lower levels of engagement.
VISUAL GUIDELINE GLIMPSE
The visual design emphasizes clarity and accessibility, using earthy tones, icon-driven navigation, and high-contrast text for readability in outdoor conditions. Imagery focuses on real-life farming scenarios, reinforcing trust and relatability. The UI elements prioritize essential information, ensuring a seamless and efficient user experience tailored to the needs of Indian farmers
With an intuitive interface, we ensure ease of use for farmers, integrating regional languages and simple navigation.
PERSPECTIVE
WHERE DO WE STAND NOW? WHAT's THE NEXT STEP?
Usability Study
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Give users what they are searching for
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Upfront Data availability
Testing -Mandi feature
ITALY
Target Customer
Sales rep
11 Users
Participated in the test
Test Time
Self-determined use of the AI assistant for 1 week
Feedback
Online questionnaire & online meeting
Pains
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Response Time: The responses were often slow.
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Accuracy: Many of the answers provided were incorrect in several areas.
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Value: I haven't found any significant value or useful information yet.
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Prompt Dependency: The quality of results seemed to vary greatly depending on how the prompts were worded.
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Relevance: There was a lack of information about relevant doctors.
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Email & Newsletters: These seemed to be treated inconsistently.
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Knowledge Gaps: The chatbot often lacked knowledge and offered irrelevant suggestions.
Gains
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Effortless Management: Streamline tasks for easy handling.
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Time Efficiency: Maximize time between client interactions.
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Simplified Processes: Reduce complexity for smoother workflows.
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Quick Access to Doctor Information: Easily retrieve relevant details about doctors.
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Centralized Control: One contact point to manage everything efficiently.
Missing piece
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Operating hours and consultation availability
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Contact number
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Past interactions or activities
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Email contact
REFINEMENT
When the bot is live, it can respond to all of your queries.
Hi Bot, could you provide a summary of the HCP I’ll be visiting next
Certainly, here's a brief overview of Dr. Sayoine. She is...
Future bot with a holographic interface, blending cutting-edge technology with seamless user interaction
Hello Bot, please record the following details of my discussion with Dr. Bhowmik.