Tarrabiz: Designing Guided Conversations That Simplify Finance for Small Businesses
As a Generative AI Conversation Designer, I was responsible for creating a comprehensive, confidence-building guidance flow for Tarrabiz. My focus was on simplifying complex financial and technical concepts while guiding users seamlessly through key tasks.
To achieve this, I leveraged Natural Language Understanding, Large Language Models, and Application Programming Interfaces to design responsive, user-centered interactions. My process involved analyzing conversation transcripts to identify top user needs and call drivers, reviewing existing knowledge base content, and structuring clear, intuitive dialogue flows.
I also applied prompt engineering, intent modeling, and continuous refinement through Quality Assurance and User Acceptance Testing to ensure the experience remained accurate, helpful, and easy to navigate.
Scenario 1: “When do I get paid?” (Payment setup anxiety)
Scenario 2: “I don’t understand” (Error Handling)
Scenario 3: “This is too much!” (Feature Overwhelm)
Scenario 4: “Am I doing this right?” (Confidence Gap)
User Challenge
A new user wants to set up payments but:
Doesn’t understand the required steps.
Fears “doing it wrong.”
Is intimidated by financial language
My approach:
Sets expectation (time = reduces uncertainty)
Uses reassurance (“I’ll guide you”)
Avoids jargon
Scenario: “When do I get paid?” Contd.
I ensure the Tarra bot boosts the user’s confidence by reinforcing their choice and using a light, positive tone without being unprofessional. It’s also crucial to reduce pressure by giving the user full control of the process.
Scenario: “When do I get paid?” (Setup completion)
The Tarra bot celebrates task completion to reinforce progress while smoothly guiding the user toward the next meaningful action.
User Challenge
A user enters a query that the chatbot doesn’t understand and:
Hits a dead-end response with no clear next step
Feels frustrated and unsure how to proceed
Drops off due to lack of guidance
My approach:
Reframes fallback from limitation to guidance (“Here’s what I can help with…”)
Introduces quick-reply options to reduce friction and guide next steps
Keeps responses actionable and user-focused to encourage continuation
User Challenge
User logs in and sees too many features:
Invoicing
Automation
Analytics
Customer management
They don’t know where to start.
My approach:
The proactive Tarra bot replaces dashboard overwhelm with guided entry points
Frames features as user goals, not system capabilities
Scenario: “This is too much!” Contd.
The Tarra bot is designed subtly to educate users while keeping choices limited to reduce cognitive load.
Scenario: “This is too much!” Contd.
The Tarra bot continues to maintain the momentum of setting time expectations while focusing on plain language as opposed to rules and logic.
User Challenge
User completes a task but feels unsure:
“Did I set this up correctly?”
“Will this work?”
My approach:
Validates user first (confidence).
Uses checklist format (clarity).
Highlights improvement gently.
Scenario: “Am I doing this right?” Contd.
The Tarra bot suggests improvement and includes a clear benefit to the user. It also avoids sounding too corrective or critical.
Impact
The redesigned conversational experience for Tarrabiz led to a 25% increase in successful payment setups, as users were guided through complex processes with clear, step-by-step support that reduced drop-offs. By simplifying financial language and proactively addressing user needs, the experience also drove a 20% improvement in task completion rates across key features like invoicing and automation. Customer satisfaction saw a notable lift, with CSAT increasing by 17%, reflecting more intuitive, confidence-building interactions. Additionally, guided prompts and contextual recommendations contributed to a 30% increase in feature adoption (such as automation and payment reminders), ultimately positioning Tarrabiz as a more accessible, trustworthy platform for small business users.