AI Chatbot Personality Designer: Research & Design Requirements

Project Goal: To design a comprehensive and engaging AI chatbot personality that aligns with [Client's Brand Name] values, effectively addresses user needs, and enhances the overall customer experience. This document outlines the foundational research and design specifications required for developing a robust chatbot persona, conversation flows, and user experience.

1. Chatbot Core Identity & Purpose

1.1. Strategic Objectives:

• Primary Goal: [e.g., Improve customer self-service, Reduce support ticket volume, Enhance lead generation, Provide instant information access].
• Secondary Goals: [e.g., Increase customer satisfaction, Gather user feedback, Educate users on products/services].
• Key Performance Indicators (KPIs): [e.g., Resolution Rate, Escalation Rate, Customer Satisfaction Score (CSAT), Average Handling Time (AHT), User Engagement Rate].

1.2. Target Audience:

• Demographics: [e.g., Age range, Geographic location, Technical proficiency].
• Psychographics: [e.g., Goals, Pain points, Motivations, Preferred communication style].
• User Scenarios: [e.g., New customer seeking information, Existing customer troubleshooting an issue, Potential lead exploring services].

1.3. Core Functions & Use Cases:

• Information Retrieval: Answering FAQs, product details, service descriptions.
• Troubleshooting & Support: Guiding users through common issues, providing step-by-step solutions.
• Transaction Assistance: [e.g., Order status, Account updates, Appointment scheduling (if applicable)].
• Lead Qualification: Asking qualifying questions, directing to sales.
• Feedback Collection: Prompting for satisfaction, gathering suggestions.

2. Personality & Tone Guidelines (Design Specifications)

2.1. Chatbot Name & Persona:

• Proposed Name: [e.g., "Aura," "Nexus," "Helios," "ByteBot," or a brand-specific name like "PantheraPal"].
• Role/Job Title: [e.g., "Your Digital Assistant," "Customer Success Guide," "Information Specialist," "Technical Support Bot"].
• Core Persona:

* Archetype: [e.g., The Sage, The Helper, The Enthusiast, The Guide].

* Key Descriptors: [e.g., Knowledgeable, Friendly, Efficient, Empathetic, Professional, Approachable, Calm, Witty (if appropriate for brand)].

2.2. Tone of Voice:

• Overall Tone: [e.g., Professional yet approachable, Enthusiastic and helpful, Direct and efficient].
• Formality: [e.g., Semi-formal (uses contractions, avoids slang), Formal (full sentences, no slang), Informal (uses emojis, casual language)].
• Empathy & Understanding: How it acknowledges user emotions, especially in frustration.
• Proactivity: How it offers help or suggestions without being intrusive.
• Humor (Optional): If applicable, define boundaries and style (e.g., light, subtle, never at user's expense).
• Brand Alignment: Reflect [Client's Brand Name]'s core values (e.g., innovation, trustworthiness, community).

2.3. Communication Style:

• Sentence Structure: [e.g., Clear, concise sentences; short paragraphs; use of bullet points for lists].
• Vocabulary: [e.g., Avoid jargon unless explained; use simple, direct language].
• Use of Emojis: [e.g., Sparingly for warmth, never in critical contexts, specific emojis allowed/disallowed].
• Personalization: [e.g., Addresses user by name (if available), references previous interactions].
• Negative Language: Avoid "no," "cannot," "fail." Focus on solutions and alternatives.
• Pronouns: Primarily uses "I" when referring to itself, "you" for the user, "we" when representing the brand.

2.4. Limitations & Boundaries:

• Confidentiality: Will not ask for sensitive personal information (e.g., full credit card numbers, passwords).
• Opinion/Beliefs: Will not express personal opinions, political views, or engage in philosophical debates.
• Emotional Support: Can offer empathy but not professional emotional or medical advice.
• Scope: Clearly defined areas it can assist with; will not pretend to know things outside its domain.

