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WHATSAPP ︎

Chib-bot is a new way for users to send
money through WhatsApp




Chib-bot is a WhatsApp based bot designed to conduct money transfers within Chib, an online banking service. All transfers are conducted securely through text.


Metrics
As a result of my design iterations and implementations,
we noticed the following performance increases:


43%        ︎︎︎  in user activity

       39%        ︎︎︎  in overall transfers

     32%        ︎︎︎  in register invites

           73%        ︎︎︎  in ticket optimization






Problem

Too many transfers for one team to handle

Chib is a money transferring platform that assists users in sending remittance to family via our web, app, and messaging portals. As Chib’s user base began to grow, our communications team had increasing difficulties being able to attend to every user’s need via messaging.

It was clear that it was time for us to expand Chib to include a new messaging system that could attend to common user requests and queries.




“How can we simplify money transfers within WhatsApp to alieviate our communication team’s workload?”







Solution

A Chat-bot for money
transference needs

I designed for Phase I and II of Chib’s DTC Chat systems, using research to explore and address common user frustrations, and using API bot integration through WhatsApp to design an internal messaging system.

Chib-bot as designed in Whatsapp has the ability to

                                                    01    Conduct monetary transfers
                                                    02    Answer customer queries
                                                    03    Provide transference history
                                                    04    Deliver notifications




View your balance, make transfers,
and invite friends to register



All without leaving WhatsApp.






Main Goals

To understand user perceptions and motivations for utilizing customer support by evaluating user and business needs






User needs

01
Discover the main reasons why users
choose
to use our over-the-phone
assistance line.

02
Scale down
our findings to only the
user essentials for our MVP.


03
Understand
the typical user walkthrough
for conducting money transfers with Chib

Business needs

01
Differentiate
between issues that are
best resolved via bot and which are best
suited to the communications team.

02
Keep our bot’s branding consistent with
the language, design, and functionality of Chib.

03
Discover limitations
and advantages of
designing within WhatsApp’s API






What is the ideal interaction
model that would minimize
user’s struggles and prevent
an overwhelmed
communications team?






Hypotheses
Key questions for our research




📱 What are the most prevalent reasons that users are utilizing our over-the-phone assistance line?

🤖 Which issues are best resolved via bot and which are more suited to the communications team?
🤔 How can we resolve these struggles given the limitations and advantages of designing within WhatsApp’s API?




White paper research
I wrote a report detailing information on 
WhatsApp’s API in relation to functionalities
that we need to know before designing



01
Learning how to prevent
common WA based errors



02
Knowledge of API constraints,
ex. bot communication is
limited to action/trigger
words and numbers
03
Understanding of common
conversational flows






Changing direction
A Pivot

User Interviews → Ticket Synthesis

User Interviews were initially selected as the best method for determining user motivations, where we could speak with users and our communications team directly.

However, we eventually decided on conducting analysis using support tickets, or records from the communications team describing incidents reported to them from users.


Why did we choose this method?

Synthesizing ticket reports from the communications team was time effective, at no excess cost, and most importantly, fallowed us to view a history of documented user problems (rather than risking error by asking users to recall them by memory).





Primary research
Support Ticket Synthesis
(n = 808)



Process




1. Gathering and organizing all
our ticket data in one place


In total, we pooled reports together to find
that 1,582 independenct users were listed
as having used our WhatsApp service






2. Omitting irrelevant data


Such as tickets that got mixed with that of
outside teams, (engineering team, graphic
design team, etc)., accidental repeats of
tickets, QA test users, and reports with key
missing information (n = 808).






3. Converting data into
descriptive statistics


Data sets were then converted into
nominal data, with consideration taken to
calculate(1) Frequency distribution and
(2) Measure of central tendency (mode).







4. Data Visualization

Providing graphics depicting our findings






Key research insights
Users mainly utilized Chib’s WhatsApp
communications team for the following reasons




🧠
Agent Assistance

To speak directly to agents over account issues because they were already familiar with WhatsApp (35.5%)

📖 Transference

Ability to conduct processes relating to transfers via WhatsApp was done because it was easy to share with friends & family (48%)
⌨️
Balance Overview


To view their balance because it
did not require having to log in using the web or app (20.9%)





digital architecture

User Flowchart
Mapping out our conversational design into something 
more tangible and cohesive for engineers.




Tracking output dialogue was the most important part of documentation, with inputs limited to specific numbers and variations of key words.

Focus was placed on three main inputs for our user to choose from that divulge into different actions.








prototyping

Flows and UI Visuals
Mock up samples were designed in order to present to
our clients what our future rollout would look like.




Prototypes were categorized as either part of the general flow or as error screens, using WhatsApp’s system design for the UI design.

One of the most important aspects of this rollout was the organization of Figma prototypes to include descriptors, states, experiences, flows, and engineering notes. This allowed engineers assigned to other projects to jump in with minimal context if necessary.







system design

UI
Abiding guidelines



Because this was an API heavy project, visual design was predetermined by WhatsApp’s existing system design. Care was taken to rebuild the WhatsApp library in Figma to include guidelines for margins, typography, colors, spacing, layouts, and components. 

Abiding and localizing existing UI in Figma was essential for not only creating prototypes, but also campaign designs.




Elements of WhatsApp’s Branding







WHATSAPP ︎

How it works



Simplifying money transference with Chib-bot














Balance

Users can view their balance,
taking into account different
currencies and best exchange rates






















Transfer

Make an instant transfer to people within your circle, all without leaving WhatsApp













Customer Service

Contact an agent directly to recieve assistence for any qualms or queries





















Recommend

Recommending Chib to friends is easy - just send our bot their way to help them register









Bonus

Considerations for a final handoff






Design Team



Before and after autolayout
Organizing & updating all designs and templates


Research Team



Sample of final findings
Summary of report & data sorting for future researchers to be able to replicate and analyze our study






Takeaways

Impact 



43%        ︎︎︎  in user activity
39%        ︎︎︎  in overall transfers
32%        ︎︎︎  in register invites
73%        ︎︎︎  in ticket optimization

Personal︎



1 Steph believes in keeping tech design accessable and transparent, so if you have any questions regarding any designs, just send an email and I’ll be sure to get back to you!




Citations


Nair, S. (2022, February 9). Designing a WhatsApp chatbot? Designing a WhatsApp Chatbot? Retrieved August 29, 2022, from https://www.haptik.ai/blog/designing-whatsapp-chatbot

Twilio. (n.d.). Conversations api. Twilio. Retrieved August 29, 2022, from https://www.twilio.com/messaging/conversations-api

Twilio. (n.d.). Programmable messaging API. Twilio. Retrieved August 29, 2022, from https://www.twilio.com/messaging/programmable-messaging-api













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