Giving Consumers More Power in Their Customer Service Interactions
Design Strategy | Directed Storytelling | Wizard Of Oz | Rapid Prototype Testing | Participatory Design
I worked with Consumer Reports, America's leading consumer rights advocate, to design an AI-powered tool, FairPlay AI, that addresses consumer frustrations with customer service.
FairPlay AI provides consumers with the resources, knowledge, and support needed to resolve customer service issues in a quick, hassle-free, and effective manner.
Client
Innovation Lab @ Consumer Reports
Duration
Jan 2024 - Aug 2024
Team & Roles
Mikayla Alsopp (Product Manager)
Vaidehi Chotai (UX Researcher)
Peiwen Huang (UX Designer)
Kai Lin (UX Designer)
Jonah Sklar (Business Consultant)
Methods
Design Research
Directed Storytelling
Wizard Of Oz Testing
Rapid Prototyping
Guerilla Intercept Interviews
Journey Mapping
Semi-Structured Interviews
Affinity Clustering
Co-Design
Have you ever been surprised by an
overcharge on your subscription bill? No warning, no explanation, and now you’re dreading contacting customer service…
PROBLEM SPACE
In today's complex service-driven marketplace, consumers interact with companies at multiple touchpoints beyond their initial purchase, yet lack sufficient protections and tools to help them in their post-purchase interactions with companies.
74%
of consumers reported experiencing a product or service issue in the past year
79%
of consumers reported they put high effort to complain about their issue
48%
of consumers got ‘nothing’
for complaining
*National Customer Rage Survey, 2023
Consumer Reports has been a long-standing advocate for consumer rights since the 1930s.
CR employs rigorous testing and its publication to promote safety and hold companies accountable. Although CR continues to be a trusted resource for consumers during their purchasing process, its influence has diminished in an increasingly service-based economy.
As consumer-company touchpoints extend beyond the initial purchase in this new services-based marketplace,
CR's ability to safeguard consumers throughout their entire customer journey has become limited.
Design a solution that ensures companies deliver on their promises by
mediating interactions between
individual consumers and companies
To address this, CR approached us to
Ultimately, CR’s goal is to extend consumer protection and advocacy beyond the purchase stage.
Overview of FairPlay AI
FINAL DESIGN SOLUTION
The Consumer Reports FairPlay AI app compiles company contact information and identifies the fastest way to reach a company, helping users avoid the hassle of searching for contact details, long wait times, and endless transfers.
FairPlay's AI-powered iMessage plugin analyzes users’ chat (with consent), identifies relevant company policies to help users negotiate, and crafts compelling arguments for the user based on the policies.
FairPlay provides policy details, talking points, and negotiation scripts to guide customer service call.
Users can save time and avoid the frustration of customer service by using the “Do It For Me” feature, where an AI voice agent contacts customer service on their behalf. Push notifications update users on the AI’s progress and prompt input at crucial decision points, maintaining transparency and control.
Overall, FairPlay empowers consumers by providing them with the information and tools they need to navigate customer service interactions in a streamlined and effective manner.
It levels the playing field, giving individuals access to resources comparable to those of large corporations, including policy information, negotiation support, and even AI assistance. This helps balance the current power dynamic where businesses often hold all the cards by having significantly more resources, manpower, legal support, and financial leverage than individual consumers.
IMPACT
Our research identified a key opportunity for Consumer Reports to expand their influence into the post-purchase customer service experience by leveraging agentic AI to empower consumers, a direction they are now actively pursuing.
We delivered significant value to Consumer Reports (CR) by identifying a key opportunity space: the post-purchase customer service experience.
Our research revealed a critical gap in CR's offerings and advocacy. While they excel at pre-purchase product testing and reviews, they have limited presence post-purchase, leaving consumers vulnerable to exploitation and frustration, particularly during customer service interactions. We found that addressing this aligned with both, current consumer needs (identified through our research) and CR's long-term business objectives, offering a powerful new direction for consumer advocacy and empowerment.
Additionally, the Innovation Lab was particularly interested in emerging technologies, and our research identified agentic AI as a powerful tool for consumer empowerment.
Our design solution demonstrated a tangible application of this technology within the post-purchase customer service space we identified, providing Consumer Reports with a clear future strategic direction that aligns with their business goals and the needs of their target users.
Following our project, Consumer Reports's Innovation Lab has been actively pursuing the direction we recommended.