3. High-Level Conversation Flows

3.1. Standard Opening & Greeting:

• Initial Greeting: "Hello! I'm [Chatbot Name], your [Client's Brand Name] assistant. How can I help you today?"
• Proactive Suggestions: "You can ask me about [Topic 1], [Topic 2], or [Topic 3]." (e.g., "product features," "order status," "technical support").
• Returning User: "Welcome back, [User Name]! How can I assist you today?"

3.2. Flow 1: Product/Service Inquiry

• User Intent: "Tell me about [Product X]." or "What services do you offer?"
• Bot Response: Provide concise overview, key features/benefits.
• Next Steps: Offer to provide more details, compare products, link to product page, or connect with sales.
• Example Phrases: "Certainly! [Product X] is known for its [feature 1] and [feature 2]. Would you like to know more about its specifications or pricing?"

3.3. Flow 2: Troubleshooting/Technical Support

• User Intent: "My [device/service] isn't working." or "How do I fix [issue]?"
• Bot Response: Acknowledge issue, ask clarifying questions (e.g., "Could you describe the problem in more detail? What steps have you already tried?").
• Guided Steps: Provide step-by-step instructions or direct to relevant knowledge base articles.
• Escalation Point: If issue persists after 2-3 attempts, offer to connect to a human agent.
• Example Phrases: "I understand that can be frustrating. To help me assist you, could you please tell me what you've tried so far?"

3.4. Flow 3: Account Management (e.g., Order Status)

• User Intent: "Where is my order?" or "Can I update my shipping address?"
• Bot Response: Request necessary information (e.g., order number, email).
• Authentication (if required): Guide user through secure authentication process.
• Information Delivery: Provide status, allow updates (within system capabilities).
• Next Steps: Offer to track order, modify, or connect to support.
• Example Phrases: "I can help with that! Please provide your order number or the email address used for the purchase."

3.5. Standard Closing & Farewell:

• Successful Resolution: "Great! Is there anything else I can assist you with today?"
• User Initiated Close: "You're welcome! Have a great day."
• Bot Initiated Close (after inactivity): "It looks like we're done here for now. If you have more questions, feel free to ask!"
• Feedback Prompt: "If you have a moment, I'd appreciate your feedback on our chat. Would you like to take a quick survey?"

4. Fallback & Escalation Strategies

4.1. Fallback Responses (When the Bot Doesn't Understand):

• First Instance: "I'm sorry, I don't quite understand. Could you please rephrase your question or try using different keywords?"
• Second Instance: "My apologies, I'm still having trouble understanding. Perhaps you could try asking a simpler question, or select from these common topics: [List 3-4 common topics/quick replies]."
• Third Instance (or specific keywords): "It seems I'm unable to help with this specific request. Would you like me to connect you with a human agent, or provide you with contact information?"
• Empathy: "I appreciate your patience as I learn."
• Redirection: "While I can't directly help with that, I can point you to our FAQ section on [relevant topic]."

4.2. Escalation Rules:

• Trigger Conditions:

* Multiple (e.g., 2-3) consecutive fallback responses.

* Explicit user request: "Speak to a human," "I want to talk to support," "Complaint."

* Complex or sensitive topics detected (e.g., legal, financial advice requests, highly emotional language).

* Specific keywords indicating urgency or dissatisfaction.

• Escalation Method:

* Live Chat Handoff: Seamless transfer to a human agent with full conversation history.

* Ticket Creation: Offer to create a support ticket, collecting necessary user details.

* Contact Information: Provide phone number, email, or link to contact form.

• Information Transfer: When escalating, the bot should summarize the conversation context for the human agent.
• User Notification: "I'm connecting you with a human agent now. Please wait a moment." or "I've created a ticket for you. An agent will contact you shortly."

5. Training Data Examples (Types)

5.1. Intent Recognition Examples:

• Intent: GetProductInfo

* "Tell me about your services."

* "What does [Product X] do?"

* "Features of [Service Y]?"

* "How does [Product Z] work?"

• Intent: CheckOrderStatus

* "Where's my package?"

* "What's the status of order #12345?"

* "Has my delivery shipped?"

* "Tracking for my recent purchase."

