Cody Scott
Design portfolio
Available
Adaptive Conversational UX
Decreased average resolution times of cutomer support interactions
Decreased average resolution times of cutomer support interactions
Decreased average resolution times of cutomer support interactions
Conversational UX
Conversational UX
Conversational UX
Overstock
Overstock
Overstock
1 month
1 month
1 month
Retail Tech
Retail Tech
Retail Tech
Context
Overstock customers faced long wait times in the customer service chat window. The mission: slash these wait times by designing a chatbot for handling common queries. The hypothesis was designing a chatbot experience with personalized assistance through simple interactions has the potential to decrease wait time. This was a cross-functional team including design, product, engineering, and customer support.
Context
Overstock customers faced long wait times in the customer service chat window. The mission: slash these wait times by designing a chatbot for handling common queries. The hypothesis was designing a chatbot experience with personalized assistance through simple interactions has the potential to decrease wait time. This was a cross-functional team including design, product, engineering, and customer support.
Context
Overstock customers faced long wait times in the customer service chat window. The mission: slash these wait times by designing a chatbot for handling common queries. The hypothesis was designing a chatbot experience with personalized assistance through simple interactions has the potential to decrease wait time. This was a cross-functional team including design, product, engineering, and customer support.
Stack
Market & Business Vision
Seamless integration with Google’s Dialogflow was just the start. We optimized costs, protected sensitive data, and ensured the chatbot became a true extension of Overstock’s brand smart, responsive, and always improving.
Market & Business Vision
Seamless integration with Google’s Dialogflow was just the start. We optimized costs, protected sensitive data, and ensured the chatbot became a true extension of Overstock’s brand smart, responsive, and always improving.
Market & Business Vision
Seamless integration with Google’s Dialogflow was just the start. We optimized costs, protected sensitive data, and ensured the chatbot became a true extension of Overstock’s brand smart, responsive, and always improving.
Design Goals
A chatbot should feel helpful, not like talking to a wall. We made interactions personal, quick, and efficient cutting wait times while ensuring users felt heard, not dismissed.
Design Goals
A chatbot should feel helpful, not like talking to a wall. We made interactions personal, quick, and efficient cutting wait times while ensuring users felt heard, not dismissed.
Design Goals
A chatbot should feel helpful, not like talking to a wall. We made interactions personal, quick, and efficient cutting wait times while ensuring users felt heard, not dismissed.
User Insights & Behavioral Patterns
Typing out a problem isn’t always easy. Users struggled with phrasing, felt frustrated by robotic responses, and endured long waits for support. Our solution? A chatbot that listens, understands, and adapts.
User Insights & Behavioral Patterns
Typing out a problem isn’t always easy. Users struggled with phrasing, felt frustrated by robotic responses, and endured long waits for support. Our solution? A chatbot that listens, understands, and adapts.
User Insights & Behavioral Patterns
Typing out a problem isn’t always easy. Users struggled with phrasing, felt frustrated by robotic responses, and endured long waits for support. Our solution? A chatbot that listens, understands, and adapts.
Artifacts
I learned about the challenges our users encountered through user interviews and behavior analysis. Understanding the frustrations caused by prolonged wait times became the base of the content strategy. I wanted to design dynamic content for prompt query resolution with key info, ensuring a personalized touch for each user.
Artifacts
I learned about the challenges our users encountered through user interviews and behavior analysis. Understanding the frustrations caused by prolonged wait times became the base of the content strategy. I wanted to design dynamic content for prompt query resolution with key info, ensuring a personalized touch for each user.
Artifacts
I learned about the challenges our users encountered through user interviews and behavior analysis. Understanding the frustrations caused by prolonged wait times became the base of the content strategy. I wanted to design dynamic content for prompt query resolution with key info, ensuring a personalized touch for each user.
Deliverables
Following the beta testing phase, we launched the first version of the chatbot. Initial user feedback was overwhelmingly positive, and this success can be attributed to the version's focus on handling fundamental customer queries such as return/refund status, order updates, product information, and links to help guides. The beta testing period played a crucial role in this success, allowing the chatbot engine to make and learn from critical mistakes before engaging with the entire customer base.
Deliverables
Following the beta testing phase, we launched the first version of the chatbot. Initial user feedback was overwhelmingly positive, and this success can be attributed to the version's focus on handling fundamental customer queries such as return/refund status, order updates, product information, and links to help guides. The beta testing period played a crucial role in this success, allowing the chatbot engine to make and learn from critical mistakes before engaging with the entire customer base.
Deliverables
Following the beta testing phase, we launched the first version of the chatbot. Initial user feedback was overwhelmingly positive, and this success can be attributed to the version's focus on handling fundamental customer queries such as return/refund status, order updates, product information, and links to help guides. The beta testing period played a crucial role in this success, allowing the chatbot engine to make and learn from critical mistakes before engaging with the entire customer base.
Common queries
Starting a Conversation
Product Suggestions
Order Summary
Return Management
Common queries
Starting a Conversation
Product Suggestions
Order Summary
Return Management
Common queries
Starting a Conversation
Product Suggestions
Order Summary
Return Management
Key Results & Takeaways
📊 Strategic Design: My design process involved in-depth research and analysis of quantitative data to ensure every detail served a purpose.
👇🏾 Human Touch Matters: While our chatbot was helpful, we acknowledged that some customers will always prefer the familiarity of live agents. Balancing technology with human touch remained a cornerstone of our approach.
🚀 Beta Testing Wisdom: The beta testing phase wasn't just a formality; it was the secret sauce. It allowed our chatbot to learn, adapt, and fine-tune its performance, ensuring it entered the customer arena with confidence and precision.
Key Results & Takeaways
📊 Strategic Design: My design process involved in-depth research and analysis of quantitative data to ensure every detail served a purpose.
👇🏾 Human Touch Matters: While our chatbot was helpful, we acknowledged that some customers will always prefer the familiarity of live agents. Balancing technology with human touch remained a cornerstone of our approach.
🚀 Beta Testing Wisdom: The beta testing phase wasn't just a formality; it was the secret sauce. It allowed our chatbot to learn, adapt, and fine-tune its performance, ensuring it entered the customer arena with confidence and precision.
Key Results & Takeaways
📊 Strategic Design: My design process involved in-depth research and analysis of quantitative data to ensure every detail served a purpose.
👇🏾 Human Touch Matters: While our chatbot was helpful, we acknowledged that some customers will always prefer the familiarity of live agents. Balancing technology with human touch remained a cornerstone of our approach.
🚀 Beta Testing Wisdom: The beta testing phase wasn't just a formality; it was the secret sauce. It allowed our chatbot to learn, adapt, and fine-tune its performance, ensuring it entered the customer arena with confidence and precision.
Recent Work
Available for Work
Available for Work