Ben Moskowitz, VP of the Innovation Lab, recently spoke about agentic AI in customer service at the VRM conference, building on the research and design work we completed in the fall. The CR team is now actively exploring how agentic AI can support and advocate for consumers in the customer experience (CX) space, as evidenced by their recent blog posts and LinkedIn updates after our project concluded in August 2024.
My Role
I spearheaded user research, insight generation, and iterative prototype testing to inform FairPlay’s core features and guide design decisions.
My primary responsibility was to lead the design research process throughout the project. Specifically, I —
Selected appropriate research methods
Designed research studies
Developed study protocols
Crafted interview questions
Moderated research studies
Planned and facilitated co-design session
Provided design recommendations
Delivered a comprehensive research report
Key Takeaways
REFLECTION
1. To build buy-in for user research, involve collaborators in the research process
Convincing cross-functional team members of the value of user research, especially during the messy and ambiguous generative phase, was a challenge. Initially, I faced resistance from team members who favored intuition-based design or prioritized business objectives over research-backed insights.
I quickly learned that involving them directly in the research process, clearly explaining its purpose, and tying it to the bigger picture was far more effective. I also developed worksheets and held training sessions to help them understand and engage with the research methods. Ultimately, this experience taught me that gaining buy-in requires making research a collaborative process from the start.
2. Client collaboration is more effective when structured around participatory design activities rather than verbal discussions
Establishing a clear understanding of the client’s objectives, target user group, and timeline from the beginning is essential. However, early in the project, we received conflicting feedback from various client stakeholders, which created ambiguity and confusion within the team.
At that point, I realized that verbal discussions and meetings alone weren’t enough—we needed structured, participatory design sessions to extract clear objectives from the client. By using established methodologies from the LUMA Institute (thanks to our advisor, Laura Vinchesi, a LUMA alum, for guiding us!), along with tangible artifacts (shown below), we were able to align stakeholders effectively. These participatory design activities and tangible prototypes provided clarity, helping us focus our efforts and deliver maximum value to the client. This structured approach replaced the confusion and conflicting feedback that arose from less formal communication.
3. Storytelling and prototypes are highly effective tools for communicating research findings & recommendations
Through this project, I learned that effectively communicating research findings requires storytelling and an understanding of the audience. It wasn’t enough to just present the data; I needed to explain why the findings mattered to the target audience, how they tied back to the project goals, and offer concrete, actionable solutions.
Initially, I hesitated to present solutions, offering only findings and broad suggestions. But I soon realized that presenting concrete solutions through user stories and interactive prototypes was far more impactful than traditional research reports. These tools brought my research to life. Compelling user stories helped clients understand the real-world impact of my recommendations, while tangible prototypes allowed them to visualize and interact with the proposed solutions directly. This led to more engaged discussions and faster buy-in.
This project reinforced the importance of presenting a clear vision and solution, rather than simply offering vague suggestions.
DESIGN RESEARCH FRAMEWORK
My Approach
Generative Research & Synthesis
WHAT IS: UNDERSTANDING THE CURRENT STATE
Understanding Client Business Needs & Objectives
Consumer Reports desires to expand its influence in the modern, service-oriented economy
Before diving into generative research to understand and define the problem space, we first sought to understand CR's strategic objectives and priorities. We conducted an Abstraction Laddering exercise with key stakeholders and uncovered the following underlying priorities and motivations.
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CR aims to attract a younger audience and diversify its revenue streams beyond its current subscriber base, which has a mean age of 63.
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The company seeks to safeguard consumers in an increasingly digital and service-oriented economy in order to ensure its continued importance and role in the modern consumer’s life.
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Consumer Reports, and specifically our client, the Innovation Lab within this organization, aspires to be a pioneer in innovative technology solutions that are consumer-centric.
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With this product, Consumer Reports hopes to drive positive change in corporate behavior and accountability.
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Maintaining Consumer Reports’ brand trust and reputation for reliability and credibility is a priority for all client stakeholders.
My colleague, Kai Lin, and I, facilitating the abstraction laddering exercise at Consumer Reports’ New York head office with 6 key client stakeholders.
WHAT IS: UNDERSTANDING THE CURRENT STATE
Understanding Consumer
Needs & Pain Points
GENERATIVE RESEARCH: PROCESS
To expand CR's impact beyond the point of purchase, I first identified key touchpoints between consumers and companies, and the needs and challenges that arise at these touchpoints. I conducted mixed-methods research—including netnography, contextual guerrilla intercept interviews, and directed storytelling sessions—to gather these insights.