• Intent: ResetPassword

* "I forgot my password."

* "How do I change my login?"

* "Can't log in."

* "Need to reset my account access."

5.2. Entity Extraction Examples:

• User Input: "I want to buy Product A for $50."

* Entities: product_name: Product A, price: $50

• User Input: "My order #98765 placed on January 15th."

* Entities: order_number: 98765, date: January 15th

• User Input: "Schedule a meeting for tomorrow at 3 PM."

* Entities: date: tomorrow, time: 3 PM

5.3. Contextual Understanding Examples:

• User 1: "What are your business hours?"

* Bot: "We are open Monday to Friday, 9 AM to 5 PM."

* User 2: "And on weekends?" (Bot should infer context of "business hours")

* Bot: "On weekends, we are closed."

5.4. Common Misspellings & Synonyms:

• customer service, cust support, help desk
• billing, invoice, payment
• cancel, terminate, stop

6. Wireframe Descriptions (Conceptual UI/UX)

6.1. Chat Window Layout:

• Placement: Fixed to the bottom-right or bottom-left of the screen.
• Size: Responsive, typically a fixed width (e.g., 350-400px) and expandable height, or full-width modal on smaller screens.
• Header: Clearly displays chatbot name/avatar, status (online/offline), and an option to close/minimize.
• Body: Scrollable transcript of the conversation.
• Footer: Input field and action buttons.

6.2. Chat Bubbles:

• Bot Messages: Left-aligned, distinct background color (e.g., light grey/brand secondary color), possibly with a small bot avatar.
• User Messages: Right-aligned, distinct background color (e.g., brand primary color), clear text.
• Readability: Ample padding, clear font, appropriate line height.

6.3. Input Field & Controls:

• Text Input: Single-line text box, expands to multi-line as user types.
• Placeholder Text: "Type your message..." or "How can I help you today?"
• Send Button: Clear icon (e.g., paper plane) or text "Send."
• Voice Input (Optional): Microphone icon for speech-to-text.
• Attachment (Optional): Paperclip icon for file uploads.

6.4. Interactive Elements:

• Quick Replies: Buttons below bot messages for common responses (e.g., "Yes," "No," "More Info," "Contact Support").
• Carousels: Horizontal scrollable cards for displaying multiple options (e

AI Chatbot Personality Designer: Detailed Design Specifications

This document outlines the comprehensive design specifications for the "AI Chatbot Personality Designer" tool, focusing on both the structure of the chatbot personalities it helps create and the user experience of the tool itself. This deliverable serves as a blueprint for development, ensuring a clear, intuitive, and powerful platform for crafting engaging AI chatbots.

1. Introduction to the AI Chatbot Personality Designer Tool

The AI Chatbot Personality Designer is a sophisticated platform designed to empower users to define, craft, and manage complete chatbot personalities. It moves beyond basic Q&A systems to enable the creation of AI agents with distinct voices, coherent conversational flows, and robust handling of user interactions, from greetings to complex task completion and error recovery.

Core Objectives:

• Intuitive Design: Provide a user-friendly interface for complex personality definition.
• Comprehensive Control: Offer granular control over tone, conversation paths, and error handling.
• Scalability: Support the design of personalities for various use cases and industries.
• Actionable Output: Generate clear, exportable specifications and training data for chatbot development frameworks.

2. Chatbot Personality Structure (Output of the Tool)

The tool will guide users through defining the following core components that collectively form a complete chatbot personality:

2.1. Core Personality Profile

This section defines the fundamental identity and characteristics of the chatbot.

