Rosenverse

This video is only accessible to Gold members. Log in or register for a free Gold Trial Account to watch.

Log in Register

Most conference talks are accessible to Gold members, while community videos are generally available to all logged-in members.

Optimizing AI Conversations: A Case Study on Personalized Shopping Assistance Frameworks
Gold
Tuesday, June 10, 2025 • Designing with AI 2025

This video is featured in the Designing with AI 2025 playlist.

Share the love for this talk
Optimizing AI Conversations: A Case Study on Personalized Shopping Assistance Frameworks
Speakers: Kritika Yadav
Link:

Summary

The Challenge Users engaging with the AI shopping assistant often felt constrained by limited options, excessive follow-up questions, and a lack of personalization. These shortcomings led to user fatigue, misunderstandings, and a subpar shopping experience. Insights from user research (UXR) and transcripts revealed that users wanted more intuitive, human-like interactions that catered to their unique needs. The Solution A robust, adaptable framework was designed to transform AI conversations into sales-like consultations. By breaking user queries into three core components—use-case, constraints, and preferences—the framework enabled the bot to understand intent and deliver relevant, personalized results. Key enhancements included: Allowing users to skip questions and navigate freely. Providing contextual help for technical queries. Transitioning to open-ended interactions after gathering essential details to prevent over-questioning. Displaying diverse and curated results aligned with user preferences.

Key Insights

  • Traditional conversational AI severely limits visual bandwidth compared to traditional e-commerce interfaces, hindering effective product exploration.

  • The catalog exploration paradox highlights the tension between rich visual browsing and conversational limitations in AI assistants.

  • The expectation gap occurs when AI fails to understand cultural or contextual nuances, eroding user trust and satisfaction.

  • User queries vary widely in specificity; treating all queries the same is a missed opportunity in AI design.

  • Structuring user queries into use case, constraints, and preferences enables AI to perform intelligent reasoning like a skilled salesperson.

  • Carefully crafted prompt design, rather than large-scale fine tuning, can effectively guide LLM reasoning for better conversational AI.

  • Adaptive questioning avoids unnecessary or repetitive queries, improving user experience and reducing frustration.

  • Designing conversational AI as reasoning systems rather than linear scripted flows fundamentally improves interaction quality.

  • A multidisciplinary team combining design, data, and engineering perspectives was crucial to solving this AI conversation challenge.

  • Shifting from seeing AI as a task execution tool to a trusted, empathetic guide changes user perception and engagement positively.

Notable Quotes

"We are designing how the assistant is trying to reason, moving from scripting responses to orchestrating the AI's cognitive process."

"It's not just about fixing the chatbot, it's about bridging the gap between user expectations and actual experiences."

"LLMs don't just match keywords or labels. They infer meaning, extract subtle nuances, and understand intent behind words."

"The catalog exploration paradox shows how current conversational AI restricts browsing and comparison, creating uncertainty."

"Users frequently felt overwhelmed and misunderstood; this was a significant barrier to a positive shopping experience."

"What if we actively taught the model how to break down and analyze queries like a skilled salesperson would?"

"The AI assistant starts with reasoning and not results, engaging users in intelligent conversation to understand needs."

"Don't design for a response, design for reasoning. Teach AI to think critically, analyze information, and arrive at logical conclusions."

"The assistant asks open-ended questions that focus on what truly matters: performance, budget, and preferences."

"We saw a 2.5 times increase in active monthly users and a 1.5 times increase in purchases attributed to the AI assistant."

Ask the Rosenbot
Robert Reimann
Taming Design Complexity with UX Models
2017 • Enterprise Experience 2017
Gold
Kristin Wisnewski
Measuring What Matters
2019 • DesignOps Summit 2019
Gold
Dorelle Rabinowitz
The Magic Word is Trust
2018 • Enterprise Experience 2018
Gold
David Conrad
The Feeling of Data
2023 • Enterprise Community
Brad Peters
Short Take #1: UX/Product Lessons from Your Industry Peers
2022 • Design in Product 2022
Gold
Ren Pope
Building Experiences for Knowledge Systems
2023 • Enterprise UX 2023
Gold
Phil Gilbert
A Consistent Culture of Design
2015 • Enterprise UX 2015
Gold
Product and Design at Bloomberg: A 15-year Evolution
2022 • Design in Product 2022
Gold
Jorge Arango
Design as an Antidote to VUCA
2019 • Enterprise Community
Amy Bucher
Harnessing behavioral science to uncover deeper truths
2025 • Advancing Research 2025
Gold
Jemma Ahmed
Bringing together market and user research
2019 • Advancing Research Community
Sarah Fathallah
Beyond insights: Rethinking the role of researchers as stewards of organizational wisdom
2025 • Advancing Research 2025
Gold
Spencer L. A. Stultz
Why Social Justice Frameworks are Necessary for Successful DEI/JEDI Initiatives
2023 • DesignOps Summit 2023
Gold
Francesca Barrientos, PhD
You Need Your Own Definition of Design Maturity
2022 • Design at Scale 2022
Gold
Saara Kamppari-Miller
DesignOps for Inclusive Design and Accessibility
2022 • DesignOps Community
Wendy Johansson
Be a Product Boss!
2022 • Design in Product 2022
Gold

More Videos

Ariel Kennan

"When I started, there were a few practitioners in the US, a small community, and now I see this growing network and community of practice."

Ariel Kennan

Theme Two Intro

November 17, 2022

Candace Myers

"Human centered design Ops is about making sure nobody thinks they’re a robot."

Candace Myers

Standardizing Design at Scale

September 9, 2022

Marissa Cui

"You don’t need a lot of upfront data; we predict energy usage with AI from just a building’s address."

Marissa Cui Rachel He Michael Leggett Manos Saratsis

Climate Design Product Showcase

March 13, 2024

Nalini Kotamraju

"Conscious uncoupling is about identity — how one thinks of oneself defines oneself and how others define you."

Nalini Kotamraju

Research After UX

March 25, 2024

Ana Maria Montero Barrantes

"The only rule is to maintain your smile and just to feel the being that have fun."

Ana Maria Montero Barrantes Aditi Dhar Michelle Kaplan Nate Osborne Matt Laurence

The Authentic UX Talent Show

January 8, 2024

Megan Blocker

"Without adoption, value is zero."

Megan Blocker

Getting to the “So What?”: How Management Consulting Practices Can Transform Your Approach to Research

March 26, 2024

Holly Cole

"Use these tools to define who you are going to hire next and what gaps those hires need to fill."

Holly Cole

Understanding Experiences: When you have to do more than work

November 8, 2018

Scher Foord

"Trust is hard to find but essential; we hire smart people so let’s all trust and move forward."

Scher Foord Corey Greenltch Sarah Rowe

Turn the Ship Around: How to Apply Design Thinking Across Your Organization

June 10, 2021

Jerome “Axle” Brown

"Change is the only constant, so designing insight sharing with self-directed learning is critical."

Jerome “Axle” Brown

How to Use Self-Directed Learning to Ensure Your Research Insights are Heard and Acted Upon

March 11, 2021