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We studied online consumer queries, discussions, and reviews on Reddit and company forums to identify the information and support that consumers frequently seek from companies after making a purchase, as well as the common pain points and challenges they encounter during these interactions.
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We conducted 12 contextual guerilla interviews at the Apple Genius Bar, Xfinity store, Target, and outside a Bank Of America to gather insights on the purpose of consumer visits and the common challenges they face when interacting with the companies post making a purchase.
This allowed us to narrow down on the most common reasons for interacting with businesses post-purchase, preferred channels of contacting companies, and consumer sentiments around online vs. in-person company interactions.
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We conducted in-depth semi-structured interviews (n = 11) using directed storytelling and storyboard artifacts to capture specific narratives on consumer experiences in the post-purchase stage.
This set of interviews helped us explore in detail the journey, fears, motivations, and pain points that consumers encounter when interacting with companies.
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Guerrilla Intercepts:
I interviewed a random sampling of Gen Z and millennial consumers that I found outside stores and service centers.
Aimed for a diverse and random sample to gain an unbiased understanding of younger consumers' needs and frustrations with businesses.
Potential bias: The sample likely overrepresented those who prefer in-person interactions and may hold more extreme views on digital interactions.
Directed Storytelling:
We interviewed a diverse group of young consumers, aged 21 - 35.
Potential sources of bias:
We relied on our personal network to recruit participants for this study since the interviews were 45 mins long and financial constraints prevented us from compensating participants or employing remote testing softwares.
30% of the pool was UX-adjacent
Bias minimization:
Each group member recruited 2 acquaintances (not close friends or family) and interview moderation for these participants was done by a member unfamiliar with the participant.
UX adjacency likely introduced minimal bias in these interviews, since these participants were recruited to narrate their past experiences with businesses and not for a study evaluating the user experience of an interaction.
23
Participants
21 - 35
Age Range
47%
Male
53%
Female
From my research, I uncovered that the most frequent and frustrating consumer engagements with companies occur during the post-purchase service request phase.
These interactions are sought by consumers when they face issues with their product/service and require assistance from companies. Specifically, I found that customer service interactions are time-consuming, mentally exhausting, and emotionally draining for consumers. They experience feelings of helplessness and anxiety when interacting with companies to advocate for what they deserve.
GENERATIVE RESEARCH: SYNTHESIS
We conducted Customer Journey Mapping and Affinity Clustering to synthesize what I discovered from generative research activities
(Top) Customer Journey Mapping revealed that the Service Request phase has the most touchpoints and negative emotions, and is also where Consumer Reports lacks presence. This insight guided us to focus on designing a solution to mediate company-consumer interactions and reduce negative emotions in this phase.
(Bottom Left) Conceptual model showing our finding that high-stakes, intangible goods and services have more touchpoints in the post-purchase stage compared to tangible, low-stakes items. High stakes goods/services are defined as those with high prices or involving sensitive data.
(Bottom Right) We clustered our findings from the generative research sessions into key themes, leading to insights on consumer motivations, needs, and challenges, which defined the “what” of our project.
GENERATIVE RESEARCH: INSIGHTS
I generated the following insights from our affinity clustering session —
Consumers spend a significant amount
of time and effort in locating the right company contact information and gathering necessary documentation
to support their case.
INSIGHT 1
-
Consumers encounter difficulties finding the right contact information, gathering required documentation, and dealing with frequently uncooperative customer service representatives.
As a result, customer service interactions with companies are often time-consuming, effortful, and mentally and emotionally draining for consumers.
This presents an opportunity for Consumer Reports to streamline these interactions and make it easier for consumers to get the help they need.
Consumers are limited in their ability to effectively negotiate with companies because they lack access to and understanding of company policies and consumer rights.
INSIGHT 2
-
Consumers often do not seek out company policies and are unaware of their rights because of the overly technical, lengthy, and legal nature of policy documents.
This limits their ability to effectively negotiate with companies during customer service interactions.
Consumer Reports has the opportunity to present relevant policies in an easy-to-understand and actionable manner to aid consumers in building policy and fact-based arguments to effectively make their case during customer service interactions.
This information and resource asymmetry causes consumer anxiety
and low confidence about interacting with customer service.
INSIGHT 3
-
Consumers often operate as solo actors, lacking the time, expertise, and knowledge that companies have about their products, policies, and internal processes.