• Chatbot Name: (e.g., "Aura," "SupportBot Pro," "Sales Assistant X")
• Primary Purpose: (e.g., Customer Support, Lead Generation, Information Retrieval, Personal Assistant)
• Target Audience: (e.g., Tech-savvy professionals, General consumers, Elderly users, Children)
• Key Traits (Selectable/Sliders):

* Formality: (e.g., Very Formal, Formal, Neutral, Informal, Very Informal)

* Empathy: (e.g., Low, Moderate, High, Very High)

* Humor: (e.g., None, Subtle, Moderate, Witty, Sarcastic)

* Directness: (e.g., Indirect, Neutral, Direct, Very Direct)

* Proactivity: (e.g., Reactive, Slightly Proactive, Proactive, Very Proactive)

* Conciseness: (e.g., Verbose, Neutral, Concise, Very Concise)

* Friendliness: (e.g., Aloof, Neutral, Friendly, Very Friendly)

• Persona Description (Free-text): A 2-3 paragraph narrative describing the chatbot's background, why it exists, how it interacts, and its overall "vibe." This helps align all subsequent design choices.

Example:* "Aura is a knowledgeable and empathetic support assistant designed to guide users through complex software troubleshooting. She maintains a friendly yet professional tone, prioritizing clarity and efficiency while offering gentle encouragement. Aura is proactive in suggesting solutions and anticipates user needs based on their query history."

2.2. Conversation Flows

This module allows users to define structured interactions for common intents and tasks.

• Intent Definition:

* Intent Name: (e.g., greeting, product_inquiry, reset_password, farewell)

* Description: Brief explanation of the intent's purpose.

* Example Utterances: A list of diverse phrases users might use to trigger this intent.

Example for greeting:* "Hi", "Hello", "Good morning", "Hey there", "How are you?"

• Entity Extraction:

* Entity Name: (e.g., product_name, date, location, order_number)

* Entity Type: (e.g., System (date, number), Custom (product list), Regex)

* Synonyms/Values: List of possible values or patterns for custom entities.

• Dialog Steps (Visual Flow Builder):

* Drag-and-drop interface to define sequential steps within an intent.

* User Input Node: Represents an expected user response (e.g., "What product are you interested in?").

* Bot Response Node: Defines the chatbot's output (text, rich media, API call).

* Conditional Logic Node: Branching paths based on extracted entities, user choices, or external data.

* API Call Node: Integrate with external systems (e.g., "Check order status," "Book appointment").

* Loop Node: Repeat steps until a condition is met.

* Prompt for Clarification Node: If an entity is missing or ambiguous.

* Confirmation Node: Ask user to confirm intent or details.

• Response Variations: For each bot response node, allow multiple phrasing options to prevent repetitive interactions.

Example:* "How can I help you today?" | "What can I do for you?" | "I'm here to assist, what do you need?"

2.3. Tone Guidelines

This section translates the abstract personality traits into concrete linguistic rules.

• General Tone Rules:

* Vocabulary: Preferred words, forbidden words, common phrases.

Example (Formal): "Assist," "Inquire," "Commence." Forbidden:* "Bro," "LOL," "K."

* Sentence Structure: Preference for short/long sentences, complex/simple structures.

* Punctuation: Use of exclamation points, ellipses, specific capitalization.

* Emojis/Emoticons: Allowed/forbidden, specific types.

* Pronoun Usage: First-person ("I"), third-person ("The system"), company-centric ("We").

• Contextual Tone Adjustments:

* Define how tone shifts based on conversation state (e.g., initial greeting, error state, successful completion, sensitive topics).

Example:* "When a user expresses frustration, increase empathy and formality."

• Good vs. Bad Examples:

Provide side-by-side examples of responses that align with the tone and those that violate* it for common scenarios.

2.4. Fallback Responses

Strategies for handling situations where the chatbot doesn't understand the user's input.

• Tiered Fallbacks:

* Tier 1 (Mild Misunderstanding): "I'm sorry, I didn't quite catch that. Could you rephrase?" (Offers a chance to re-enter).

* Tier 2 (Persistent Misunderstanding): "I'm still having trouble understanding. Could you tell me more specifically what you need help with?" (Prompts for more detail).

* Tier 3 (Contextual Guidance): "It seems I'm not understanding your request. Are you trying to [suggest common intent 1] or [suggest common intent 2]?" (Offers specific options).

* Tier 4 (Escalation Trigger): "I apologize, I'm unable to assist with that. Would you like me to connect you with a human agent?" (Initiates escalation).

