Nivi Singh

TELL MY STORY

CHALLENGE

Traditional target persona for Kodak was no longer printing. With the cameras always available to the consumers on their phones, their picture taking and sharing behavior had changed. 

Our goal in this project was to understand the needs of consumers in the digital photographic content space and provide an engaging and novel way to help tell their stories through the Kodak Moments app. 

The underlying business need was to increase the frequency of use and engaging consumers with Kodak Moments app on the daily basis. 

MY ROLE AND PROCESS

I led the research and design on this project along with the product manager and collaborated at different times with visual designers, image analysts, engineers, and business stakeholders. 
  1. Tell My Story
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    Tell My Story
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OUTCOME & LEARNING

  • The product, Tell My Story, was received by the target consumer as a creative way of using still images and adding dimensions of audio and motion (Ken Burn effect) to narrate stories from consumers' daily lives.
  • Launched the presence of the Kodak Moments app as a  social app.
  • A detailed and targeted roadmap for the Kodak Moments app.
  • The main discovery in this project was finding an inherent hesitation in  using own voice for narrating the story
  • The project brought a lot of learning for me as a researcher and a good understanding of our target consumer, their storytelling needs, and social media behavior.
 



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FIELD STUDY: FIRST NOTICE OF LOSS ​ 

THE OPPORTUNITY

Customer calls data can provide huge insights about the user experience with our services, products, and also a great source for ideas for innovative thinking. 

After some customer interviews for another project, I got a few pointers about how insurance plays a part in people's lives. Insurance remains a necessary but primarily invisible part of our lives. However, we all have those moments in life when we need its support. What goes in a customer's life and what do they expect from it when they need the service that they pay such a high cost for? To create awareness and empathy within the company for the needs and expectations of the customers, I wanted to analyze live service calls and understand customer behavior and expectations when in stressful situations such as accident reporting (First Notices of Loss). 
   

APPROACH & MY ROLE

FIELD STUDY

SHADOWING CALLS

CONTEXTUAL INTERVIEWS

  • Understand customer behavior and environment at the time of stressful situations of auto accidents
  • Understand the pain points customers have when reporting a claim over the phone
  • Understand the protocol and pain points for the call handlers
  • Identify process improvement areas 

OBJECTIVES

  • Create empathy for the customer when interacting with the system and process in stressful situations
  • Explore opportunities to improve the claims experience for customers and call handler
Listening to live calls was an opportunity to develop a deeper understanding of the problems customers face when they need support from their insurance. The approach was to identify further research areas and surface opportunities to enhance existing or to identify new products and services that will meet the needs of our customers.

What I did to achieve those goals:
  • About 40 hours of listening to FNOL calls 
  • Listened in on 60 customer calls, primarily auto claims
  • Identified themes and the pain points for each category ​

WHAT WE LEARNED

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THE OUTCOME: A ROADMAP

  • Created empathy for the customer 
  • Identified customer problems to solve
  • Created Effort-Impact matrix to prioritize
  • Identified opportunities for:  
    • Information needs
    • Self-service applications
    • Training needs for reps
    • Process changes
    


GENERATIVE RESEARCH: AMICA APP UTILITY SUITE 

THE OPPORTUNITY

Amica was venturing out in the app world with some utility apps; I led the generative research initiative with the product team and third-party developer team on this project.

The main challenge of this project was how Amica is perceived as an insurance company, the primary customer base of the company consists of an older and higher economic status demographic population that has been with Amica for a long time (sometimes the only insurance they have had). Researching concepts and ideas that are not directly related to insurance brought interesting challenges and insights both from the customers and the stakeholders of the projects.

   
HOME MAINTENANCE APP

The app was planned to be offered as a utility app to the customers for their home maintenance needs. It was targeted for the homeowner policyholders but was not limited to that segment. The app was designed to help the homeowners to schedule and plan for their home maintenance needs.
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APPROACH AND MY ROLE

As the principal researcher for this project, I designed an open online forum with customers (Amica Idea Community deployed through FlueCycle). The format of the forum was purposefully kept open and generative to understand the main activities homeowners do on regular basis and seek help with.

Analyzed and mapped the data collected for the patterns in activities, needs, and themes of pain points. Created Needs, Pain, and Gain analysis charts. Most frequent and repetitive maintenance themes were selected to address the pain and opportunity areas for the app.  

The selected home maintenance activity themes were taken through in-house design conception and ideation phases and validated with remote moderated interview sessions, surveys, usability and design validation studies at various stages of the research.

 ALEXA SKILLS

Alexa and other AI platforms are rapidly becoming part of our daily lives. Keeping with the trends and needs of the customers, Amica Alexa skill was being developed. Amica’s Alexa skill has since been released on Amazon.

APPROACH AND MY ROLE

Conducted the initial research for this project:
  • Technology exploration: what is Alexa/voice enabled interactions?
  • Benchmarking competitor Alexa skills: what are our competitors doing with Alexa?
  • Contextual inquiry: listening-in the service calls to identify frequently handled queries.

Results:    
  • Analyzed service calls data and identified 26 clear query patterns.
  • For each main query, identified and mapped possible subqueries (query tree).
  • Worked with a third-party development team to create and test Alexa skills for identified queries.​