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Predictive CX Analysis Tool
UX / UI, ML / AI, Information Architechture
Duration: 8 Weeks
Story
What is Spectrum AI?
Spectrum AI delivers continuous predictive CX analytics that give you real-time insight into every account so you can focus your effort where it will have the biggest impact on customers. Get on the same page with teammates and colleagues with continuously updated insights that flow all the way from overall account health, to each stage of the customer journey, to the operational metrics that contribute to the customer experience
My Role
Identify the problem and user needs with stakeholder's
Conduct data led UX activities with cross functional team
Usability Test and validation
Visual Design & Animation with fellow designers
The Problem
Its been observed there is data gap on response rate gathered through NPS. And these gaps often translated into assumptions which lacks real insight for customers accounts.
Why Spectrum AI?
Response Rates
Data Recieving in NPS
Assumptions
Data Gap effecting CX
As a result there could have been negative impact on customers which will effect business in a negative scale followed by taking wrong decisions in business.
The Challenge
“ Understanding data relation and map as per use cases for individual screens and design user friendly and engaging CX analytics application.”
Problem Solving Approach
Empathizing
Discover & Identify
Stakeholder Interview to understand project scope and user view
Use Cases Analysis and improvising accordingly
Cohort Data relationships deriving from ML team
Defining
Ideating UX with initial wireframing
Ideating based on use cases getting from stake holders
Exploration of content and understanding to represent data for each screens
Lo-fidelity mockups & Testing
Prototyping & Testing
Intuitive visual design
Exploration on contemporary practices of UI design in dark and light mode
Giving user pleasurable experience to understand data and interact with it
Hi-fidelity mockups & Testing
Key Insights
Get continuous, personalized updates – only when they matter to you – in your CX feed
Dive deep to explore in-depth data on account portfolios or customer segments, so you can spot trends, uncover trouble spots, or make new connections
Know what operational factors / KPI’s have the biggest impact on customers
Collaborate effectively with teammates on accounts of interest to you, based on a shared view of the customer journey
Information Architecture and Wireflow
Problems Faced
Technical Constraints
Some custom components has standards as per development guidelines or library guidelines which design team re-designed the components otherwise it would impact UX flow.
Data Evolved during the process
Customer feedbacks encourages us to relook data relationship at later point which changing the UX flow significantly.
Design as per data
Custom design approach as per data and articulating to dev team at the point of implementation .
Grid system
Multiples of 5 Grid system
This unique grid system designed to get pixel perfect consistency for all screens and also guide developers how to segment the cells for each screen and animate also.
This grid system also suggests not to take uneven numbers into count.
For eg. - 11.5 px
Color Guidelines
Poppins Typeface
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1234567890!
CX Feed
Feed screen shows portfolio, accounts, customer journey and NPS changes for portfolios and accounts. It helps user to map the journey on various touch points
Portfolio Analytics
It shows the group of accounts and customer journey based on data metrics
Operational Drivers
Its shows the KPI impact based on varied metrics on each KPI.
Product Roadmap
In the entire process this have been seen how data influence CX which generate the value of insight for business and through the AI prediction able to determine impact level and business decisions.
Next Steps ----
> The scorecard based on the impact on portfolio / accounts
> Collaboration of teammates
> More traffic on dynamic feed
> More accuracy on AI analytics
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Hey! Looking for full-time opportunities.
Feel free to contact me. I'd be happy to collaborate.
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