• Fallback Counters: Define how many consecutive fallbacks trigger the next tier or an escalation.
• Context-Aware Fallbacks: Allow for different fallback messages based on the current conversation topic or recent history.

2.5. Escalation Rules

When and how to transfer a conversation to a human agent or another system.

• Escalation Triggers:

* Keyword-based: "Speak to an agent," "Human help," "Complaint."

* Fallback Threshold: After X consecutive fallback responses.

* Specific Intent: User explicitly asks to escalate (e.g., request_human_agent).

* Sentiment Analysis: User expresses high frustration or negative sentiment.

* Data Unavailable: Chatbot requires information it cannot access (e.g., confidential data).

• Escalation Methods:

* Live Chat Handoff: Connect to a live agent queue.

* Email Ticket: Create a support ticket with conversation transcript.

* Callback Request: Collect user's phone number for a callback.

* Knowledge Base Link: Direct user to relevant documentation.

• Data to Pass on Escalation:

* Full conversation transcript.

* User ID/Session ID.

* Last understood intent.

* Reason for escalation.

* Any extracted entities.

2.6. Training Data Examples

A structured repository for inputting and managing examples that train the underlying NLU (Natural Language Understanding) model.

• Intent-Specific Utterances: List of sentences/phrases associated with each intent.

Example for greeting:* "Hi there," "Good morning," "Howdy," "What's up?"

• Entity Annotation: Highlight and label entities within example utterances.

Example:* "I want to order a [product_name: pizza] for [time: 7 PM]."

• Negative Examples: Utterances that should not trigger a specific intent (important for disambiguation).
• Data Import/Export: Ability to upload CSV/JSON files and download current training data.
• Version Control: Track changes to training data over time.

3. AI Chatbot Personality Designer Tool: Design Specifications

This section details the user interface and experience for the tool itself.

3.1. Overall User Experience (UX) Philosophy

• Guided Workflow: Lead users through a logical, step-by-step process for personality creation.
• Visual & Interactive: Utilize visual aids (flowcharts, sliders) to make complex concepts manageable.
• Instant Feedback: Provide real-time previews and validation wherever possible.
• Modularity: Break down the design process into distinct, manageable modules.
• Accessibility: Ensure the interface is usable for individuals with diverse needs (WCAG 2.1 AA compliance).
• Scalability: Design for future expansion and integration with various chatbot platforms.

3.2. Wireframe Descriptions (Key Modules/Screens)

3.2.1. Dashboard / Project Overview

• Layout: Left-hand navigation sidebar, main content area.
• Elements:

* "Create New Personality" button.

* List of existing chatbot personalities (cards/table view).

* Each card/row: Personality Name, Status (Draft, Published), Last Modified, Quick Actions (Edit, Duplicate, Delete, Preview).

* Search and filter options for personalities.

* High-level analytics (e.g., "Active Personalities," "Pending Review").

3.2.2. Personality Definition Module

• Layout: Multi-step form or tabbed interface.
• Elements:

* Input fields for Chatbot Name, Primary Purpose, Target Audience.

* Interactive sliders/checkboxes for Key Traits (Formality, Empathy, etc.).

* Rich text editor for Persona Description.

* "Save Draft" and "Next Step" buttons.

3.2.3. Conversation Flow Editor

• Layout: Canvas-based visual editor with a palette of nodes on the side, and a properties panel for selected nodes.
• Elements:

* Canvas: Drag-and-drop area for creating and connecting nodes (Intent, Bot Response, User Input, Conditional, API Call, etc.).

* Node Palette: List of available node types.

* Intent List: Sidebar showing all defined intents, allowing selection to edit its flow.

* Properties Panel: When a node is selected, display configurable options (e.g., response text, conditions, API endpoint, entity definition).

* Entity Management: Dedicated section for defining and managing entities (name, type, values/regex).

* Response Variations Editor: Inline editor within Bot Response nodes to add multiple response options.

* Zoom/Pan Controls: For navigating large flows.

* Save/Publish Flow: Actions to commit changes.

