AutoZone | Ciara Potter

AutoZone

Enhancing e-commerce & customer support through UX design.

As a E-Commerce Digital Design Intern at AutoZone, I had the opportunity to work on projects that enhanced the digital shopping experience and streamlined customer support. I designed responsive digital interfaces for mobile, tablet, and desktop, ensuring a seamless and intuitive user experience. I also contributed to the redesign of Product Detail Pages (PDPs) on AutoZone.com, improving usability and product visibility. Additionally, I helped revamp AutoZone’s ZeroHeight platform, refining brand guidelines to create a more consistent and accessible design system.

One of the most impactful projects I worked on was designing a customer service chatbot to reduce call volume to AutoZone’s Mexico call center. I conducted research and interviews with customer service representatives, identified high-call drivers, and prototyped a chatbot to automate frequent inquiries. Presenting my findings and pitching the chatbot solution was a valuable experience that strengthened my skills in UX design, digital strategy, and problem-solving.

AutoZone Rewards Chatbot: Improving Customer Experience 

As a eCommerce Digital Design Intern, I prototyped an AutoZone Rewards Chatbot to automate rewards-related customer service tasks. This internal solution aims to reduce call and email volume for customer service representatives, improving efficiency and customer satisfaction. By streamlining routine inquiries, the chatbot supports AutoZone's values of community service and customer care, ultimately enhancing the brand. This project not only addresses an existing issue of overloaded support teams but also has the potential to increase customer retention, drive sales, and positively impact net profit by improving operational efficiency and customer engagement.

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What impact does automating high-volume customer service tasks through a chatbot have on response time, customer satisfaction, and operational efficiency?

Project Year: 2023

Project Duration: 6 weeks

Overview: As an eCommerce Digital Design Intern, I developed an AutoZone Rewards Chatbot to automate rewards-related customer service tasks. This internal solution aims to reduce call and email volume for customer service representatives, improving efficiency and customer satisfaction. By streamlining routine inquiries, the chatbot supports AutoZone's values of community service and customer care, ultimately enhancing the brand. This project not only addresses an existing issue of overloaded support teams but also has the potential to increase customer retention, drive sales, and positively impact net profit by improving operational efficiency and customer engagement.

This project focused on developing an intelligent chatbot to streamline customer service operations by automating common inquiries and reducing reliance on human agents. Designed for AutoZone Rewards customers, the chatbot aimed to bridge in-store and online interactions, offering a seamless, efficient, and accessible support system.

Built using Google Business Messages and Dialogflow, the chatbot was designed to handle high-volume customer service tasks, such as filing claims, checking rewards balances, resolving lost package issues, and managing account inquiries. By automating these repetitive tasks, the chatbot significantly reduced wait times, improved customer satisfaction, and freed up service representatives to focus on complex cases.

Skills Used: UX/UI Design, Conversation Design, Natural Language Processing (NLP), Data Analysis, Prototyping, Wireframing, Usability Testing, Project Management, API Integration, Customer Experience Optimization

Project Overview

Background & Problem: AutoZone’s customer service team handles thousands of rewards-related inquiries each quarter, many of which are simple, repetitive tasks that consume significant time and resources. Based on Q3 customer support data, the most common inquiries included:

Checking missing or expired credits – 2,961 calls (26,500 minutes).
Account creation, linking, and resetting – 867 calls (10,201 minutes).
Checking rewards balance – 1,456 calls (8,978 minutes).
Rewards program information – 708 calls (5,392 minutes).

These tasks, while high in volume, do not require human decision-making and could be automated to reduce Average Handle Time (AHT) and improve efficiency.

Research Problem: Customer service representatives (CSRs) are overloaded with repetitive inquiries, leading to long wait times and reduced availability for complex cases. Customers needing more in-depth assistance must wait while agents handle routine tasks that a chatbot could efficiently manage.

Process: Customer Service Data Analysis, User Interviews, FAQ and Inquiry Review, Call and Email Log Analysis, Chatbot Feasibility Study, User Flow Mapping, Wireframing & Prototyping, Intent and Entity Definition, Conversation Flowcharting, Dialogflow Development, User Testing & Iteration, UI/UX Refinement

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Conclusion

Final Thoughts: The AutoZone Rewards Chatbot demonstrated the power of automation in customer service, reducing call volume, wait times, and operational costs while enhancing customer satisfaction. By addressing common rewards-related inquiries, it provided instant support, freeing human agents to handle complex cases. Its success highlights the value of AI-driven solutions in improving service efficiency.

Results:

Showcased chatbot’s ability to automate 51,073 minutes (852 hours) per quarter and 204,292 minutes (3,404 hours) annually.
Highlighted how reducing AHT improves customer satisfaction.
Addressed practicality & investment, explaining how chatbot complexity affects development time and costs.

Final Pitch & Presentation

Timeline: Week 6

Conclusion: The AutoZone Rewards Chatbot successfully streamlined rewards-related inquiries, saving time and resources while improving the customer experience. If fully implemented, this chatbot could significantly enhance customer satisfaction and reduce operational costs for AutoZone.