This resource asymmetry and lack of transparency leads to anxiety and diminished confidence when interacting with customer service representatives.
Furthermore, this asymmetry forces consumers to rely on emotional arguments and debates with representatives, making the interactions uncomfortable and emotionally draining.
This highlights the need for Consumer Reports to help increase consumer confidence in customer service interactions by mitigating resource and information asymmetry between consumers and companies.
Opportunity
These insights point to a solution that makes it easier for consumers to —
Connect with the right company representatives
Construct effective negotiation arguments using facts and policies
Reduce their apprehensions about interacting with companies
Ideation & Prototyping
WHAT COULD BE: IMAGINING A DESIRED FUTURE STATE
Ideation & Parallel Prototyping
We created storyboards, design fiction narratives, and paper prototypes to explore different ways in which the Consumer Reports can empower consumers in their customer service interactions with companies.
We conducted parallel prototyping to rapidly explore different design solutions in various user contexts. This led us to design the three low-fi prototypes shown above.
The first prototype provides real-time assistance and policy alerts during customer service calls. The second is a mobile widget that flags deceptive patterns and predatory behavior and provides relevant policy details and insights in simple language. And the third prototype helps users troubleshoot product issues and submits service requests on behalf of the consumer.
The prototypes and design solutions we ideated not only meet consumer needs and challenges that we identified through generative research, but are also aligned with the client’s business objectives.
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The prototypes address the needs and challenges of younger consumers, specifically targeting Gen Z and Millennial generations, with the goal of attracting more young subscribers and patrons to the organization.
Our design solution focuses on customer service interactions, which increases Consumer Reports' presence in the post-purchase journey, a critical stage in today’s digital, service-based economy.
The prototypes leverage emerging technologies, such as artificial intelligence and virtual reality, in a consumer-centric manner.
We envision these prototypes as standalone applications, independent of the current Consumer Reports app and subscription bundle, creating new revenue opportunities.
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Negotiation Helper provides:
A database of customer service numbers of different companies
Real-time assistance and policy alerts during customer service calls
Post-call summary, transcript, and tips
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Policy Assistant is a browser extension and a mobile widget that:
Flags deceptive patterns and predatory behavior
Provides relevant policy details and insights in simple language
Drafts policy-backed arguments for consumers
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CR Wallet is a mobile app that:
Stores users’ products along with their respective customer handbooks, policies, and terms of service in a centralized “wallet
Help users troubleshoot product issues
Submits service requests on behalf of the consumer
WHAT COULD BE: IMAGINING A DESIRED FUTURE STATE
Co-design With Stakeholders
We decided to present our three initial design ideas to our client and conducted a co-design session with key stakeholders using the prototypes as tangible starting points to receive feedback, gain alignment, and get further clarity on client needs and expectations.
We conducted three activities, Rose, Bud, Thorn critique, Buy A Feature, and Build Your Own Product-Service during the co-design session.
The objective of these activities was to understand the motivations, concerns, considerations, and priorities of different stakeholders at Consumer Reports, from the Vice President of the CR Innovation Lab to the Technical Lead.
Negotiation Helper aligned most closely with Consumer Reports’ desired strategic direction and objectives.
Final Design Solution & Process
Building an effective case for negotiation takes a lot of time & effort
PROBLEM 1
Female, 30s, Directed Storytelling (P14)
Provide negotiation arguments relevant to the issue at hand in easy-to-understand language
SOLUTION
One common challenge consumers face when dealing with customer service is the need to build a strong case—either based on policies like warranties or through emotional appeals—in order to secure a favorable outcome.
This process can be effortful and frustrating, especially when consumers lack access to or understanding of relevant policies and their rights.
FairPlay provides consumers with easy-to-understand, policy-based negotiation arguments sourced from company and legal databases.
The intelligent agent extracts relevant policies and consumer rights to build effective cases for consumers.
These are tailored to their specific issue and are presented as direct talking points to help consumers navigate customer service interactions with greater confidence and efficiency.
Overall, by offering relevant negotiation arguments, FairPlay empowers consumers, reduces the effort and emotional frustration required to make their case, and levels the playing field with well-resourced companies.
How did I get to this solution?
DESIGN RESEARCH PROCESS
Since customer service calls are high-stress, anxiety-inducing interactions, I decided to test an initial prototype where an “intelligent agent” listens to the call and helps the user negotiate in real-time through written messages.