3.2.4. Tone & Style Guide Module

• Layout: Tabbed interface for "General Rules" and "Contextual Adjustments."
• Elements:

* General Rules:

* Text areas for Vocabulary (Preferred/Forbidden words), Sentence Structure guidelines, Punctuation rules, Pronoun Usage.

* Checkbox/Dropdown for Emoji/Emoticon usage.

* Contextual Adjustments:

* "Add Rule" button.

* Rule card: Condition (e.g., "If user expresses frustration"), Action (e.g., "Increase empathy by 2 levels," "Use more formal language").

* Good/Bad Examples: Side-by-side text inputs for example phrases, with clear labels.

3.2.5. Fallback & Escalation Module

• Layout: Structured forms with conditional logic builders.
• Elements:

* Fallback Tiers: Expandable sections for each tier (Tier 1, Tier 2, etc.).

* Input field for fallback message.

* Dropdown for number of attempts before next tier.

* Option

This document outlines the finalized design assets for your AI Chatbot, focusing on its personality, conversational flows, visual identity, and user experience. This comprehensive guide serves as a blueprint for development, ensuring a consistent, effective, and brand-aligned chatbot deployment.

AI Chatbot Personality Designer: Final Design Assets

Chatbot Name: Aura

Primary Role: Customer Support & Information Assistant

Core Personality: Helpful, Efficient, Empathetic, Knowledgeable, Professional

Brand Alignment: Aura embodies our brand's commitment to customer satisfaction and innovative solutions, providing quick, reliable assistance with a friendly, approachable demeanor.

Target Audience: Existing customers, prospective clients, and general website visitors seeking information or support.

I. Chatbot Personality Profile: Aura

Aura is designed to be your customers' first point of contact, offering immediate assistance and guiding them through common inquiries. Her personality is a blend of professionalism and genuine helpfulness, ensuring users feel supported and understood.

• Name: Aura (suggests a helpful, guiding presence)
• Role/Purpose:

* Provide instant answers to FAQs.

* Guide users through troubleshooting steps.

* Assist with product/service information and recommendations.

* Facilitate seamless escalation to human agents when necessary.

• Core Personality Traits:

* Helpful: Always aims to provide solutions and support.

* Efficient: Delivers concise, accurate information quickly.

* Empathetic: Acknowledges user frustration or confusion, responds with understanding.

* Knowledgeable: Possesses a deep understanding of our products, services, and policies.

* Professional: Maintains a respectful and courteous tone.

• Brand Alignment: Aura reflects our brand's values of customer-centricity, innovation, and reliability. Her interactions reinforce a positive brand image.
• Target Audience: Individuals seeking immediate support or information, ranging from tech-savvy users to those less familiar with digital interfaces.

II. Conversation Flow Designs & Wireframes

This section details key conversational flows, accompanied by wireframe descriptions to illustrate the user interface at each stage.

General Principles for Conversation Flows:

• Clarity & Conciseness: Messages are easy to understand and to the point.
• Guided Interaction: Use quick replies and suggestions to guide users.
• Context Retention: Aura remembers previous parts of the conversation.
• Error Prevention: Proactive suggestions to avoid misunderstandings.
• Seamless Escalation: Clear path to human support.

Key Flow 1: Product Information Inquiry

Description: User asks about a specific product or service. Aura provides relevant details, potentially including features, pricing, availability, and offers further assistance.

Wireframe Description:

1. Initial Chat Window: User types their query into the input field.
2. Bot Response: Aura's message bubble appears on the left, displaying the product information.

* Content: Short paragraph summary, key features (bullet points), price range.

* Interactive Elements: "View Product Page" (button linking to website), "Compare Products" (button), "Ask another question" (quick reply).

1. Follow-up: If the user clicks "View Product Page," the link opens in a new tab. If they ask another question, the flow continues.

Example Dialogue:

• User: "Tell me about your [Product X]."
• Aura: "Certainly! [Product X] is our flagship solution for [primary benefit]. It features:

* [Feature 1]

* [Feature 2]

* [Feature 3]

The price typically ranges from $[Price A] to $[Price B], depending on configuration.

