Miru Huang

About

Miru Huang

About

AI Audi Navigator

Conversational AI Design

Side Project

Automobile

B2C

Desktop/Mobile Web

AI Audi Navigator

Conversational AI Design

Side Project

Automobile

B2C

Desktop/Mobile Web

AI Audi Navigator

Conversational AI Design

Side Project

Automobile

B2C

Desktop/Mobile Web

Overview

Problem

Understand

Initial ideation

Final Design

Reflection

This project was developed for the Audi Innovation Award Hackathon 2023, with the aim of transforming the Audi car-buying experience in Taiwan. By utilizing sentiment analysis, this innovative AI sales agent streamlines purchases, offers personalized guidance, and expertly negotiates, making Audi more accessible and appealing to Taiwanese customers.

MY ROLE

User Research, Define, Ideation, Mockups, Prototyping

COLLABORATED WITH

Data Analyst/Backend *1

Compliance RAQA*1

Product Manager*1

DURATION

• Hackerthon : 3 days, full time, August 2023

• Refined design : 1 month, September 2023

Problem Space

Ineffective marketing strategies resulting in low sales for Audi.

Despite being a premium brand, Audi faces stiff competition. According to the 2022 Taiwan Car Sales Ranking Report, whether from the overall market perspective or the imported luxury brands, Audi always finds itself trailing far behind. Audi's main strategy has been trying to focus on enhancing digital experiences with the aim of improving customer satisfaction.

Customer barriers during complex car buying process.

It has become evident that new potential customers often face challenges and uncertainties after we talked with Audi sales agents and gathered information via web crawler, including:

A desire to understand pricing without engaging in uncomfortable negotiations.

The selection of the most suitable model from a wide range of options.

Limited availability of Audi dealerships.

Solution - AI Audi Navigator

Solution -
AI Audi Navigator

AI Chatbot with negotiation capabilities to interact with customers of varying personalities.

The impact

Overcoming hesitation, and making choices easier.

By gathering data that traditional sales systems couldn't achieve before, it provides more precise and efficient marketing methods, whether for a chatbot or a sales team. It also reduces customer hesitation and increases the likelihood of closing a deal.

Limits

The compressed timeframe of the 3-day Hackathon restricted our capacity to develop a fully realized prototype. Consequently, we focused on the business strategy and technical components for the final presentation. We encountered obstacles due to limitations in revealing confidential information supplied by Audi. Following the event, I dedicated an additional 3 weeks to delve deeper into the project and finalize the detailed design.

Talk with Sales Agents

Before delving into the project, we engaged with Audi's sales agents to gain valuable insights.

They highlighted the frustrations experienced by both customers & agents when dealing with complex forms. This set the stage for our design challenges.

Customers who visit the showroom often hesitate to provide all the required details on the forms, making it challenging for the sales team to collect customer data for future marketing purposes.

Why Do Customers Hesitate?

Individuals can exhibit hesitancy and anxiety when facing unfamiliar situations or people based on psychological theories.

Researches show that there are 5 major factors related to consumer behavior.

Resources from Encyclopedia of Psychology, American Psychological Association.

While it's important to note that individual reactions can vary widely based on personality, past experiences, and situational factors, the exact nature of hesitancy and anxiety can differ from person to person.

Identifying the Pain Points

We now know that word of mouth is one of the essential factors that affects customer's decisions.

After conducting research via web crawler, we found that the majority of the reviews, whether from online forums or customer feedback data, are negative.

But how can we advance the consideration process?

Brainstorming

We attended a Value Proposition workshop. Using this model, we analyzed if Audi's current products and services fulfill the customer's jobs, desires, and relieve their pains.

We identified what can be resolved first at consideration stage from the right side, and then developed updated solutions on the left.

Early Ideation

A streamlined, AI-powered online car buying process was our goal.

At the early stages, we've explored multiple solutions. Our early ideation aimed to develop a simplified buying process, which involved the following 3 key steps:

However, things don't always go as planned

Our initial solution was overly ambitious, and required a refocus.

Despite our initial direction, we faced technical challenges. After consulting with professionals, including a senior PM, a UX designer, and the Head of Strategy, we realized that it was not feasible to create a comprehensive business plan with all the intended features within the given timeframe. Therefore, we had to make a difficult decision before the night of presentation.

With a last-minute pivot, we decided to concentrate on the AI sales aspect.

AI Audi Navigator - No face-to-face interaction, no time constraints, and no sales pressure.

Users visiting the official website could access the chat feature, enabling direct interaction with the AI sales agent.

Why we did this, even though Audi Taiwan already has an official LINE chatbot?

Audi Taiwan established an official LINE account in 2020, recognizing its popularity as a communication tool in Taiwan. However, there is room for improvement in certain areas.

Limited Flexibility

Many services require users to navigate to other windows, such as web or app, reducing the overall user experience.

Limited Flexibility

Many services require users to navigate to other windows, such as web or app, reducing the overall user experience.

Limited Flexibility

Many services require users to navigate to other windows, such as web or app, reducing the overall user experience.

Not attracting new customers

For individuals who are not car owners, the official LINE account offers limited utility or usage since most services are geared towards car owners.

Not attracting new customers

For individuals who are not car owners, the official LINE account offers limited utility or usage since most services are geared towards car owners.

Not attracting new customers

For individuals who are not car owners, the official LINE account offers limited utility or usage since most services are geared towards car owners.

So what's so special about AI Audi Navigator compared to a regular chatbot?

Clustering Car Models by Personality Tag

The AI chatbot employed Support Vector Machine (SVM) technology, utilizing a dataset of around 15,000 pieces of Voice of Customer (VOC) data for personality tagging.