I tested the utility and effectiveness of real-time negotiation support using Wizard of Oz protocol.
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In our first round of Concept Testing, I wanted to test:
Is real-time negotiation support effective in improving consumer confidence, customer service experience, and outcome?
How is the simultaneous customer service call and app text support interaction for users?
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I used Wizard of Oz testing in the first round of concept testing to simulate a customer service call and the intelligent agent that provides real-time negotiation support to the participant in response to the phone conversation.
To start with, I formulated a scenario to put participants in context. Then, I tasked the participants to use the app to contact customer service to resolve the service issue provided in the scenario.
Scenario
Participant is overcharged on their Xfinity Wi-Fi bill due to a service change they didn't authorize.Roles
Moderator: Guides the participant through the test and observes their interaction with the prototype.
AI Agent (Wizard 1): Plays the role of the intelligent agent behind the scenes, providing real-time information & negotiation support based on the conversation via text messages (performed by a team member in another room).
Xfinity Agent (Wizard 2): Plays the role of a customer service representative for Xfinity (performed by a team member in another room).
Participant: Interacts with the prototype and Xfinity customer service to resolve the overcharge.
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I recruited a diverse sample of participants, aged 24-32 for all 3 rounds of concept testing.
While the participants were diverse in their gender and racial backgrounds, one potential source of bias was that many were Carnegie Mellon students, which is a largely technical school. As a result, the participants likely had greater tech-literacy and a higher comfort level with AI applications than the larger population.
They were recruited out of time and budget constraints and we acknowledged this bias when presenting our findings to the client.
If I had more time and a dedicated research budget, I would have liked to test our concept and prototypes with young consumers with less exposure to and experience with AI, to match that of the general population.
Pre-arming consumers with direct talking points before customer service calls is 20% more effective in helping them negotiate than policy clauses & suggestions provided in real time.
Providing real-time negotiation support
ITERATION 1
Providing preparatory
talking points
ITERATION 2
"I was confused about what was going on. I was trying to listen and then read at the same time and answer. It was overwhelming.”
Female, 30s (Round 1, P8)
"Having policy points is quite helpful. The (customer service) agent denied me a full refund, but the tips (from the app) said I am entitled to a partial refund based on their policy. Without this guidance, I might have simply accepted the agent’s initial response."
Male, 20s (Round 2, P2)
Customer service is an extra step in the issue resolution process — consumers simply want their problem solved!
PROBLEM 2
Female, 20s, Concept Testing Round 2 (P2)
Male, 30s, Concept Testing Round 2 (P7)
Agentic AI system that automates customer service processes
SOLUTION
During prototype testing with simulated customer service calls, I noticed a recurring sentiment: most participants dreaded interacting with customer service and wanted to avoid "doing all the talking and figuring out." They simply wanted their issues resolved without having to engage with customer service at all.
While our prototypes aimed to empower consumers during their customer service interactions, they did not address the real problem behind the problem: consumers want a quick resolution to their product or service problem. For consumers, customer service is an added step that makes the issue resolution process inefficient and frustrating, and they would prefer to avoid it altogether.
To address this, our solution needed to streamline the issue resolution process, potentially bypassing customer service entirely. We realized that automation, driven by recent advances in AI, could help achieve this goal.
We introduced a feature where users can delegate their customer service interactions to an AI agent.
At a high level of intervention, the AI agent can make calls on the user's behalf, providing real-time updates through push notifications. The AI functionality also extends to other communication channels, including drafting and sending emails or participating in live chats with customer service.
Push notifications balance convenience with user control, allowing issues to be resolved hands-free while keeping users informed at key decision points. To minimize errors and ensure control, users can verify important details (such as account numbers, addresses etc.) and review AI scripts before the agent proceeds, providing feedforward to users. After the AI completes its interaction with customer service, users also receive a summary and transcript of the conversation.
Although voice AI agent functionality is novel, it aligns with our client, the Innovation Lab at Consumer Reports's future goals to harness emerging technologies in order to protect and empower consumers.
How did I get to this solution?
DESIGN RESEARCH PROCESS
To test the concept of an AI agent handling customer service interactions on behalf of the user, I focused on the riskiest assumption: a voice AI agent calling customer service to resolve a product issue.