Key Takeaways & Lessons Learned:

Automation Has High ROI: By handling high-volume, low-complexity inquiries, chatbots can significantly reduce customer wait times and improve service efficiency.

Data-Driven Decision Making is Essential: Analyzing customer call logs was crucial in prioritizing automation areas, ensuring the chatbot addressed the most impactful issues.

Seamless Integration Improves Adoption: Placing the chatbot in the bottom-right corner made it easy to access, increasing customer engagement.

Cost & Complexity Need to Be Balanced: Developing a simple chatbot takes a few weeks, while complex AI-powered bots require months and higher budgets.

Chatbots Support, But Don’t Replace, Human Agents: While automation reduces workloads, some complex cases (e.g., account merging) still require human intervention.

Researching AutoZone’s chatbots to identify efficiency gaps and improvements.

Project Timeline: Week 1 - Week 2

Overview: I analyzed AutoZone’s existing chatbots and identified opportunities where automation could enhance customer support and improve the customer experience.

Chatbot Exploration

Why a Chatbot?: AutoZone’s customer service team spends significant time handling repetitive rewards-related inquiries, such as checking credits, account issues, and rewards balances. In Q3 alone, these tasks accounted for over 53,000 minutes of customer service time, leading to longer wait times and increased workload for support representatives.

Currently, many customers rely on Google Search or calling customer service for answers. AutoZone currently has a chatbot through Google Business Suite but this system is underutilized, as even internal teams were unfamiliar with it. The lack of a direct, on-site support system presented an opportunity to connect loyalty customers with a streamlined, chatbot-powered FAQ linked to their AutoZone Rewards profile.

The chatbot has capacity to:

Automate frequent inquiries, reducing Average Handle Time (AHT).
Assist with claim filings, including lost rewards points, missing packages, and order issues.
Enhance customer experience by providing quick, accurate responses without needing to call customer service.

What Tasks Could Be Automated?
Based on high-call drivers, the chatbot was designed to automate:
✔ Checking missing or expired credits
✔ Creating, linking, or resetting MyZone accounts
✔ Checking rewards balances and rewards program details

Improving AutoZone loyalty experience and easing customer support.

Project Timeline: Week 2 - Week 3

Overview: As an eCommerce Digital Design Intern, I developed an AutoZone Rewards Chatbot to automate rewards-related customer service tasks. The chatbot aimed to reduce call and email volume to customer service representatives while providing quicker assistance for loyalty customers.

Research Focus: This project aimed to determine how chatbot automation could improve customer service efficiency by:

Reducing customer wait times with instant responses.
Minimizing AHT by offloading repetitive inquiries.
Enhancing CSR effectiveness by allowing them to prioritize complex cases.

Goal & Objectives:

Automate rewards inquiries (checking missing or expired credits, account management, reward balance, and program information).
Reduce the Average Handle Time (AHT) for high-volume customer inquiries.
Provide an efficient and seamless experience for loyalty members.
Support customer service teams by handling simple, repetitive requests, allowing them to focus on complex cases.

Key Insights from Research

Secondary Research Findings: AutoZone’s customer service team spends significant time handling repetitive rewards-related inquiries, such as checking credits, account issues, and rewards balances. These tasks, totaling over 53,000 minutes in Q3, could be automated to reduce Average Handle Time (AHT) and improve efficiency. Currently, CSRs are overloaded with these routine inquiries, causing long wait times for customers needing more complex support. Implementing a chatbot could ease this burden, allowing agents to focus on more critical issues.

Primary Research: To validate the feasibility of chatbot automation, I conducted interviews with two customer support representatives from call centers in Mexico. Key insights included:

High-Call Drivers: Representatives confirmed that missing rewards, account resets, and balance inquiries were among the most frequent issues.
Chatbot Potential: They believed a chatbot could streamline these inquiries, allowing customers to get immediate responses rather than waiting on hold.
Impact on Customer Experience: By automating simple requests, CSRs could focus on more complex issues, ensuring that customers with urgent concerns receive better support.

Design and Prototyping

Objective: The chatbot helps loyalty customers access rewards, point balances, offers, and redemption options.

Use Cases:

Check point balances
View rewards or offers
Redeem points for discounts/gifts
Update account info/preferences
Find nearby stores or delivery options

Build Dialog: I designed conversation flows in Dialogflow with intents and predefined responses from highest call drivers like:

"Provide your customer ID to check your points balance."
"Your balance is 320. Would you like to redeem them?"

Testing: Simulate conversations to ensure correct data retrieval and natural conversation flow.

Future Website Integration:

Use real-time customer data from AutoZone’s backend.Use API calls to fetch loyalty data (e.g., point balances, rewards).
Generate embed code and integrate it on AutoZone’s website, especially in loyalty sections.
Place a visible button or popup like "Check your rewards."
Ensure easy access from the loyalty program page.

Improving AutoZone loyalty experience and easing customer support.

Project Timeline: Week 3 - Week 4

Overview: Enhancing AutoZone’s chatbot is a cost-effective, scalable solution using Google Business Suite. By integrating it into the website and customer service database, it automates common inquiries, reducing call volume and saving up to 978 hours. This upgrade minimizes costs, improves efficiency, and ensures a seamless customer support experience.