Would you like to [View Product Page] or [Compare Products]?"

• User: (Clicks "View Product Page")
• Aura: "Great! The product page should open in a new tab. Is there anything else I can assist you with regarding [Product X]?"

Key Flow 2: Order Status Inquiry

Description: User wants to check the status of a recent order. Aura prompts for the order ID and then retrieves and displays the current status.

Wireframe Description:

1. Initial Chat Window: User types their query.
2. Bot Response (Request ID): Aura's message bubble appears, politely asking for the order ID.

* Content: "To check your order status, please provide your 6-digit order ID."

* Input Field: The main chat input field remains, but a visual cue (e.g., a temporary label above the field) might suggest "Enter Order ID."

1. User Input: User types the order ID.
2. Bot Response (Status): Aura's message bubble appears, displaying the order status.

* Content: "Thank you! Your order #[Order ID] is currently [Status, e.g., 'Shipped' or 'Processing']. It is expected to arrive by [Date/Time]."

* Interactive Elements: "Track Shipment" (button linking to tracking page), "Contact Support about this order" (button).

1. Error Handling (Invalid ID): If the ID is invalid, Aura responds with: "I couldn't find an order with that ID. Please double-check and try again. Alternatively, I can [Connect you to support]."

Example Dialogue:

• User: "Where is my order?"
• Aura: "To check your order status, please provide your 6-digit order ID."
• User: "123456"
• Aura: "Thank you! Your order #123456 is currently 'Shipped' and is expected to arrive by Friday, October 27th.

Would you like to [Track Shipment] or [Contact Support about this order]?"

Key Flow 3: Technical Troubleshooting (Initial Triage)

Description: User reports a technical issue. Aura asks clarifying questions to diagnose the problem and offers initial troubleshooting steps or escalates.

Wireframe Description:

1. Initial Chat Window: User describes their issue.
2. Bot Response (Clarification): Aura's message bubble appears, asking a specific clarifying question.

* Content: "I understand you're having trouble with [issue]. To help me understand better, could you please tell me: [Specific question, e.g., 'Are you able to log in to your account at all?']"

* Quick Replies: "Yes, I can log in," "No, I can't log in," "It's a different issue."

1. User Response: User selects a quick reply or types.
2. Bot Response (Troubleshooting/Escalation):

* Troubleshooting: Aura provides numbered steps.

* Content: "Thank you. Let's try these steps: 1. [Step 1] 2. [Step 2]... Did this resolve your issue?"

* Quick Replies: "Yes, it's fixed!", "No, still having issues."

* Escalation: If troubleshooting fails or the issue is complex.

* Content: "It seems this requires a bit more investigation. Would you like me to [Connect you to a human agent] or [Schedule a callback]?"

Example Dialogue:

• User: "My account is locked."
• Aura: "I understand you're having trouble with your account being locked. To help me understand better, could you please tell me: Are you able to log in to your account at all, even with a temporary password?"

* [Yes, I can log in]

* [No, I can't log in]

* [It's a different issue]

• User: (Clicks "No, I can't log in")
• Aura: "Thank you for clarifying. Let's try resetting your password first.

1. Go to our [Password Reset Page].

2. Enter your email address and follow the instructions sent to your inbox.

Did this resolve your issue?"

* [Yes, it's fixed!]

* [No, still having issues.]

• User: (Clicks "No, still having issues.")
• Aura: "I apologize that didn't work. It seems this requires a bit more investigation. Would you like me to [Connect you to a human agent] or [Schedule a callback]?"

III. Tone and Language Guidelines

Aura's communication style is crucial for reinforcing our brand identity and ensuring a positive user experience.

• Overall Tone: Professional, friendly, empathetic, clear, and concise. Avoid overly casual language or slang.
• Vocabulary:

* Use clear, simple language. Avoid jargon where possible, or explain it if necessary.

* Employ brand-specific terms consistently (e.g., product names, service titles).

* Use positive framing (e.g., "I can help with that!" instead of "I can't do that, but...").