This allowed us to categorize customers into different groups based on their preferences and personalities.

For example, we've identified 2 main groups for A-series car owners vs Q-series car owners from the database we had during the Hackerthon.

Therefore, we can infer the personality traits inclined towards individuals who are interested in certain models.

4 Negotiation Modes

The AI chatbot adapts to customer personalities with 4 negotiation modes, adjusting in real-time based on received messages.

We established these 4 negotiation modes based on sales team feedback. By utilizing LLaMa, allowing the AI chatbot to tailor their interactions based on the user's personality traits, ensuring the most personalized and effective service.

How it works

The AI collects chat records and performs data analysis, with the goal of helping the Sales team create customer personas, ultimately preparing them to provide better customer service.

Users can ask questions in natural language regarding personal guidance, accessory combinations, and even pricing. If users prefer a human representative, they have that option too.

Set Up

Before establishing conversation flow, I needed to determine the conversation elements for the chatbot.

Elements

Persistent Menu/Quick Drawer

Minimum Viable Information Architecture

I mapped out scenario use cases to create seamless conversation flows.

Hello : Triggered once a user clicks on the "Get Started" button. This will be the default entry flow.

Catch All : Triggered once a user does or says something that bot doesn't understand.

Human Handoff: Triggered when they want to talk to a human.

Goodbye: Triggered once a user completes the experience.

Use Cases and Data Gained

There are 3 main tasks taking A-Series car potential buyer as examples of conversation flow and the data that could be collected during each task:

Task 1 : Consult

Preferences:

Information about what the customer values in a car (e.g., luxury, fuel efficiency, performance).

Preferences:

Information about what the customer values in a car (e.g., luxury, fuel efficiency, performance).

Preferences:

Information about what the customer values in a car (e.g., luxury, fuel efficiency, performance).

Intended Use:

Understanding how the customer plans to use the car (e.g., family trips, commuting, adventure).

Intended Use:

Understanding how the customer plans to use the car (e.g., family trips, commuting, adventure).

Intended Use:

Understanding how the customer plans to use the car (e.g., family trips, commuting, adventure).

Budget:

Any budget constraints or financial considerations the customer has.

Budget:

Any budget constraints or financial considerations the customer has.

Budget:

Any budget constraints or financial considerations the customer has.

Task 2 : Request an online quote

Car Model Interest:

The specific Audi model the customer is interested in.

Car Model Interest:

The specific Audi model the customer is interested in.

Car Model Interest:

The specific Audi model the customer is interested in.

Potential Add-Ons:

Any additional features or services the customer might be interested in.

Potential Add-Ons:

Any additional features or services the customer might be interested in.

Potential Add-Ons:

Any additional features or services the customer might be interested in.

Contact Information:

If the customer decides to proceed, their contact details for follow-up and quote delivery.

Contact Information:

If the customer decides to proceed, their contact details for follow-up and quote delivery.

Contact Information:

If the customer decides to proceed, their contact details for follow-up and quote delivery.

Task 3 : Request a test drive

Availability:

Preferred date and time for the test drive, which can also indicate the customer’s urgency.

Availability:

Preferred date and time for the test drive, which can also indicate the customer’s urgency.

Availability:

Preferred date and time for the test drive, which can also indicate the customer’s urgency.

Contact Information:

Name, phone number, or email to confirm the test drive appointment.

Contact Information:

Name, phone number, or email to confirm the test drive appointment.

Contact Information:

Name, phone number, or email to confirm the test drive appointment.

Location Preference:

If the dealership has multiple locations, understanding which is most convenient for the customer.

Location Preference:

If the dealership has multiple locations, understanding which is most convenient for the customer.

Location Preference:

If the dealership has multiple locations, understanding which is most convenient for the customer.

My Reflections

Despite being the only UX/UI designer on the team, I decided not to limit myself and be more proactive about what I could offer to the project. During this project, I constantly consulted with our engineer and data scientist to get a better understand about how this technology works, even though it was not my area of expertise. I believe that staying curious is essential for a designer.

There was a time when we had considered many solutions, only to realize that we needed to refocus. That's when I learned we cannot pursue everything as resources are limited, and it's best to allocate them to the most certain one. I also learned that design process is definitely not linear nor perfect; it could return to its initial stage at anytime. However, I had to appreciate that we identified our problems early on, preventing us from falling into traps.

If we had more time to make the project more comprehensive, I hope we could create a way to present the data analysis and customer personas for sales agents, and define how they could use them.

I also wished to find a way to integrate AI Audi Navigator into Audi's current LINE Chatbot, which is more tailored to people in Taiwan.

And if I could start over, I would improve my presentation pitch. It was my only regret during the competition. I should have focused on how the AI Audi Navigator's personalities interact with different types of customers in various situations. We received feedbacks that the judges were interested and debating about our project.

In the end, this experience has taught me valuable lessons about teamwork, problem-solving and iterative nature of design. It was a journey of growth, and I'm excited to apply these new skills to my future projects.

If we had more time to make the project more comprehensive, I hope we could create a way to present the data analysis and customer personas for sales agents, and define how they could use them.

I also wished to find a way to integrate AI Audi Navigator into Audi's current LINE Chatbot, which is more tailored to people in Taiwan.

If we had more time to make the project more comprehensive, I hope we could create a way to present the data analysis and customer personas for sales agents, and define how they could use them.

I also wished to find a way to integrate AI Audi Navigator into Audi's current LINE Chatbot, which is more tailored to people in Taiwan.

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