I assessed user comfort, trust, and perceived utility of the voice AI agent using a Wizard of Oz protocol (see Video 1 below). Additionally, I tested monitoring and interjection features that streamline a three-way conversation between the user, AI agent, and customer service representative, using a recorded interaction embedded in a clickable prototype (see Video 2 below).
-
We studied online consumer queries, discussions, and reviews on Reddit and company forums to identify the information and support that consumers frequently seek from companies after making a purchase, as well as the common pain points and challenges they encounter during these interactions.
-
We conducted 12 contextual guerilla interviews at the Apple Genius Bar, Xfinity store, Target, and outside a Bank Of America to gather insights on the purpose of consumer visits and the common challenges they face when interacting with the companies post making a purchase.
This allowed us to narrow down on the most common reasons for interacting with businesses post-purchase, preferred channels of contacting companies, and consumer sentiments around online vs. in-person company interactions.
-
I recruited a diverse sample of participants, aged 24-32 for all 3 rounds of concept testing.
While the participants were diverse in their gender and racial backgrounds, one potential source of bias was that many were Carnegie Mellon students, which is a largely technical school. As a result, the participants likely had greater tech-literacy and a higher comfort level with AI applications than the larger population.
They were recruited out of time and budget constraints and we acknowledged this bias when presenting our findings to the client.
If I had more time and a dedicated research budget, I would have liked to test our concept and prototypes with young consumers with less exposure to and experience with AI, to match that of the general population.
80% of participants were comfortable with an AI agent handling customer service interactions on their behalf, and 100% were opposed to being a part of a 3-way conversation.
In round 1 of testing, I tested a voice AI agent with two modes of user interjection: text and voice to determine user comfortability with an AI agent acting on their behalf. While users were comfortable with AI acting on their behalf, user interjection was stressful and cumbersome, and preferences were split between the two modes of interjection.
To streamline the flow of user interjection and three-way conversation, we redesigned the text and voice interjection interactions in iteration 2. Testing this iteration, I found that while the new interjection interactions facilitated smoother user interjections, there was a tension between users’ desire to supervise the voice agent and the discomfort of active monitoring.
This led me to iteration 3, the final iteration of our design. I replaced active monitoring and interjection with a passive monitoring system that uses push notifications to provide feedforward and timely updates on the AI's progress, allowing users to remain informed without requiring continuous engagement.
Concept Testing Voice
AI Agent Acting on
Behalf of the User
ITERATION 1
Adding Features that Streamline Three-Way Conversation Flow
ITERATION 2
Shifting to Passive Monitoring via Push Notifications
ITERATION 3
80%
were open to a voice AI agent conducting customer service calls on their behalf and found it helpful
(n = 20)
$26.50
were willing to pay $26.50 per year on average for an AI agent to handle customer service issues for them
(n = 10)
100%
would rather not be present at all in a 3-way phone conversation between themselves, the voice AI agent, and the customer service rep (n = 10)
80%
expressed a desire to passively monitor the agent, through pre-call information verification, live updates, or post-call summaries (n = 10)
“I would definitely use this service, because a lot of times when you have to return something life gets in the way or you just don't know the policies well enough, and it kind of falls back.
And at the end, you are like, okay, maybe I should just get another TV because you don't want to put up with all that. So I think this would be really nice."
Female, 20s (Round 2, P8)
“If I have to be engaged when the AI is making the phone call, then I should just make the phone call myself.”
Male, 30s (Round 3, P3)
“I would like confirmations before, or little checkpoints along the way to know the agent is not going rogue so I don't need to be on the phone.”
Female, 30s (Round 3, P3)
Locating company contact details and quickly reaching the right customer service agent
PROBLEM 3
A common pain point I identified in our generative research was that consumers often struggle to locate customer service contact information and reach the appropriate representative. This process is lengthy & frustrating, typically involving extensive online searches, long hold times, and multiple transfers between departments.
Male, 20s, Directed Storytelling (P12)
Providing optimal communication channel recommendations & direct contact details
SOLUTION
By recommending the fastest communication channel to resolve the user’s specific issue and providing direct contact details, FairPlay reduces the time spent searching for company contact information and minimizes wait times.
This approach streamlines the issue resolution process for consumers, alleviating the frustration of having to invest significant time and effort simply to reach a company.
My collaborator, Peiwen, and I maintained a blog throughout this project. You can read more about our journey here!
Read my key takeaways from this project.
I published an article on the Consumer Reports website talking about our research findings and how agentic AI technology can be employed in the post-purchase phase to empower consumers. Read it here!
